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Author SHA1 Message Date
Daichi Narushima 1ffac45d57 feat: add publish_grafana_copy, Grafana examples, and optional OTel metrics (#89)
* feat: Grafana copy publishing, dashboard examples, and optional OTel metrics

Implements three observability improvements:

#82 — publish_grafana_copy(): Uses SQLite online backup API (WAL-safe) to
atomically publish a consistent read-only copy beside the target. Adds
--publish-copy option to grafana-schema and snapshot CLI commands.

#83 — examples/grafana/: Minimal working Grafana setup with docker-compose,
provisioning datasource/dashboard YAML, and three dashboard JSON files
(mt5cli-overview, mt5cli-trades, mt5cli-market). All queries use grafana_*
views; no credentials or private paths included.

#84 — mt5cli/telemetry.py: Optional OTel metrics behind mt5cli[otel] extra.
Base install is unaffected. Adds _Mt5Metrics singleton (no-op until
configure_metrics() is called), wraps update_history() and
update_observability() with record_history_update / record_snapshot_update
context managers, and emits account/position gauges from snapshots.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: replace ambiguous multiplication sign in comment

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: normalize markdown formatting in grafana README

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: preserve file mode on Grafana copy and fix unsupported time macro

- publish_grafana_copy: chmod temp file to match the existing target's
  permissions (or 0o644 when no prior target exists) before atomic
  replace, so Grafana running as a different OS user (e.g. UID 472 in
  Docker) can read the published database
- mt5cli-market.json: replace unsupported \$__timeFilter(time) with the
  epoch-based filter supported by frser-sqlite-datasource:
  "time" >= \$__from / 1000 AND "time" < \$__to / 1000

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: skip Windows-incompatible mode test, rename compose file to compose.yaml

- Skip test_overwrite_preserves_existing_target_mode on win32 since
  Windows chmod does not preserve Unix group/other permission bits
- Simplify test_fresh_target_has_readable_permissions to check owner
  read bit only (portable across platforms)
- Rename docker-compose.yml -> compose.yaml (modern Compose convention)
- Update README and test reference to match new filename

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: rename *.yaml to *.yml in examples/grafana

Renames compose.yaml, mt5cli-sqlite.yaml, and mt5cli.yaml to .yml;
updates README and test references accordingly.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: format Grafana dashboards and expand qa script to include JSON

- Update qa.sh prettier pattern to format JSON files alongside markdown
- Reformat Grafana dashboard JSONs with consistent spacing

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: address owner review comments before merge

- qa.sh: fix Prettier glob from `{,d,json}` to `{md,json}` so Markdown
  files are actually formatted by local QA (P2)
- compose.yml: add GF_INSTALL_PLUGINS env var so the frser-sqlite-datasource
  plugin is installed at container start (P1)
- telemetry.py: replace no-op get_meter() call with a real SDK MeterProvider
  pipeline; add optional `readers` kwarg so callers can inject custom readers
  (e.g. InMemoryMetricReader in tests) without needing the OTLP package (P1)
- sdk.py: aggregate profit and volume by symbol before emitting gauge values
  so hedging accounts with multiple same-symbol positions emit one point per
  symbol instead of overwriting with each row (P2)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: emit mt5_history_update_rows_total via conn.total_changes delta

The counter was registered but never incremented, making the advertised
history-update throughput metric permanently zero. Add add_history_rows()
to _Mt5Metrics and call it in update_history() using the SQLite
total_changes delta measured around write_incremental_datasets().

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: address three owner review comments

- compose.yml: replace soft fallback with :? error expansion so Compose
  refuses to start when MT5CLI_DB_PATH is unset or empty (P1)
- README.md: tell native Windows users to copy only the datasource
  provisioning file; the dashboards yml contains a Docker-specific path
  that is invalid on Windows (P2)
- telemetry.py / sdk.py: emit mt5_terminal_connected,
  mt5_terminal_trade_allowed, and mt5_terminal_trade_expert gauges via a
  new record_terminal_state() method called from _snapshot_terminal(),
  completing the connection-status metric surface from issue #84 (P2)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat: add snapshot freshness panel and win-rate column to dashboards

- mt5cli-overview.json: add a full-width "Last Snapshot" stat panel
  (dateTimeFromNow unit) below the account stats, querying
  MAX(time)*1000 from grafana_account_snapshots so users can tell
  whether Grafana is reading a current published copy (#83)
- mt5cli-trades.json: add win_rate_pct computed column to the Trade
  Statistics by Symbol table via 100.0 * winning_deals / NULLIF(
  total_deals, 0), with a percent unit override and "Win Rate (%)"
  display label (#83)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: reject same source and target path in publish_grafana_copy

Adds an early same-path guard to publish_grafana_copy: resolves both
paths before any I/O and raises ValueError if they are identical,
preventing the function from overwriting the live source database with
its own backup copy. Also adds a unit test for the rejected case.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: address ruff EM102/TRY003/E501 in same-path guard

Assigns the ValueError message to a variable before raising and
shortens the test docstring to stay within the 88-char line limit.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: apply ruff format to publish_grafana_copy error message

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: remove grafana_ticks panel from default market dashboard

The Tick Bid/Ask panel queried grafana_ticks which only exists when users
collect tick data (opt-in). Users following the default OHLCV-only setup
path hit "no such table: grafana_ticks" on dashboard load.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: close SQLite connections before atomic replace in publish_grafana_copy

Wrap both src and dst connections with contextlib.closing() so they are
explicitly closed before tmp_path.replace(target_path) runs. Without
this, sqlite3.Connection's context manager only commits/rolls back but
leaves the file handle open, which can cause PermissionError on Windows.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: rename history.grafana.db to history.mt5cli.db in Grafana examples

frser-sqlite-datasource blocks paths containing "grafana.db" via its
internal blocklist. Rename the recommended published filename in the
README, compose comment, and datasource provisioning comment to avoid
a blocked/denied datasource for native Windows users.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: update Docker Compose quick-start to pass MT5CLI_DB_PATH

The compose.yml already required MT5CLI_DB_PATH via ${MT5CLI_DB_PATH:?...},
but the README still showed bare `docker compose up -d`. Update the section
to show the env-var-prefixed invocation and document the .env file alternative.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-28 17:14:17 +09:00
Daichi Narushima d27da02f3f feat: add Grafana-ready SQLite observability (#86)
* feat: add Grafana-ready SQLite observability (#79, #80, #81)

New `mt5cli/grafana.py` module with idempotent DDL helpers:
- `create_snapshot_tables` — five SQLite tables for time-series account,
  position, order, terminal, and run-status snapshots
- `create_grafana_views` — 13 `grafana_*` views with integer epoch-second
  `time` columns; missing source tables emit warnings and are skipped
- `create_grafana_indexes` — 9 performance indexes guarded by column checks
- `ensure_grafana_schema` — convenience wrapper calling all three above
- Insert helpers: `insert_account_snapshot`, `insert_position_snapshots`,
  `insert_order_snapshots`, `insert_terminal_snapshot`, `record_snapshot_run`

New stable SDK exports in `mt5cli.__init__` and `mt5cli.contract`:
- `update_observability` — appends a timestamped snapshot to a SQLite db
  using an already-connected `Mt5DataClient`; never places orders
- `update_observability_with_config` — standalone wrapper that opens and
  closes the MT5 connection automatically

New CLI commands (Collection panel):
- `grafana-schema` — idempotent schema setup, no MT5 connection required
- `snapshot` — append account/position/order/terminal rows; supports
  `--symbol`, `--with-account/--no-account`, and equivalent flags

All public modules maintain 100 % branch coverage; 968 tests pass.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: apply mdformat to docs after grafana observability additions

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: bump version to 1.1.0

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: address PR #86 review feedback

- Fix unaggregated time in grafana_realized_pnl GROUP BY query (MAX)
- Replace O(N) per-symbol API calls with single call + client-side filter
- Eliminate double create_snapshot_tables when with_grafana_schema=True
- Move grafana imports to module level in sdk.py (remove PLC0415 noqa)
- Default with_grafana_schema to False (run grafana-schema once for setup)
- Fix README position example to use snapshot_runs for latest snapshot
- Update tests to reflect new behavior and correct patch targets

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: apply ruff formatting and sync lock file

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: address owner review feedback on PR #86

- Filter grafana_*_snapshots views to only expose rows from successful
  runs (JOIN snapshot_runs WHERE status='ok'), closing the partial-snapshot
  visibility gap raised in PRRT_kwDORzI_286MvDJ6
- Add issubset column guards for snapshot table index creation, consistent
  with the rest of create_grafana_indexes (PRRT_kwDORzI_286MvUx1)
- Fix README example queries: views expose 'time' not 'observed_at'
  (PRRT_kwDORzI_286MvUxw)
- Correct public-contract.md default for with_grafana_schema (False, not
  True) and point to grafana-schema command (PRRT_kwDORzI_286MvUxy)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: add run_id to snapshot schema and fix stale-positions README query

Replace second-level observed_at as the join key between snapshot_runs
and snapshot tables with a stable run_id INTEGER PRIMARY KEY. Two runs
in the same second now get distinct run_ids, preventing view duplication
and cross-contamination from a failed run. Update README example to use
snapshot_runs for latest-snapshot lookup so zero-position runs return an
empty result instead of stale rows.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: format markdown tables

Align table column widths in README and public-contract documentation.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

* fix: close sqlite connections deterministically

* fix: require entry filter in grafana_realized_pnl and add time to grafana_trade_stats

grafana_realized_pnl now requires the entry column and filters to
close-side deals (entry IN (1, 2, 3)), consistent with grafana_symbol_pnl
and grafana_trade_stats. grafana_trade_stats now requires the time column
and emits MAX(time_expr) AS "time" so it satisfies the documented Grafana
view contract (integer epoch-second time column throughout).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: normalize pd.Timestamp time_setup to epoch int in insert_order_snapshots

orders_get_as_df() returns datetime-converted columns by default, so
time_setup is a pd.Timestamp in normal use. Passing it directly to
sqlite3.executemany raises ProgrammingError. Added _to_epoch_int helper
that converts datetime.datetime subclasses (including pd.Timestamp) and
raw int/float values to integer epoch seconds, returning None for other
types. Regression tests cover all four input paths.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: pre-drop all grafana_* views at start of create_grafana_views

Previously, a builder that skipped due to a missing source table or column
would not drop the view it owned, leaving stale views referencing gone
tables. Now create_grafana_views drops all 13 known grafana_* views before
calling any builder, so a schema refresh always removes views whose source
has disappeared. Regression test covers the create → drop-source → refresh
cycle.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: expose run_id in snapshot views and drop time from summary views

Grafana snapshot views now expose run_id so latest-state queries can use
MAX(run_id) instead of the ambiguous second-level MAX(observed_at).
grafana_realized_pnl and grafana_trade_stats lose their MAX(time) column
and are reclassified as static summary views; their all-time aggregates
are not filterable by Grafana time-range selectors.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: guard snapshot views against missing run_id and fix README view docs

_build_snapshot_view now skips with a warning when the underlying
snapshot table exists but lacks a run_id column, preventing a broken
view that fails at query time. Adds a regression test for that path.

README Grafana section now qualifies that grafana_realized_pnl and
grafana_trade_stats are static summary views (no time column) and splits
the view table to match docs/api/public-contract.md.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-28 07:55:26 +09:00
Daichi Narushima 4bc36d09d2 fix: add copy_rates_from_pos_as_df fallback for trading client rate fetch (#88)
* fix: add copy_rates_from_pos_as_df fallback in fetch_latest_closed_rates_for_trading_client

Mt5DataClient (returned by create_trading_client) exposes copy_rates_from_pos_as_df,
not fetch_latest_rates_as_df. Adds a fallback path that resolves the granularity string
to an integer timeframe via parse_timeframe, fetches count+1 bars from start_pos=0,
and applies the same drop_forming_rate_bar + tail(count) logic so callers that use
the client returned by create_trading_client no longer need a compatibility shim.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Bump version to v1.0.3

* fix: hoist parse_timeframe before dispatch and add invalid-granularity test

Hoisting parse_timeframe(granularity) before the fetch_latest_rates_as_df /
copy_rates_from_pos_as_df dispatch ensures invalid granularity strings fail
consistently on both paths with a clear ValueError, rather than only when
the fallback branch is taken.

Adds test_copy_rates_from_pos_fallback_raises_on_invalid_granularity to pin
the early-validation contract and confirm the underlying method is never called.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-28 07:18:54 +09:00
dceoy 3a126ced30 BUmp version to 1.0.2 2026-06-28 06:08:21 +09:00
Daichi Narushima 80c3f3f65e Make ticks dataset opt-in for collect-history (#87)
* feat: make SQLite tick history opt-in for collect-history

Ticks can grow SQLite databases quickly, so they are excluded from the
default dataset selection. The new DEFAULT_HISTORY_DATASETS constant
(rates, history-orders, history-deals) drives resolve_history_datasets(None),
collect_history(), and update_history(). Callers must pass
--dataset ticks (CLI) or datasets={Dataset.ticks} (SDK) to include ticks.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ALK71tg75JWrrCKaiShb7b

* chore: reformat docs/index.md table column widths

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ALK71tg75JWrrCKaiShb7b

* fix: update stale docstrings and tighten CLI None check

- update_history and ThrottledHistoryUpdater.__init__ docstrings now
  state that ticks are opt-in, matching collect_history's wording
- cli.py collect-history uses `is not None` for explicit empty-list safety

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ALK71tg75JWrrCKaiShb7b

* docs: update README collect-history to reflect ticks opt-in default

The command table and section intro previously stated ticks were
collected by default ("all four", "rates, ticks, history-orders, and
history-deals"). Both now reflect the new default (rates, history-orders,
history-deals) and note that --dataset ticks is required to include ticks.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ALK71tg75JWrrCKaiShb7b

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-28 06:00:26 +09:00
Daichi Narushima 43f632bc40 Reorganize CLI help text and command grouping for data/execution clarity (#85)
* feat: clarify CLI/docs scope as generic MT5 data and execution infrastructure

- Update app help text and module docstring to describe mt5cli as MT5 data
  and execution utilities rather than export-only tooling
- Group CLI commands under rich_help_panel sections: Data / Export, Execution,
  and Collection; command names are unchanged for compatibility
- Expand order-send docstring to explicitly flag it as the expert raw-request
  live-trading path; preserve --yes gate
- Split docs/index.md Trading section into "Trading State" (read-only) and
  "Execution (live / mutating)" with close-positions now documented
- Add TestHelpText tests verifying top-level panel grouping, order-send
  expert/live language, and close-positions safety gate coverage

Closes #78

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018yH6esaqc5D1cmo1dK2Ur9

* chore: trim trailing whitespace in docs/index.md table

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018yH6esaqc5D1cmo1dK2Ur9

* chore: bump version to 1.0.1

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018yH6esaqc5D1cmo1dK2Ur9

* chore: update uv.lock for version 1.0.1

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018yH6esaqc5D1cmo1dK2Ur9

* fix: address review feedback on CLI/docs scope PR

- Remove dead help invocation in test_order_send_help_mentions_expert_and_raw
  (the result was immediately overwritten by result2)
- Strengthen assertion from `or` to `and`; both "raw" and "expert" are present
  in the docstring so disjunction masked a potential regression
- Split into two `assert` statements to satisfy PT018 (ruff)
- Fix docs/index.md inaccuracy: order-check has no --yes gate; clarify that
  only order-send and close-positions require confirmation for live execution
- Move order-check from "Execution" rich_help_panel to "Data / Export" so the
  Execution panel name is truthful (order-check is read-only)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018yH6esaqc5D1cmo1dK2Ur9

* docs: move order-check out of Execution section into Trading State

order-check is read-only and now lives in the CLI's Data / Export panel,
so documenting it under "Execution (live / mutating)" was inconsistent.
Moved it to the Trading State table. The Execution section now only lists
order-send and close-positions, both of which require --yes.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018yH6esaqc5D1cmo1dK2Ur9

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-28 01:23:17 +09:00
dceoy 8028263b24 docs: format public contract table
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-27 02:04:29 +09:00
dceoy 63a8d67419 chore: bump version to 1.0.0
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-27 02:03:46 +09:00
Daichi Narushima 93565681e1 fix: decouple mt5cli from pdmt5 high-level trading helpers (#76)
* fix: decouple mt5cli from pdmt5 high-level trading helpers

- Replace Mt5TradingClient type annotations with internal _Mt5ClientProtocol
- Lazy-import Mt5TradingClient in create_trading_client to avoid hard dependency
- Replace Mt5TradingError with Mt5OperationError in mt5cli validation paths
- Update exception handling to support future pdmt5 versions without Mt5TradingError
- Add test to enforce that mt5cli doesn't import high-level symbols at module level
- Update documentation to clarify dependency boundaries

mt5cli now relies only on low-level MT5 primitives:
- Mt5Config for configuration
- Mt5RuntimeError for runtime errors
- Raw MT5 methods (order_send, order_check, account_info, etc.)

This aligns with pdmt5's direction to remove high-level trading helpers and focus
on low-level MT5 access plus DataFrame/dict conversion.

Fixes #75 (dceoy/mt5cli#75)

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PcGVFTVgyqzse3LLw38ber

* fix: address PR #76 review feedback on pdmt5 decoupling

- Replace Mt5TradingClient with Mt5DataClient in create_trading_client()
  so the function no longer depends on the high-level trading client
- Fix _RECOVERABLE_MT5_ERRORS in exceptions.py to use tuple unpacking
  form, removing the incorrect ternary assignment
- Add pragma: no cover to except ImportError branches in exceptions.py
  and sdk.py (dead code when pdmt5 is installed)
- Switch coverage exclude_lines to exclude_also so the default
  pragma: no cover pattern is preserved; also exclude bare ... stubs
  (Protocol method bodies) from coverage
- Correct inaccurate note in docs/api/public-contract.md: Mt5TradingClient
  is no longer required internally; Mt5TradingError is conditionally
  available but mt5cli raises Mt5OperationError for trading failures
- Update all mock patches from pdmt5.Mt5TradingClient to
  mt5cli.trading.Mt5DataClient to match the new module-level import

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-26 22:26:54 +09:00
Daichi Narushima f435544f07 Shrink public API surface and remove storage re-export module (#74) 2026-06-26 18:23:30 +09:00
Daichi Narushima 668f38d8aa feat: reduce package-root API surface and require pdmt5>=1.0.0 (closes #70) (#73) 2026-06-26 12:08:00 +09:00
dceoy 8da5ee9242 Bump version to v0.9.7
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-25 14:10:23 +09:00
Daichi Narushima 9dbb46fbb1 feat: make pyarrow optional via mt5cli[parquet] extra (#69) 2026-06-25 14:03:24 +09:00
Daichi Narushima dfe80ce500 feat: add close-positions CLI and replace_symbol projection mode (#65 #66) (#67)
* feat: add close-positions CLI command and replace_symbol projection mode (#65 #66)

Part 1 — close-positions CLI (#65):
- Add `close-positions` subcommand delegating to `close_open_positions()`.
- Accepts repeated `--symbol` and `--ticket` filters (AND semantics).
- Supports `--dry-run` (no `--yes` required); live execution requires `--yes`.
- Fails closed with `BadParameter` when neither `--symbol` nor `--ticket` is given.
- Exports normalized `OrderExecutionResult` list as a DataFrame (request/response
  serialized as JSON strings for clean CSV/JSON/Parquet/SQLite output).
- `order-send` remains the raw expert path; `close-positions` is the safer
  high-level helper that builds correct close requests automatically.

Part 2 — ProjectionMode and replace_symbol (#66):
- Add `ProjectionMode = Literal["add", "replace_symbol"]` type alias.
- Add optional `projection_mode` parameter to `calculate_symbol_group_margin_ratio`.
  Default `"add"` preserves existing additive behavior.
  `"replace_symbol"` subtracts current margin for `new_symbol`, then adds
  candidate margin — the subtraction and addition are atomic (suppressed together).
- Export `ProjectionMode` from `mt5cli` and add to `STABLE_SDK_EXPORTS`.
- No mteor-specific strategy, risk-threshold, or policy logic added.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: remove unused ProjectionMode import in test_contracts.py

The parametrized test_stable_exports_are_importable_from_package_root
already covers ProjectionMode via hasattr(mt5cli, name). Ruff correctly
flagged the explicit top-level import as unused (F401).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Bump version to v0.9.6

* fix: address PR #67 review feedback

- Floor replace_symbol margin subtraction at zero to prevent negative ratio
- Serialize response unconditionally via json.dumps (null for dry-run rows)
- Return a schema-preserving empty DataFrame when results list is empty
- Add test: --dry-run --yes precedence (dry-run wins, no order_send)
- Add test: zero-match filter produces empty JSON array with exit 0
- Move projection_mode prose to stable trading section in docs

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* feat: add runtime validation for projection_mode in calculate_symbol_group_margin_ratio

Unsupported values previously silently fell through as "add". The new
_validate_projection_mode helper raises ValueError with a message that
names the bad value and the two accepted modes.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-25 10:39:49 +09:00
Daichi Narushima 15bfd17db3 test: reduce test_trading.py duplication with parametrize (#64)
* test: reduce test_trading.py duplication with parametrize

Collapse repetitive individual tests in test_trading.py into
parametrized equivalents, cutting 267 lines without losing any cases.

- TestExtractTickPrice: 13 tests → 2 parametrized (×3 valid, ×10 None)
- TestEstimateOrderMargin: 4 invalid-margin tests → 1 parametrized ×4;
  nan/inf volume tests → 1 parametrized ×2
- TestNormalizeOrderVolume: multi-assert bodies split into parametrized
  cases for non-finite volume and constraints
- TestVolumeAndExecution: 9 place_market_order retcode tests → 1 ×11;
  5 update_sltp retcode tests → 1 ×5
- test_calculate_trailing_stop_updates_missing_symbol_digits:
  inline double-assert body → 1 parametrized ×2

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* test: further reduce test_trading.py duplication with parametrize

Merge six broker stop-level tests into two parametrized tests, collapse
two default-digits fallback tests and three symbol-filter zero-margin
tests into one each.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* test: address claude[bot] review on PR #64

- Consolidate _MISSING_RETCODE sentinel to one line with corrected comment
- Add comment explaining ids list is required for deterministic node IDs
- Document intentional narrower retcode coverage in update_sltp test

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* test: reduce duplication in test_sdk, test_history, test_contracts

- TestBuildConfigWholeDollarEnv: 3 field tests (server/password/path) → 1
  parametrized ×3
- TestResolveAccountSpec: whole-dollar expand/no-expand pair → 1 parametrized ×2
- test_normalize_mt5_exception_maps_types: 2 isinstance asserts → parametrized ×2
- test_resolve_history_tick_flags_invalid: 2 pytest.raises blocks → parametrized ×2

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-25 01:55:04 +09:00
Daichi Narushima 37eef16e99 feat: support string login in build_config and add substitute_mapping_values (#63)
* feat: support string login in build_config and add substitute_mapping_values (#61, #62)

Extend build_config() to accept login: int | str | None. String logins
are coerced via the existing coerce_login() helper (empty/whitespace →
None, numeric strings → int, non-numeric → ValueError). When
allow_whole_dollar_env=True, ${ENV} and $ENV placeholders are expanded
before coercion, consistent with path/password/server behavior.

Add substitute_mapping_values(), a generic recursive helper that
substitutes environment placeholders in nested dicts/lists only for
caller-selected mapping keys. Non-selected fields (including literal
dollar signs) are preserved exactly. Supports blank_string_keys_as_none
to normalise empty strings to None after substitution. No application-
specific key names (e.g. mt5_login) are hard-coded in mt5cli.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Bump version to v0.9.5

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs+test: clarify substitute_mapping_values docstring and pin tuple behaviour

- Adds sentence noting list-element strings are never substituted (only
  immediate dict values are), addressing reviewer finding #1.
- Rewrites Returns section to accurately describe scalar pass-through
  behaviour, addressing reviewer finding #2.
- Adds recursion-depth caveat to the generic-utility docstring,
  addressing reviewer finding #4.
- Adds test_tuple_container_not_traversed to pin the existing silent
  tuple-exclusion contract, addressing reviewer finding #3.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* docs: update public contract and README for build_config login coercion and substitute_mapping_values

- Expands build_config row to document login: int | str | None,
  numeric-string coercion, blank-string handling, and env placeholder
  expansion when allow_whole_dollar_env=True.
- Adds substitute_mapping_values to the stable SDK table with a note
  that key names are never hard-coded in mt5cli.
- Extends allow_whole_dollar_env paragraph to list substitute_mapping_values.
- README: adds build_config env-placeholder example and imports to the
  trading lifecycle snippet.
- README: extends credential-resolution bullet with a substitute_mapping_values
  usage example using generic key names.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-25 01:04:32 +09:00
Daichi Narushima 96c75f7852 Add account-wide projected margin ratio helper (#60)
* feat: add account projected margin ratio helper

* Bump version to v0.9.4

* fix: address account margin ratio review feedback

* fix: simplify account margin ratio errors
2026-06-24 03:43:52 +09:00
Daichi Narushima 292fac899a Add generic trading helpers and reduce public API tiers (#58)
* feat: add generic trading helpers and API tiers

* Bump version to v0.9.3

* fix: require symbol digits for trailing stops

* fix: allow side-specific trailing stop ticks

* test: enforce complete public export tiers

* docs: align public contract tiers

* refactor: remove legacy public supports
2026-06-24 01:58:32 +09:00
Daichi Narushima 9ac3b885c3 test: add explicit unit tests for calculate_positions_margin_by_symbol and calculate_positions_margin_safe (#50) (#53)
* test: add explicit unit tests for calculate_positions_margin_by_symbol and calculate_positions_margin_safe (#50)

Covers all acceptance criteria: partial failure with warning log, all-fail,
empty symbol list with no-broker-call assertion, duplicate deduplication,
successful aggregation with first-seen key order, suppress_errors=False
propagation, and three calculate_positions_margin_safe cases (partial skip,
all-fail → 0.0, empty list → 0.0).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* test: fix warning log assertion and parametrize suppress_errors=False test

- Use record.getMessage() + levelno check instead of record.message, which
  is only populated after formatting and can return an empty string.
- Parametrize test_one_symbol_fails_suppress_errors_false over all three
  exception types caught by the implementation (Mt5TradingError,
  Mt5RuntimeError, AttributeError) so any future narrowing of the except
  tuple would be caught by tests.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* style: shorten docstring to fit 88-char line limit

* style: shorten docstring to fit 88-char line limit

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-23 21:41:30 +09:00
Daichi Narushima 823cb5b0a4 Revert "Bump version to v0.9.3 (#51)" (#52)
This reverts commit f1ada55bce.
2026-06-23 19:17:42 +09:00
agent 1c57be5c44 fix: centralize tick price validation in calculate_spread_ratio and determine_order_limits (#52)
Replaces manual isinstance/<=0 checks in calculate_spread_ratio() and
determine_order_limits() with _valid_tick_price(), ensuring NaN, inf,
-inf, zero, negative, bool, and invalid-string tick values are
consistently rejected across all trading helpers.

Adds regression tests covering numeric-string acceptance and every
invalid-value category for both functions.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-23 09:48:13 +00:00
Daichi Narushima f1ada55bce Bump version to v0.9.3 (#51) 2026-06-23 18:30:18 +09:00
agent d292fbb9d9 feat: centralize tick price validation and add resilient position margin helpers (#49, #50)
Add _valid_tick_price() internal helper that returns a positive finite float
from a tick dict or None for any invalid value (missing, None, NaN, infinite,
zero, negative, or unsupported type). Refactor five existing bid/ask validation
sites in trading.py to use it, removing duplicated isinstance/isfinite checks.

Add calculate_positions_margin_by_symbol() which computes margin per unique
symbol independently using the existing strict calculate_positions_margin(),
with first-seen deduplication and configurable error suppression
(Mt5TradingError, Mt5RuntimeError, AttributeError) via suppress_errors=.

Add calculate_positions_margin_safe() as a thin sum wrapper with
suppress_errors=True, returning 0.0 on empty or fully-failed inputs.

Both new helpers are exported from mt5cli, added to STABLE_SDK_EXPORTS, and
documented in docs/api/public-contract.md. Existing strict behavior of
calculate_positions_margin() is unchanged.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-23 07:30:02 +00:00
Daichi Narushima 8e53212a24 fix: always use mt5cli calculate_volume_by_margin to prevent LACK OF FUNDS (#48) 2026-06-23 14:01:46 +09:00
Daichi Narushima b878a61c07 fix: re-verify normalized volume margin in calculate_volume_by_margin (#46)
* fix: re-verify normalized volume margin before returning from calculate_volume_by_margin

For CFDs, index products, and tiered-margin instruments, the initial
min-lot margin estimate can be optimistic; the normalized stepped volume
may require more margin than available_margin.  After computing the
normalized volume, step down by volume_step until order_calc_margin
confirms affordability, or return 0.0 if no step is affordable.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* test: fix ruff line-length violations in calculate_volume_by_margin tests

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: use integer step index and add actual>0 guard in calculate_volume_by_margin

Replace float-subtraction loop with integer step index to eliminate
accumulation rounding error and add `actual > 0` guard so a broker
returning zero/negative margin is never accepted as affordable.
Inline `capped` to keep local-variable count within Ruff PLR0914 limit.
Update docstring to reflect re-verification behaviour and 0.0 fallback.
Tighten test assertion from `volume > 0` to the symbol's valid range.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Bump version to v0.9.1

* perf: replace linear step-down scan with binary search in calculate_volume_by_margin

Resolves the P2 review finding: the previous O(n) loop called
order_calc_margin once per volume step, making sizing appear hung for
symbols with a large step range or small volume_step.

Binary search over the integer step index finds the largest affordable
step in O(log n) IPC calls (≈17 for a 99 999-step range vs up to 99 999
in the worst case). Monotonicity of broker margin with volume is assumed,
which holds for standard linear margin schedules.

To stay within the PLR0914 local-variable limit the steps variable is
inlined into hi and the tick temporary is eliminated by accessing the
snapshot dict directly. Error messages still go via msg to satisfy EM102.

Two existing tests are updated to match the binary-search call sequence.
A new regression test (volume_min=0.01, volume_max=1000.0) configures
a tiered-margin mock with its threshold at step 50000 and asserts that
the total order_calc_margin call count does not exceed 25.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: remove obsolete TC003 per-file-ignore for history.py

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: agent <agent@localhost>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-23 04:40:00 +09:00
dceoy 0610ea732c fix: handle NumPy object rate timestamps 2026-06-22 23:01:31 +09:00
Daichi Narushima 82a39731ed feat: add fetch_latest_closed_rates_indexed and allow_whole_dollar_env opt-in (#45)
* feat: add fetch_latest_closed_rates_indexed and allow_whole_dollar_env opt-in (#43, #44)

Closes #43: add fetch_latest_closed_rates_indexed(client, *, symbol,
granularity, count) -> pd.DataFrame to mt5cli/trading.py. Internally
reuses fetch_latest_closed_rates_for_trading_client(), converts the
"time" column to a UTC-aware DatetimeIndex named "time", and drops the
original column. Exported from trading.__all__, mt5cli.__init__, and
STABLE_SDK_EXPORTS.

Closes #44: extend substitute_env_placeholders() with opt-in
allow_whole_dollar_env=False that expands whole-value $ENV_NAME strings
(entire string must be exactly $IDENTIFIER). Threaded through
build_config(), resolve_account_spec(), and resolve_account_specs() with
the same default=False. Partial strings like "plan$pass", "abc$ENV", or
"$ENV-suffix" are never expanded.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* chore: align Markdown table columns in docs and skill file

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: treat numeric (float64) epoch seconds as UTC in _rate_time_to_utc

After DataFrame concat or NA upcast the time column becomes float64, which
is still epoch seconds. Using is_numeric_dtype instead of is_integer_dtype
fixes the silent misalignment. Using series.to_numpy() before passing to
pd.to_datetime avoids the redundant pd.DatetimeIndex() wrapper and aligns
with how existing rate-time normalization in schemas.py handles numeric
timestamps.

Add test_converts_float_epoch_seconds_to_utc_datetime_index to cover the
regression. Add a doc note clarifying that build_config cannot expand
login since that parameter is int | None.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: reject NaT values after rate timestamp conversion in _rate_time_to_utc

pd.to_datetime() silently produces NaT for None/NaN inputs rather than
raising, so the function could return a DatetimeIndex containing NaT
despite documenting invalid timestamps as a ValueError. Check any(idx.isna())
after conversion and raise with a clear message.

Add test_raises_on_nat_time_column to cover the regression.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* Bump version to v0.9.0

* fix: handle object numeric rate timestamps

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-06-22 22:52:19 +09:00
Daichi Narushima c4a4253fbc feat: stable SDK helpers for volume, margin, and closed bars (#39–#41) (#42)
* feat: add stable SDK helpers for volume, margin, and closed bars (#39, #40, #41)

Expose generic trading utilities in the stable downstream SDK so applications
like mteor can drop local MT5 adapter code:

- normalize_order_volume() for broker step/min/max sizing
- estimate_order_margin() and calculate_positions_margin() for margin totals
- fetch_latest_closed_rates_for_trading_client() for closed bars from Mt5TradingClient

Update STABLE_SDK_EXPORTS, package-root exports, docs, and unit tests.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* chore: bump version to 0.8.3

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: address PR review feedback on volume cap, rate time, and margin grouping

- Re-apply volume_max after step normalization in normalize_order_volume()
- Drop misleading non-time index reset branch in _ensure_rate_time_column()
- Group positions by (symbol, side) before margin estimation
- Add branch-coverage tests for tick price validation and volume cap edge case

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: address remaining PR review threads on docs and DatetimeIndex

- Rename unnamed DatetimeIndex column to time after reset_index()
- Guard estimate_order_margin example on positive normalized volume
- Document calculate_positions_margin skip vs error propagation behavior
- Add test for unnamed DatetimeIndex branch coverage

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: harden stable SDK margin, rate fetch, and volume normalization

- Wrap order_calc_margin conversion and reject None/non-numeric results
- Validate fetched rate objects are DataFrames before time normalization
- Return 0.0 for non-finite volume inputs and constraints in normalize_order_volume

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: reject non-finite volumes in margin estimation helpers

Use _is_positive_finite_number() in estimate_order_margin() and
calculate_positions_margin() so NaN/inf volumes never reach broker calls.
Add focused tests and document non-finite volume skipping in trading.md.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: guard symbol filter in calculate_positions_margin for empty frames

Return 0.0 before filtering when positions are empty or lack a symbol column.
Add regression tests for filtered calls on malformed position frames.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
2026-06-19 01:02:18 +09:00
dceoy 9f2968cc98 Update .agents/skills/pr-feedback-triage/SKILL.md 2026-06-19 00:21:33 +09:00
Daichi Narushima 7de3ce0b7a feat: add injectable update_backend to ThrottledHistoryUpdater (#38)
* feat: add injectable update_backend to ThrottledHistoryUpdater

Allow downstream applications to substitute the history update backend via
the ThrottledHistoryUpdater constructor without monkey-patching
mt5cli.sdk.update_history. Defaults to update_history for backward
compatibility.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* chore: fix lint and format after QA

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* chore: bump version to 0.8.2

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: use explicit None check for ThrottledHistoryUpdater backend

Only None selects the default update_history backend so falsy callable
objects with __bool__ returning False are preserved as custom backends.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
2026-06-18 22:58:09 +09:00
Daichi Narushima 897f7f0a0d docs: stable SDK contract and strategy-neutral order helpers (#37) 2026-06-18 19:12:11 +09:00
Daichi Narushima d156dd7176 [codex] fix mt5 adapter APIs (#36)
* fix mt5 adapter APIs

* address PR feedback

* fix zero ratio minimum volume sizing

* Bump version to v0.8.0
2026-06-15 02:47:05 +09:00
dceoy 307d6f5320 docs: restructure AGENTS.md with concise repository guidance
Align agent instructions with the streamlined project structure, QA workflow, and security notes used elsewhere in the repo.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-14 23:07:13 +09:00
Daichi Narushima 8031389a67 Add GitHub CodeQL analysis to CI workflow (#35)
* chore: add GitHub CodeQL analysis to CI workflow

Enable automated security scanning with GitHub CodeQL to detect potential vulnerabilities in Python code.

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

* chore: run CodeQL analysis on pull requests

Co-authored-by: Cursor <cursoragent@cursor.com>

* Add checks and statuses read permissions for dependabot auto-merge.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Claude Haiku 4.5 <noreply@anthropic.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-14 22:54:28 +09:00
dceoy fdf5e08d31 Add .agents/skills/pr-feedback-triage/SKILL.md 2026-06-14 21:16:52 +09:00
dceoy 254c159ad5 Bump version to v0.7.2 2026-06-13 01:34:03 +09:00
Daichi Narushima 78c49238cf feat: stable MT5Client public API and infrastructure layer (#30)
* feat: add stable MT5Client public API and infrastructure layer

Introduce a reusable public API for downstream trading applications:

- MT5Client as the primary client abstraction with order_check/order_send
- schemas module with DataKind contracts, validation, and normalization
- converters, exceptions, retry, and storage facade modules
- CLI order commands now route through MT5Client
- connected_client made public; retry logic centralized
- Contract tests for API surface, schemas, and storage round-trips
- README and docs updated with Python API usage examples

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: correct time coercion, broker-safe symbols, and execution docs

- Normalize MT5 time columns with correct second/millisecond units
- Coerce all present known MT5 time fields, including optional order times
- Preserve broker symbol casing in normalize_symbol()
- Document order_send() as a live execution primitive with clear scope boundaries
- Add contract tests for timestamp and symbol normalization behavior

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
2026-06-13 01:32:03 +09:00
Daichi Narushima 9356d5dcdf Consolidate duplicated export and history streaming helpers (#29)
* Consolidate duplicated export and history streaming helpers.

Reduce repeated CLI export plumbing, shared per-symbol SQLite writes, and test mock setup without changing public behavior.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Bump version from 0.7.0 to 0.7.1.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-12 23:14:34 +09:00
Daichi Narushima 0fad55d609 Refactor MT5 constant parsing to delegate to pdmt5 >= 0.3.0 (#28)
* Refactor MT5 constant parsing to delegate to pdmt5 >= 0.3.0

Replace local TIMEFRAME_MAP, TICK_FLAG_MAP, and parser helpers with thin
compatibility wrappers around pdmt5. COPY_TICKS flags now use real MT5 values
(ALL=-1, INFO=1, TRADE=2). Click parameter types validate all inputs through
the wrappers. Update tests and docs to describe the pdmt5/mt5cli/mt5api layering.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Fix timeframe defaults and COPY_TICKS flag defaults after pdmt5 migration

Use short timeframe aliases for default history collection and granularity
naming via pdmt5.get_timeframe_name. Set CLI/SDK default tick flags to ALL
(-1) instead of the legacy mt5cli-only value.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Address CI lint failure and PR review feedback

Fix ruff import ordering in history.py. Use ALL string defaults for CLI tick
flags, isolate TICK_FLAG_MAP as a dict snapshot, derive flag names from pdmt5,
reuse TIMEFRAME_NAMES for default history timeframes, and add tests for prefix
stripping and TIMEFRAME_ key filtering.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Bump version to 0.7.0

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
2026-06-11 23:22:50 +09:00
dceoy d654b82f9d Bump version from 0.6.0 to 0.6.1.
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-11 19:36:34 +09:00
Daichi Narushima b5e82e71c7 Add trading session helpers and extend ThrottledHistoryUpdater (#25)
* Add trading session helpers and extend ThrottledHistoryUpdater

Introduce mt5cli.trading with mt5_trading_session() for Mt5TradingClient
lifecycle management and reusable operational helpers for position-side
detection, margin/volume sizing, and protective order price derivation.

Extend ThrottledHistoryUpdater to validate inputs before updates and to
optionally suppress ValueError, OSError, and missing-method errors without
advancing the throttle timestamp.

Export the new helpers from mt5cli.__init__, add unit tests with mocked
clients, and document migration guidance for downstream projects such as
mteor.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Narrow ThrottledHistoryUpdater suppress_errors handling (#27)

* Narrow ThrottledHistoryUpdater suppress_errors for MT5 capability only

Remove broad AttributeError/TypeError handling from recoverable errors.
Add _is_mt5_client_capability_error() to detect missing history API methods
or non-callable client attributes by message and attribute name.

Generic AttributeError/TypeError values always propagate even when
suppress_errors=True. Update docs and tests accordingly.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Detect non-callable history client methods in suppress_errors

Address review feedback: when a history API attribute exists but is not
callable, Python raises a generic TypeError. Inspect the traceback for
mt5cli.history client call sites so these capability mismatches are still
suppressed without matching all TypeError values.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Address PR review feedback on trading helpers

- Resolve history module path once at import time
- Only treat non-callable TypeErrors as capability errors at the raise site
- Validate SL/TP ratios in determine_order_limits
- Add tests for margin_free edge cases, body-raise shutdown, and internal TypeError propagation
- Clarify ThrottledHistoryUpdater suppress_errors docs
- Split README migration example into trading vs read-only history sessions

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* Tighten protective ratio validation and clamp negative margin_free

Add _require_protective_ratio enforcing 0 <= ratio < 1 for SL/TP limits so
a ratio of 1.0 cannot produce zero protective prices. Clamp negative
margin_free to 0.0 in calculate_margin_and_volume before sizing.

Add boundary and negative-margin tests; document constraints in trading API
docs.

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
2026-06-11 19:32:52 +09:00
Daichi Narushima 18df96872b Add closed-bar rate helpers (v0.6.0) (#26)
* Add closed-bar rate helpers and bump version to 0.6.0.

Expose drop_forming_rate_bar and multi-account collectors so downstream apps no longer need count+1 fetches and manual bar trimming.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Bump pygments to 2.20.0 to fix CVE-2026-4539 ReDoS advisory.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Address PR review feedback on closed-bar rate collection.

Validate count and start_pos before MT5 fetches, avoid redundant frame copies, clarify empty-series errors, and expand test coverage.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Include symbol and timeframe in empty closed-rate error messages.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-11 02:30:48 +09:00
Daichi Narushima 5b1d54bfe9 Add resilient multi-account orchestration helpers (#22)
* Add SDK orchestration helpers for resilient multi-account collection

- collect_latest_rates_for_accounts_with_retries(): exponential-backoff
  retries around collect_latest_rates_for_accounts(), retrying only
  Mt5TradingError/Mt5RuntimeError and re-raising on exhaustion.
- resolve_account_spec()/resolve_account_specs() and
  substitute_env_placeholders(): merge explicit overrides over AccountSpec
  fields and expand ${ENV_VAR} placeholders, raising ValueError on missing
  variables.
- ThrottledHistoryUpdater: monotonic-clock throttled wrapper around
  update_history() with should_update()/update() and opt-in suppress_errors.
- load_rate_series_by_granularity(): rate-series loader keyed by
  (symbol | None, granularity_name).
- Export new APIs, add unit tests (100% coverage), and document in README
  and docs/api.

* chore: bump version from 0.5.1 to 0.5.3 (#24)

Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: resolve leftover merge conflict markers in version files

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

* fix: address PR review feedback on SDK orchestration helpers

- Use single-pass env substitution to avoid TOCTOU KeyError
- Apply backoff_base to all retry delays (backoff_base ** (attempt + 1))
- Preserve integer logins in resolve_account_spec; hide login in repr
- Fix docs examples (env ordering, while True loop, backoff comment)
- Parametrize suppress_errors tests for MT5 and SQLite errors

Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor Agent <cursoragent@cursor.com>
Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
2026-06-10 00:15:07 +09:00
Daichi Narushima ad9e513253 [codex] Guard dedup scopes by written columns (#23)
* Guard dedup scopes by written columns

* Address dedup scope review feedback

* Remove legacy dedup scope support

* Remove stale legacy descriptions

* chore: bump version from 0.5.1 to 0.5.2
2026-06-09 23:27:54 +09:00
Daichi Narushima 334f01b647 chore: bump version from 0.5.0 to 0.5.1 (#21) 2026-06-09 15:52:32 +09:00
Daichi Narushima 1b69e8f08e Add generic MT5 rate-loading SDK APIs for downstream reuse (#20) 2026-06-09 15:37:24 +09:00
Daichi Narushima 9957b0a1de [codex] Add generic MT5 SDK and SQLite rate loader (#19)
* Add generic MT5 SDK and SQLite rate loader

* Fix MT5 latest rates connection reuse

* Make MT5 summary export safe

* Address PR review feedback for SDK and SQLite rate loader.

Reuse parse_sqlite_timestamp for rate time parsing, document empty-table
errors, tighten tests, and align docs with require_existing=True.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-09 11:27:29 +09:00
Daichi Narushima b2bb2ad0a0 Add rate view resolution and downstream SDK helpers (#18)
* Add public helpers to resolve rate compatibility view names.

Expose resolve_rate_view_name and resolve_rate_view_names in mt5cli.history so consumers can derive mt5cli-managed SQLite view names from stored rates metadata without reimplementing the naming rules.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Add reusable export, tick-window, and margin helpers for downstream tools.

Expose SQLite append/dedup export, recent tick retrieval, and minimum margin
summary through the SDK and CLI so projects like mteor can depend on mt5cli
instead of duplicating MT5 data plumbing.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Bump version to 0.4.3.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Address PR review feedback for rate view resolution and SDK helpers.

Harden SQLite read-only connections, tighten view discovery, improve recent_ticks
fetch efficiency, default SQLite export to append, and expand tests and docs.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Fix read-only SQLite URI construction on Windows.

Use Path.as_uri() so encoded file URIs work cross-platform with mode=ro.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-09 03:29:03 +09:00
Daichi Narushima 756faf747b Rename sqlite_history module to history (#17)
* Rename sqlite_history module to history.

Drop the sqlite-specific prefix now that history collection is the primary module name across SDK, tests, and docs.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Address PR review feedback for history module rename.

Add a sqlite_history compatibility shim, clarify docs naming, and align the
module docstring with the collect-history SQLite scope.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Remove sqlite_history compatibility shim.

The rename to mt5cli.history is intentionally breaking; downstream code
should update imports rather than rely on a deprecated re-export path.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-09 02:40:25 +09:00
Daichi Narushima c4232bf44d Add incremental SQLite history SDK (#16)
* Add incremental SQLite history SDK for automated pipelines.

Extract sqlite history helpers into a dedicated module and expose update_history APIs that resume from existing MAX(time) values instead of re-fetching fixed date ranges.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Fix incremental history deals and stale rate view cleanup.

Fetch account events once during incremental updates, drop stale rate_* views when timeframes change, and avoid SQLite variable limits on wide frames.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Fix incremental deal filtering edge cases

Co-authored-by: Cursor <cursoragent@cursor.com>

* Address PR review feedback for incremental SQLite history.

Make rate views collision-free, batch incremental resume queries, scope deduplication to appended boundaries, validate before opening MT5, use atomic SQLite transactions, and expand docs/tests for the new helpers.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Document collect-history SQLite schema with ER diagram.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Fix account-event filtering and drop legacy rates resume.

Account events must follow only account_event_start, not per-symbol trade
cursors. Require normalized rates schema and fail fast when timeframe is missing.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Validate normalized rates schema before incremental resume.

Require symbol, timeframe, and time on existing rates tables with clear
ValueError messages, and add regression tests for malformed schemas.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-09 01:28:22 +09:00
Daichi Narushima 5b44318d55 Add programmatic SDK and refactor mt5cli into cli, sdk, and utils (#15)
* Refactor cli.py into cli and utils modules

Extract constants, enums, Click parameter types, and parse/export utility
functions into a new mt5cli/utils.py module, keeping the typer app, commands,
and collect-history SQLite helpers in cli.py.

https://claude.ai/code/session_016JwSEhPyq6phXySktQ1FGU

* Address review comments

* Add programmatic SDK layer for read-only MT5 data collection.

Expose Mt5CliClient and collect_history through the package API while keeping CLI commands as thin adapters over the SDK.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Harden SDK connection lifecycle and scope internal helpers as private.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Export build_config in the public API and bump version to 0.4.0.

Co-authored-by: Cursor <cursoragent@cursor.com>

* Remove duplicate scripts/ in favor of local-qa skill script.

Co-authored-by: Cursor <cursoragent@cursor.com>

---------

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-08 22:54:53 +09:00
dceoy 7f70073301 Update pyproject.toml 2026-06-07 23:47:32 +09:00
Daichi Narushima da74c11087 Add collect-history command for bulk data collection (#14)
* Add collect-history command for bulk SQLite export

Bundles rates, ticks, history-orders, and history-deals for one or more
symbols into a single SQLite database. Tick collection uses
copy_ticks_range_as_df with a --flags option defaulting to ALL. With
--with-views, optional cash_events and positions_reconstructed views are
derived from history_deals when the required columns are present.

* Extend collect-history with datasets, if-exists, timeframe, view fixes

- Fetch history-orders and history-deals per symbol so --symbol applies
  consistently across all four datasets.
- Add repeatable --dataset (rates, ticks, history-orders, history-deals)
  so ticks are no longer required and any subset can be collected.
- Add --if-exists append|replace|fail to control SQLite table conflict
  behavior instead of hard-coding replace.
- Record the requested timeframe in a timeframe column on the rates
  table so appended runs at different timeframes stay distinguishable.
- Fix positions_reconstructed to exclude positions with no closing
  deals, use volume-weighted open/close prices, and report reversal
  deals (DEAL_ENTRY_INOUT) via volume_reversal / reversal_count without
  contributing to weighted prices.
- Update tests, README, docs, and skill to match.

* Address collect-history review feedback

* Stream collect-history writes per symbol

* Address PR cleanup for collect-history

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-05-29 01:22:59 +09:00
Daichi Narushima c45efb953c Update local QA skill workflow (#13) 2026-05-25 02:12:28 +09:00
dceoy c1eea3fa3d Update .github/workflows/ci.yml 2026-05-25 01:48:43 +09:00
github-actions[bot] 62e5f438f0 Merge pull request #12 from dceoy/dependabot/uv/uv-d665ee01e3
Bump idna from 3.13 to 3.15 in the uv group across 1 directory
2026-05-19 21:12:38 +00:00
dependabot[bot] 50f62bca73 Bump idna from 3.13 to 3.15 in the uv group across 1 directory
Bumps the uv group with 1 update in the / directory: [idna](https://github.com/kjd/idna).


Updates `idna` from 3.13 to 3.15
- [Release notes](https://github.com/kjd/idna/releases)
- [Changelog](https://github.com/kjd/idna/blob/master/HISTORY.md)
- [Commits](https://github.com/kjd/idna/compare/v3.13...v3.15)

---
updated-dependencies:
- dependency-name: idna
  dependency-version: '3.15'
  dependency-type: indirect
  dependency-group: uv
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-05-19 21:11:32 +00:00
github-actions[bot] 0b7dfdc621 Merge pull request #11 from dceoy/dependabot/uv/uv-ab67d3f053
Bump pymdown-extensions from 10.21.2 to 10.21.3 in the uv group across 1 directory
2026-05-19 20:48:47 +00:00
dependabot[bot] bab776e700 Bump pymdown-extensions in the uv group across 1 directory
Bumps the uv group with 1 update in the / directory: [pymdown-extensions](https://github.com/facelessuser/pymdown-extensions).


Updates `pymdown-extensions` from 10.21.2 to 10.21.3
- [Release notes](https://github.com/facelessuser/pymdown-extensions/releases)
- [Commits](https://github.com/facelessuser/pymdown-extensions/compare/10.21.2...10.21.3)

---
updated-dependencies:
- dependency-name: pymdown-extensions
  dependency-version: 10.21.3
  dependency-type: direct:development
  dependency-group: uv
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-05-19 20:47:23 +00:00
github-actions[bot] 9bf9a6a72c Merge pull request #10 from dceoy/dependabot/uv/uv-c30c77f42d
Bump urllib3 from 2.6.3 to 2.7.0 in the uv group across 1 directory
2026-05-11 18:22:00 +00:00
dependabot[bot] d7594ddc43 Bump urllib3 from 2.6.3 to 2.7.0 in the uv group across 1 directory
Bumps the uv group with 1 update in the / directory: [urllib3](https://github.com/urllib3/urllib3).


Updates `urllib3` from 2.6.3 to 2.7.0
- [Release notes](https://github.com/urllib3/urllib3/releases)
- [Changelog](https://github.com/urllib3/urllib3/blob/main/CHANGES.rst)
- [Commits](https://github.com/urllib3/urllib3/compare/2.6.3...2.7.0)

---
updated-dependencies:
- dependency-name: urllib3
  dependency-version: 2.7.0
  dependency-type: indirect
  dependency-group: uv
...

Signed-off-by: dependabot[bot] <support@github.com>
2026-05-11 18:20:57 +00:00
52 changed files with 25446 additions and 1065 deletions
+18 -21
View File
@@ -1,25 +1,22 @@
# local-qa
---
name: local-qa
description: Run local QA including formatting, linting, and testing for the repository. Use whenever any file has been updated.
disable-model-invocation: false
---
Run local QA checks (format, lint, test) on the repository.
# Local QA (format, lint, and test)
## When to use
Run the local QA script `scripts/qa.sh` in this skill.
After making changes to repository files, run `scripts/qa.sh` to validate formatting, linting, and tests.
## Procedure
## Steps
1. Execute `scripts/qa.sh` and capture the results.
2. Report successes, failures, warnings, and any modified files.
## If tools are missing
Install them following this priority order:
1. Project package managers (`uv`, `poetry`, npm scripts)
2. System package managers (`brew`, `apt`)
3. Language-specific installers (`pipx`, `pip`, `npm`, `go install`)
## Constraints
- Only execute QA and tool-installation commands.
- If installation fails or requires unavailable privileges, report the attempt and exact failure, then stop.
- Execute the script exactly as shown above when this skill is triggered.
- Capture and summarize key output (success/failure, major warnings, and any files modified).
- If the script fails due to missing tooling (`command not found`, missing executable, or equivalent), install the missing tool(s) and rerun `./scripts/qa.sh`.
- Install tools using this order of preference:
1. Use the project's package manager when applicable (`uv`/`poetry` for Python, package manager scripts/dependencies for Node.js).
2. Use a system package manager (`brew` on macOS, `apt` on Debian/Ubuntu) when project-local install is not applicable.
3. Use language-specific installers as fallback (`pipx`/`pip`, `npm`, `go install`, etc.).
- If multiple tools are missing, repeat install -> rerun until QA completes or you hit a blocker.
- If installation fails or requires unavailable privileges, report what was attempted, the exact failure, and stop.
- Do not run unrelated commands; only run commands needed for QA and missing-tool installation.
+12 -5
View File
@@ -10,10 +10,17 @@ uv run pyright .
uv run pytest
# Markdown
npx -y prettier --write './**/*.md'
npx -y prettier --write './**/*.{md,json}'
# GitHub Actions
zizmor --fix=safe .github/workflows
git ls-files -z -- '.github/workflows/*.yml' | xargs -0 -t actionlint
git ls-files -z -- '.github/workflows/*.yml' | xargs -0 -t yamllint -d '{"extends": "relaxed", "rules": {"line-length": "disable"}}'
checkov --framework=all --output=github_failed_only --directory=.
case "${OSTYPE}" in
darwin* | linux* )
zizmor --fix=safe .github/workflows
git ls-files -z -- '.github/workflows/*.yml' | xargs -0 -t actionlint
git ls-files -z -- '.github/workflows/*.yml' | xargs -0 -t yamllint -d '{"extends": "relaxed", "rules": {"line-length": "disable"}}'
checkov --framework=all --output=github_failed_only --directory=.
;;
* )
echo "GitHub Actions linting is only supported on Linux and macOS."
;;
esac
+201
View File
@@ -0,0 +1,201 @@
---
name: pr-feedback-triage
description: Triage pull request review comments into fixes, replies, clarification requests, or open follow-ups while respecting safe execution modes.
---
# PR Feedback Triage
Triage pull request review feedback, decide what action each thread needs, make focused fixes when allowed, and report or resolve only what is actually handled.
## When to Use
- A PR has review comments, requested changes, unresolved review threads, or bot review findings.
- The user asks to address, respond to, or resolve PR feedback.
- The user provides a PR URL/number, a branch with an associated PR, or copied comments.
Do not use this skill for a first-pass code review with no existing feedback; use a code review skill instead.
## Inputs
- Pull request URL or number, or a current branch that has an associated pull request.
- Repository checkout or platform access sufficient to inspect the PR diff and review feedback.
- Optional reviewer priorities from the user, such as "only address blocking comments" or "do not reply on the PR platform".
- Optional operating mode flags: `dry_run`, `no_push`, and `no_reply`.
If no PR or review comments are identifiable, ask for the target PR or the copied comments before proceeding.
## Modes
- `dry_run`: inspect review feedback and report the triage only. Do not edit files, run write-mode formatters, commit, push, post replies, or resolve review threads.
- `no_push`: local edits and verification are allowed, but do not push commits or otherwise update the remote branch. Report the local diff or local commits that still need to be pushed. Do not resolve threads whose resolution depends on unpushed local edits.
- `no_reply`: do not post replies, submit reviews, or resolve review threads. Provide suggested replies and resolution actions in the final report instead.
When a mode disables an action, skip that destructive or externally visible action even if normal workflow text would otherwise allow it.
## Preflight
1. Identify the current branch and target PR.
2. Check tracked local changes with `git diff --name-only` and `git diff --cached --name-only`. Ignore untracked files unless the review feedback explicitly concerns them.
3. Check unpushed commits before relying on remote review feedback.
4. If tracked local changes or unpushed commits exist, warn that existing PR comments may not cover the latest local state. In `normal` mode, push only when the user request or repository workflow allows it; otherwise continue with a clearly reported limitation.
## Feedback Collection
Gather the complete feedback set before editing:
- Fetch unresolved review threads, requested-change reviews, PR-level summary comments, and copied comments.
- Use platform-native APIs/CLI when available. Paginate results; do not inspect only the first page of threads or comments.
- For bot reviewers that post both summary comments and inline comments, collect both. Summary comments often contain severity, rationale, and fix instructions; inline comments contain the exact file and line context.
- Preserve every thread/comment identifier needed to reply or resolve later.
- Compare each comment with the current diff and file contents because review lines can become outdated.
## Deduplication and Ordering
Build one triage record per distinct finding:
- Prefer exact review-thread identity when available.
- For duplicate bot findings appearing in both summary and inline comments, merge by exact issue title first, then by file path plus line range as a fallback.
- Prefer inline comments for location and current code context.
- Prefer summary comments for severity, category, rationale, and detailed agent prompts.
- Preserve the reviewers exact issue title and original wording where practical. Do not rename findings in a way that would make replies hard to map back to comments.
- Preserve the reviewers original ordering unless the user asks for priority reordering. Many review bots already order findings by severity.
Each triage record should track: original title, reviewer, source IDs, location, current applicability, severity/priority if available, disposition, planned action, verification, reply text if any, resolution decision, platform action attempted, and final platform state.
## Resolution Policy
In normal mode, `Resolve conversation` is the default action for any review thread that has been fully handled. A thread is handled when the requested change is implemented and verified, the current code already satisfies the comment, the comment is outdated and no longer applies, or a deliberate deferral/won't-fix response has been posted with a clear reason.
Keep a thread open only when it still needs reviewer, maintainer, or product input, the fix is local-only and not pushed, verification is missing for a material change, or the user explicitly requested `dry_run`, `no_push`, or `no_reply` behavior that prevents resolution.
When resolving a thread, add a concise reply first only if it provides useful context, such as what changed, why no code change was needed, why a finding was intentionally deferred, or why the original comment is now outdated. Do not add noisy replies for self-evident fixes unless project norms require them.
## Platform Action Contract
Do not treat triage as complete until every collected source ID reaches an explicit terminal state:
- `resolved`: a platform resolve action succeeded, or a re-check shows the thread is already resolved.
- `replied_left_open`: a reply or question was posted and the thread is intentionally left unresolved.
- `not_resolvable`: the source is a PR-level summary comment or copied comment that has no platform-level resolve action; reply or post a PR summary when useful.
- `skipped_by_mode`: `dry_run`, `no_push`, or `no_reply` prevented the external action.
- `failed_action`: a reply or resolve action was attempted and failed; include the attempted action and failure in the final summary.
In normal mode, build and execute a platform action queue after fixes are verified and pushed when needed:
- `reply_then_resolve`: use for handled threads where the reviewer needs context before resolution.
- `resolve_only`: use for self-evident fixes and already-addressed or outdated threads where an extra reply would add noise.
- `reply_leave_open`: use only for clarification requests, blocked work, or intentionally open follow-ups.
- `reply_only`: use for PR-level comments or summaries that cannot be resolved as review threads.
For duplicate findings, execute the terminal action for every source thread ID, not only the primary triage record. If one finding is represented by three unresolved inline threads, all three must be resolved or explicitly left open.
## GitHub Action Guidance
Prefer platform-native APIs or `gh` commands that expose review-thread resolution state. For GitHub inline review threads, use the thread node ID and the GraphQL `resolveReviewThread` mutation rather than assuming that a reply resolves the conversation.
A reliable pattern is:
1. Re-fetch review threads and comments immediately before acting.
2. Reply to the thread when the action queue says a reply is needed.
3. Resolve the review thread by node ID when the terminal state should be `resolved`.
4. Re-fetch unresolved review threads after the action queue completes.
5. Retry any expected-to-be-resolved thread that is still unresolved once; if it still remains unresolved, mark it `failed_action` instead of claiming completion.
Example GraphQL mutation shape:
```graphql
mutation ($threadId: ID!) {
resolveReviewThread(input: { threadId: $threadId }) {
thread {
id
isResolved
}
}
}
```
A posted reply alone is sufficient only for `reply_leave_open`, `reply_only`, or `not_resolvable` sources. For handled inline review threads, reply and resolve are separate actions.
## Flow
```mermaid
flowchart TD
A[Identify PR and branch state] --> B[Collect all review feedback]
B --> C[Deduplicate and preserve source IDs]
C --> D[Inspect current diff and code]
D --> E{Classify each triage record}
E -->|Fix| F[Implement minimal change]
E -->|Answer| G[Prepare concise reply]
E -->|Clarify| H[Prepare question and leave open]
E -->|Already addressed or Outdated| I[Prepare evidence]
E -->|Defer or Won't fix| J[Document reason]
F --> K[Verify]
G --> L{Mode}
H --> L
I --> L
J --> L
K --> L
L -->|dry_run| M[Report triage only]
L -->|no_push| N[Report local diff or commits]
L -->|no_reply| O[Report suggested replies/actions]
L -->|normal| P[Commit/push if changed]
P --> R[Execute reply/resolve action queue]
R --> S[Re-fetch threads and retry unresolved handled threads once]
M --> Q[Final summary]
N --> Q
O --> Q
S --> Q
```
## Compact Workflow
1. **Collect all relevant feedback**
- Identify the PR and gather unresolved review threads, requested-change reviews, PR-level summaries, inline comments, and copied comments.
- Paginate all platform calls and keep comment/thread IDs for later replies and resolution.
- For bot reviews, collect both summary and inline comments, then merge duplicates rather than fixing the same finding twice.
2. **Classify each triage record**
- **Fix**: Valid requested change; make the smallest focused edit when not in `dry_run`.
- **Answer**: No code change needed; prepare a concise explanation.
- **Clarify**: Ambiguous, conflicting, or missing context; reply with the question and leave unresolved.
- **Already addressed**: Current code already satisfies it; prepare evidence.
- **Outdated**: Commented code or issue no longer exists; prepare evidence.
- **Defer / Won't fix**: Valid concern intentionally not changed now; document a specific reason.
3. **Act according to the classification and mode**
- Keep edits scoped to the review feedback.
- Follow reviewer-provided fix instructions literally when they are still applicable; deviate only when the current code proves the instruction is stale or unsafe.
- In `dry_run`, stop at triage, proposed fixes, suggested replies, and verification plan.
- In `no_push`, local edits are allowed, but do not push or resolve threads whose fix is only local. Reply or resolve non-code, already-addressed, or outdated threads only when the action does not depend on unpushed work and `no_reply` is not set.
- In `no_reply`, do not post replies or resolve threads; report suggested replies/actions instead.
- In normal mode, commit and push changed code when appropriate, then execute the platform action queue for every collected source ID.
4. **Verify before claiming completion**
- For fixes, run appropriate checks or explain why they could not run.
- Re-inspect the updated diff and comment context to confirm the concern is resolved.
- Re-fetch review threads after reply/resolve actions and confirm all expected-to-be-resolved thread IDs are resolved.
- Do not mark a thread resolved if it still needs reviewer, maintainer, or product input.
- If a resolve or reply operation fails, retry once when safe; then report `failed_action` with the affected source ID and reason.
5. **Finish**
- Normal mode: commit/push changes when appropriate, post useful replies or a summary, resolve all handled threads by default, and reconcile the final unresolved set.
- Safe modes: report the local state and the exact replies/resolution actions a human could take.
## Reply Guidance
- Keep inline replies short and tied to the original title or concern.
- For fixed findings, mention the concrete change or commit if useful.
- For already-addressed or outdated findings, cite the current code path or behavior that makes the finding no longer applicable.
- For deferred or won't-fix findings, provide the reason and any follow-up issue or owner if known.
- If a reply or resolve operation fails, continue with the remaining threads and report the failure in the final summary.
## Final Summary Checklist
- Mode used: `normal`, `dry_run`, `no_push`, or `no_reply`
- Counts by disposition: fixed, answered, clarified/left open, already addressed, outdated, deferred/won't-fix
- Counts by platform terminal state: resolved, replied-left-open, not-resolvable, skipped-by-mode, failed-action
- Threads resolved, intentionally left open, already resolved, or resolution actions skipped by mode
- Any expected-to-be-resolved thread that remained unresolved after retry
- Verification run or planned
- Commits pushed, local diff/commits, or "none"
- Remaining open items and who needs to respond
+16 -2
View File
@@ -35,7 +35,7 @@ jobs:
|| (github.event_name == 'workflow_dispatch' && inputs.workflow == 'lint-and-test')
permissions:
contents: read
uses: dceoy/gh-actions-for-devops/.github/workflows/python-package-lint-and-scan.yml@main # zizmor: ignore[unpinned-uses]
uses: dceoy/gh-actions-for-devops/.github/workflows/python-package-lint-and-scan.yml@main # zizmor: ignore[unpinned-uses]
with:
package-path: .
runs-on: windows-latest
@@ -59,10 +59,22 @@ jobs:
uses: dceoy/gh-actions-for-devops/.github/workflows/python-package-mkdocs-gh-deploy.yml@main # zizmor: ignore[unpinned-uses]
with:
package-path: .
mkdocs-theme: material
runs-on: ubuntu-slim
secrets:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
github-codeql-analysis:
if: >
github.event_name == 'push'
|| github.event_name == 'pull_request'
|| (github.event_name == 'workflow_dispatch' && inputs.workflow == 'lint-and-test')
permissions:
contents: read
security-events: write
actions: read
uses: dceoy/gh-actions-for-devops/.github/workflows/github-codeql-analysis.yml@main # zizmor: ignore[unpinned-uses]
with:
language: >
["python"]
dependabot-auto-merge:
if: >
github.event_name == 'pull_request' && github.actor == 'dependabot[bot]'
@@ -74,5 +86,7 @@ jobs:
contents: write
pull-requests: write
actions: read
checks: read
statuses: read
with:
unconditional: true
+20 -62
View File
@@ -1,79 +1,37 @@
# Repository Guidelines
## Commands
## Project Structure & Module Organization
### Development Setup
`mt5cli/` contains the package source. Important modules include `cli.py` for the Typer command-line app, `client.py` and `sdk.py` for public MT5 client/session APIs, `history.py` for SQLite history collection, `storage.py` and `converters.py` for export behavior, and `schemas.py` for normalized dataset contracts. `tests/` holds pytest coverage for CLI behavior, SDK contracts, trading helpers, history, and utilities. `docs/` and `mkdocs.yml` define the MkDocs site and API reference. `skills/mt5cli/SKILL.md` documents the mt5cli agent skill.
```bash
uv sync
```
## Build, Test, and Development Commands
### Code Quality and Documentation
- `uv sync` installs runtime and development dependencies from `pyproject.toml` and `uv.lock`.
- `uv run mt5cli --help` runs the local CLI entry point.
- `uv run ruff format .` formats Python files.
- `uv run ruff check --fix .` lints and applies safe fixes.
- `uv run pyright .` runs strict type checking.
- `uv run pytest` runs doctests, branch coverage, and the test suite.
- `uv run mkdocs serve` previews documentation locally; `uv run mkdocs build` validates the docs build.
**Important**: Run these before committing or creating a PR.
Use `.agents/skills/local-qa/SKILL.md` for pre-handoff QA. It runs `.agents/skills/local-qa/scripts/qa.sh`, which formats, lints, type-checks, tests, formats Markdown, and checks GitHub workflows.
1. **format, lint, and test**: Use `local-qa` skill.
2. **Documentation build** (if any public API changes): `uv run mkdocs build`
## Coding Style & Naming Conventions
## Architecture
Target Python `>=3.11,<3.14`. Use Ruffs configured 88-character line length and Google-style docstrings. Pyright is strict, so prefer explicit public type annotations and narrow exception handling. Keep module, function, and variable names in `snake_case`; classes and enums use `PascalCase`. Preserve the packages small, typed helper style rather than adding broad abstractions.
### Key Dependencies
## Design Principles
- **pdmt5**: Pandas-based data handler for MetaTrader 5 (core library)
- **typer**: CLI framework for building command-line interfaces
- **click**: Parameter type customization for CLI options
- **pandas**: Core data manipulation and analysis
Apply KISS, DRY, and YAGNI when changing code. Prefer the simplest implementation that satisfies the current CLI/API contract. Remove duplication when shared behavior is already proven by at least two concrete call sites, but avoid generic helpers for speculative reuse. Do not add configuration flags, extension hooks, or alternate backends until a real repository use case requires them.
### Package Structure
## Testing Guidelines
- `mt5cli/`: Main package directory
- `__init__.py`: Package initialization and exports (`detect_format`, `export_dataframe`)
- `cli.py`: CLI application with typer-based commands for data export
- `__main__.py`: Entry point for `python -m mt5cli`
- `tests/`: Comprehensive test suite (pytest-based)
- `test_cli.py`: Tests for CLI commands, parameter types, and export functions
- `docs/`: MkDocs documentation with API reference
- `docs/index.md`: Main documentation
- `docs/api/`: Auto-generated API documentation for all modules
- Modern Python packaging with `pyproject.toml` and uv dependency management
### Quality Standards
- Type hints required (pyright strict mode)
- Comprehensive linting with 35+ rule categories (ruff)
- Test coverage tracking with 100% (pytest-cov)
- Parametrized tests for input/result matrices using `pytest.mark.parametrize` (pytest)
- Test doubles (mocks, stubs) using `pytest_mock` for external dependencies (pytest-mock)
- Pydantic models for data validation and configuration
### Documentation workflow
1. Add Google-style docstrings to functions/classes
2. Local preview: `uv run mkdocs serve`
3. Build: `uv run mkdocs build`
4. Deploy: `uv run mkdocs gh-deploy`
Tests use pytest, pytest-mock, doctests, and pytest-cov. Test files should match `tests/test_*.py`, classes `Test*`, and functions `test_*`. Coverage is configured with `fail_under = 100`, so add focused tests for every behavior change. Mock MT5/pdmt5 boundaries; do not require a live MetaTrader terminal in unit tests.
## Commit & Pull Request Guidelines
- Run QA checks using `local-qa` skill before committing or creating a PR.
- Branch names use appropriate prefixes on creation (e.g., `feature/...`, `bugfix/...`, `refactor/...`, `docs/...`, `chore/...`).
- When instructed to create a PR, create it as a draft with appropriate labels by default.
Recent history uses concise imperative commits, sometimes with conventional prefixes such as `feat:` or `chore:` and PR numbers appended by GitHub. Keep commits scoped to one logical change. Pull requests should describe behavior changes, note tests run, link related issues, and call out MT5/live-trading risk where relevant.
## Code Design Principles
## Security & Configuration Tips
Always prefer the simplest design that works.
- **KISS**: Choose straightforward solutions and avoid unnecessary abstraction.
- **DRY**: Remove duplication when it improves clarity and maintainability.
- **YAGNI**: Do not add features, hooks, or flexibility until they are needed.
- **SOLID/Clean Code**: Apply these as tools, only when they keep the design simpler and easier to change.
## Development Methodology
Keep delivery incremental, test-backed, and easy to review.
- Make small, safe, reversible changes.
- Prefer `Red -> Green -> Refactor`.
- Do not mix feature work and refactoring in the same commit.
- Refactor when it improves clarity or removes real duplication (Rule of Three).
- Keep tests fast, focused, and self-validating.
Never commit account credentials, broker passwords, exported private data, or local `.venv` contents. Treat `order_send` and CLI `order-send --yes` as live execution paths; gate examples and tests so they cannot place real trades accidentally.
+375 -23
View File
@@ -2,10 +2,18 @@
[![CI/CD](https://github.com/dceoy/mt5cli/actions/workflows/ci.yml/badge.svg)](https://github.com/dceoy/mt5cli/actions/workflows/ci.yml)
Command-line tool for exporting MetaTrader 5 data to CSV, JSON, Parquet, and SQLite3.
Generic MT5 data and execution infrastructure for Python applications. Export from the CLI or import a small, stable Python API in downstream packages.
The [Public API Contract](docs/api/public-contract.md) lists stable SDK exports (`mt5cli.STABLE_SDK_EXPORTS`), CLI commands, internal helpers, and responsibilities that remain out of scope (strategy logic, backtests, optimization).
Built on top of [pdmt5](https://github.com/dceoy/pdmt5), a pandas-based data handler for MetaTrader 5.
## Architecture
- **pdmt5** — canonical MT5 client, DataFrame/trading primitives, and MT5 constant parsing (`TIMEFRAME_*`, `COPY_TICKS_*`, order types).
- **mt5cli** — public `MT5Client` API, standardized dataset schemas, storage helpers, CLI commands, and SQLite history collection built on pdmt5.
- **mt5api** — sibling HTTP adapter for remote MT5 access; not a dependency of mt5cli.
## Features
- **Multi-format export**: CSV, JSON, Parquet, and SQLite3 output formats
@@ -13,6 +21,7 @@ Built on top of [pdmt5](https://github.com/dceoy/pdmt5), a pandas-based data han
- **Comprehensive data access**: Rates, ticks, account info, symbols, orders, positions, and trading history
- **Flexible timeframes**: Named timeframes (M1, H1, D1, etc.) and numeric values
- **Connection management**: Optional credentials, server, and timeout configuration
- **SQLite rate loading**: Load mt5cli-managed rate tables/views for offline workflows
## Installation
@@ -20,7 +29,105 @@ Built on top of [pdmt5](https://github.com/dceoy/pdmt5), a pandas-based data han
pip install -U mt5cli MetaTrader5
```
## Usage
Parquet export is not included by default. To enable it, install the `parquet` extra:
```bash
pip install -U "mt5cli[parquet]" MetaTrader5
```
## Python API (downstream packages)
Import `MT5Client` for generic MT5 data access, schema normalization, and optional order primitives.
```python
from datetime import UTC, datetime
from pathlib import Path
from mt5cli import (
MT5Client,
build_config,
collect_history,
mt5_session,
update_history_with_config,
)
from mt5cli.schemas import DataKind, normalize_dataframe
from mt5cli.utils import Dataset, export_dataframe
# Persistent session for multiple calls
with mt5_session(build_config(login=12345, server="Broker-Demo")) as client:
rates = client.copy_rates_range(
"EURUSD",
timeframe="H1",
date_from="2024-01-01",
date_to="2024-02-01",
)
positions = client.positions()
check = client.order_check({"action": 1, "symbol": "EURUSD", "volume": 0.1})
# Normalize MT5 frames to the public schema contract before storage
closed_rates = normalize_dataframe(
rates, DataKind.rates, symbol="EURUSD", timeframe="H1"
)
export_dataframe(closed_rates, Path("rates.csv"), "csv")
# Bulk SQLite history (same behavior as collect-history CLI command)
collect_history(
Path("history.db"),
symbols=["EURUSD"],
date_from=datetime(2024, 1, 1, tzinfo=UTC),
date_to=datetime(2024, 2, 1, tzinfo=UTC),
datasets={Dataset.rates, Dataset.history_deals},
)
# Incremental append for automated pipelines
update_history_with_config(
output="history.db",
symbols=["EURUSD"],
config=build_config(login=12345),
)
```
Schema contracts live in `mt5cli.schemas` (`DataKind`, `validate_schema`, `normalize_dataframe`). Export and storage helpers are in `mt5cli.utils` (`Dataset`, `export_dataframe`) and `mt5cli.history`.
`MT5Client.order_send()` is a live execution primitive: it can place real trades on the connected account. mt5cli does not implement strategy logic, signal generation, backtesting, or optimization — downstream applications must gate live execution explicitly.
### Trading lifecycle and state helpers
Trading applications can depend on `mt5cli` imports only; terminal path,
credentials, server, and timeout are forwarded to `pdmt5.Mt5Config`, numeric
login strings are coerced to integers, and empty login strings are treated as
unset. Pass `allow_whole_dollar_env=True` to expand `${ENV_VAR}` and bare
`$ENV_NAME` placeholders in connection string parameters before coercion.
```python
from mt5cli import (
build_config,
calculate_spread_ratio,
create_trading_client,
get_account_snapshot,
mt5_trading_session,
)
# Login from environment — numeric string is coerced to int automatically
config = build_config(login="$MT5_LOGIN", allow_whole_dollar_env=True)
with mt5_trading_session(
path=r"C:\Program Files\MetaTrader 5\terminal64.exe",
login="12345",
password="from-env-or-secret-store",
server="Broker-Demo",
) as client:
account = get_account_snapshot(client)
spread = calculate_spread_ratio(client, "EURUSD")
client = create_trading_client(login=12345, server="Broker-Demo")
try:
positions = client.positions_get_as_df(symbol="EURUSD")
finally:
client.shutdown()
```
## CLI usage
```bash
# Export account information to CSV
@@ -50,29 +157,217 @@ python -m mt5cli -o account.csv account-info
## Commands
| Command | Description |
| ------------------ | ------------------------------------------- |
| `rates-from` | Export rates from a start date |
| `rates-from-pos` | Export rates from a start position |
| `rates-range` | Export rates for a date range |
| `ticks-from` | Export ticks from a start date |
| `ticks-range` | Export ticks for a date range |
| `account-info` | Export account information |
| `terminal-info` | Export terminal information |
| `version` | Export MetaTrader 5 version information |
| `last-error` | Export the last error information |
| `symbols` | Export symbol list |
| `symbol-info` | Export symbol details |
| `symbol-info-tick` | Export the last tick for a symbol |
| `market-book` | Export market depth (order book) |
| `orders` | Export active orders |
| `positions` | Export open positions |
| `history-orders` | Export historical orders |
| `history-deals` | Export historical deals |
| `order-check` | Check funds sufficiency for a trade request |
| `order-send` | Send a trade request to the trade server (`--yes` required) |
| Command | Description |
| ---------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| `rates-from` | Export rates from a start date |
| `rates-from-pos` | Export rates from a start position |
| `latest-rates` | Export latest rates from a start position |
| `rates-range` | Export rates for a date range |
| `ticks-from` | Export ticks from a start date |
| `ticks-range` | Export ticks for a date range |
| `ticks-recent` | Export ticks from a recent trailing window |
| `account-info` | Export account information |
| `terminal-info` | Export terminal information |
| `version` | Export MetaTrader 5 version information |
| `last-error` | Export the last error information |
| `symbols` | Export symbol list |
| `symbol-info` | Export symbol details |
| `symbol-info-tick` | Export the last tick for a symbol |
| `minimum-margins` | Export minimum-volume buy and sell margin requirements |
| `market-book` | Export market depth (order book) |
| `orders` | Export active orders |
| `positions` | Export open positions |
| `history-orders` | Export historical orders |
| `history-deals` | Export historical deals |
| `recent-history-deals` | Export historical deals from a recent trailing window |
| `mt5-summary` | Export terminal/account status summary |
| `order-check` | Check funds sufficiency for a trade request |
| `order-send` | Send a raw trade request to the trade server (`--yes` required; expert path) |
| `close-positions` | Close open positions by `--symbol` or `--ticket` (`--yes` required for live; `--dry-run` available) |
| `collect-history` | Collect rates, history-orders, and history-deals for one or more symbols into a single SQLite database (ticks opt-in via `--dataset ticks`) |
| `grafana-schema` | Create or refresh Grafana-ready views and indexes in an existing SQLite database (idempotent, no MT5 connection) |
| `snapshot` | Snapshot current account, position, order, and terminal state into SQLite for live Grafana dashboards |
Use `order-check` to validate a request payload before running `order-send --yes`.
`close-positions` is the safer high-level alternative that builds correct close
requests automatically. At least one `--symbol` or `--ticket` must be provided.
### `collect-history`
Collect several historical datasets per symbol into one SQLite database in a single MT5 session. Pick datasets with repeatable `--dataset` (default: `rates`, `history-orders`, `history-deals`; add `--dataset ticks` when tick-level history is required — tick data can grow the SQLite database quickly), choose conflict behavior with `--if-exists append|replace|fail` (default: `fail`), and optionally derive `cash_events` / `positions_reconstructed` views from `history_deals` via `--with-views`.
```bash
mt5cli -o history.db collect-history \
--symbol EURUSD --symbol GBPUSD \
--date-from 2024-01-01 --date-to 2024-02-01 \
--dataset rates --dataset history-deals \
--timeframe M1 --flags ALL --if-exists append --with-views
```
History orders and deals are fetched per symbol and concatenated, so the symbol filter is applied consistently across all datasets. The `cash_events` view is derived from symbol-filtered `history_deals`, so account-level cash events with empty or non-matching symbols may be excluded. The `rates` table records the requested `timeframe` so appended runs at different timeframes remain distinguishable. The `positions_reconstructed` view aggregates trade deals by `position_id`, excludes positions without closing-side entries, and uses volume-weighted open/close prices; reversal deals (`DEAL_ENTRY_INOUT`) are reported via `volume_reversal` / `reversal_count` columns.
### Grafana-ready SQLite dashboards
mt5cli can prepare a SQLite database for use as a Grafana datasource (via the [SQLite plugin](https://grafana.com/grafana/plugins/frser-sqlite-datasource/) or similar). Most `grafana_*` views expose an integer epoch-second `time` column for use in Grafana time-series panels. Two views (`grafana_realized_pnl`, `grafana_trade_stats`) are static symbol-level summaries with no `time` column — use them in table or stat panels.
#### Prepare the schema (idempotent, no MT5 connection needed)
```bash
mt5cli -o history.db grafana-schema
```
This creates snapshot tables (`account_snapshots`, `position_snapshots`, `order_snapshots`, `terminal_snapshots`, `snapshot_runs`) and all `grafana_*` views and indexes in the SQLite database. Safe to run repeatedly — all operations are idempotent.
#### Snapshot current account state
```bash
mt5cli -o history.db snapshot \
--symbol JP225 --symbol HK50 --symbol NL25 \
--with-account --with-positions --with-orders --with-terminal \
--with-grafana-schema
```
Appends one timestamped row per data type. Never places orders or modifies trading state. Run periodically (e.g. from a cron job or a loop) to build a time-series account history.
#### SDK usage
```python
from pdmt5 import Mt5DataClient, Mt5Config
from mt5cli import update_observability, update_observability_with_config
# Reuse an already-connected client
client = Mt5DataClient(config=Mt5Config(login=12345))
client.initialize_and_login_mt5()
try:
update_observability(
client=client,
output="history.db",
symbols=["EURUSD", "GBPUSD"], # optional position/order filter
include_account=True,
include_positions=True,
include_orders=True,
include_terminal=True,
with_grafana_schema=True,
)
finally:
client.shutdown()
# Standalone wrapper that opens/closes MT5 automatically
update_observability_with_config(
output="history.db",
config=Mt5Config(login=12345),
)
```
#### Available Grafana views
**Time-series views** (integer epoch-second `time` column; snapshot views also expose `run_id`):
| View | Source | Description |
| ---------------------------- | -------------------- | ---------------------------------------------------------- |
| `grafana_rates` | `rates` | OHLCV bars with integer epoch `time` |
| `grafana_ticks` | `ticks` | Tick data with integer epoch `time` |
| `grafana_history_deals` | `history_deals` | All deals with epoch `time` |
| `grafana_history_orders` | `history_orders` | All historical orders; adds epoch `time` from `time_setup` |
| `grafana_trade_deals` | `history_deals` | Trade deals only (`type IN (0,1)`) |
| `grafana_cash_events` | `history_deals` | Non-trade deals (deposits, dividends, etc.) |
| `grafana_symbol_pnl` | `history_deals` | Per-close-deal profit/loss per symbol |
| `grafana_account_snapshots` | `account_snapshots` | Account balance/equity/margin time series |
| `grafana_position_snapshots` | `position_snapshots` | Open position snapshots over time |
| `grafana_order_snapshots` | `order_snapshots` | Active order snapshots over time |
| `grafana_terminal_snapshots` | `terminal_snapshots` | Terminal connectivity snapshots |
**Static summary views** (no `time` column; use in table or stat panels, not time-series):
| View | Source | Description |
| ---------------------- | --------------- | ------------------------------------- |
| `grafana_realized_pnl` | `history_deals` | Cumulative realized PnL per symbol |
| `grafana_trade_stats` | `history_deals` | Win/loss counts and profit per symbol |
#### Example Grafana queries
```sql
-- Equity curve over time
SELECT time, equity FROM grafana_account_snapshots ORDER BY time;
-- Rolling balance by account login
SELECT time, login, balance FROM grafana_account_snapshots
WHERE login = $login ORDER BY time;
-- Open positions at latest successful snapshot
SELECT symbol, volume, profit FROM grafana_position_snapshots
WHERE run_id = (SELECT MAX(run_id) FROM snapshot_runs WHERE status = 'ok');
-- Realized PnL by symbol
SELECT symbol, total_profit FROM grafana_trade_stats ORDER BY total_profit DESC;
```
> **Note**: OpenTelemetry integration is intentionally not part of this release and is tracked separately.
### Incremental history SDK
For automated pipelines, use the importable incremental API instead of re-fetching fixed date ranges:
```python
from pdmt5 import Mt5Config, Mt5DataClient
from mt5cli import update_history, update_history_with_config
from mt5cli.utils import Dataset
# Reuse an already-connected pdmt5 client (does not open/close MT5)
client = Mt5DataClient(config=Mt5Config(login=12345))
client.initialize_and_login_mt5()
try:
update_history(
client=client,
output="history.db",
symbols=["EURUSD", "GBPUSD"],
datasets={Dataset.rates, Dataset.history_deals},
timeframes=["M1", "H1"], # default: all fixed MT5 timeframes
lookback_hours=24,
create_rate_views=True,
with_views=True,
include_account_events=True,
)
finally:
client.shutdown()
# Standalone wrapper that opens and closes MT5 for you
update_history_with_config(
output="history.db",
symbols=["EURUSD"],
config=Mt5Config(login=12345),
)
```
- **`collect-history`**: explicit date-range export into SQLite.
- **`update_history`**: incremental append based on existing SQLite `MAX(time)` per symbol (and timeframe for rates); account-level deals use a separate cursor when `include_account_events=True`.
- **`rates` table**: normalized storage with `symbol` and `timeframe` columns.
- **Rate compatibility views**: mt5cli manages all `rate_*` views. Naming is `rate_<symbol>__<timeframe>` when a symbol has one timeframe, otherwise `rate_<symbol>__<granularity>_<timeframe>` (for example `rate_EURUSD__M1_1`). Stale `rate_*` views are dropped and recreated when rates change for offline downstream tools.
- **Rate view resolution**: use `resolve_rate_view_name()` / `resolve_rate_view_names()` to map symbols and granularities to existing SQLite compatibility views without creating databases. Both accept `None` (or a missing path) and return deterministic default names unless `require_existing=True`.
- **Rate view loading**: use `load_rate_data()` / `load_rate_data_from_connection()` to load a SQLite rate table or view into a `DatetimeIndex` DataFrame.
- **Multi-series rate loading**: use `build_rate_targets()` to build neutral `RateTarget(symbol, timeframe)` pairs, `resolve_rate_tables()` to map them to table/view names (pass `require_existing=True` for strict resolution), and `load_rate_series_from_sqlite()` to load them into a mapping keyed by `(symbol, integer timeframe)`. The loader requires existing managed views unless `explicit_tables` is supplied, and rejects duplicate `(symbol, timeframe)` targets.
- **Multi-account latest rates**: use `collect_latest_rates_for_accounts()` with `AccountSpec` to read the latest bars for several account groups, merged into a `(symbol, integer timeframe)` mapping. For long-running pollers, `collect_latest_rates_for_accounts_with_retries()` adds bounded exponential backoff that retries only recoverable MT5 errors and re-raises once `retry_count` is exhausted.
- **Latest closed bars**: use `collect_latest_closed_rates_for_accounts()` when downstream logic must exclude the still-forming current bar. It fetches `count + 1` bars at `start_pos=0`, drops the last row with `drop_forming_rate_bar()`, and validates each series is non-empty. `collect_latest_closed_rates_by_granularity()` returns the same data keyed by `(symbol, granularity_name)` such as `("EURUSD", "M1")`.
```python
from mt5cli import AccountSpec, collect_latest_closed_rates_by_granularity
rates = collect_latest_closed_rates_by_granularity(
[AccountSpec(symbols=["EURUSD", "GBPUSD"], login=12345)],
["M1", "H1"],
count=500,
retry_count=3,
)
eurusd_m1 = rates["EURUSD", "M1"] # closed bars only
```
- **Credential resolution**: use `resolve_account_spec()` / `resolve_account_specs()` to merge explicit override values over `AccountSpec` fields and expand `${ENV_VAR}` placeholders (via `substitute_env_placeholders()`), raising `ValueError` for missing variables. This keeps secrets out of plan/config files without coupling to any strategy code. For config dicts or nested structures loaded from YAML/TOML, use `substitute_mapping_values(data, keys={"login", "password"})` to expand placeholders only for caller-specified keys — key names are never hard-coded in mt5cli.
- **Throttled history updates**: use `ThrottledHistoryUpdater` to wrap `update_history()` with a minimum `interval_seconds` between successful runs (monotonic clock). Call `should_update()` / `update(client, symbols)` from an application loop; errors propagate by default, or pass `suppress_errors=True` to swallow recoverable `Mt5*Error`, `sqlite3.Error`, `ValueError`, `OSError`, and MT5 client capability errors for history API methods without advancing the throttle (other `AttributeError` / `TypeError` values always propagate). Pass `update_backend` to inject a custom history update callable (same keyword arguments as `update_history`) instead of monkey-patching `mt5cli.sdk.update_history`.
- **Trading session helpers**: use `mt5_trading_session()` for a trading-capable client that initializes/logs in via `Mt5Config.path` and always shuts down safely. Pair with `detect_position_side()`, `calculate_margin_and_volume()`, and `determine_order_limits()` for generic position and sizing utilities. Keep read-only collection on `mt5_session()` / `MT5Client`.
- **Granularity-keyed rate loading**: `load_rate_series_by_granularity()` builds targets with `build_rate_targets()`, loads them with `load_rate_series_from_sqlite()`, and returns a mapping keyed by `(symbol | None, granularity_name)` such as `("EURUSD", "M1")` to reduce downstream boilerplate.
- **MT5 session helper**: use the `mt5_session()` context manager to attach to (or, when `Mt5Config.path` is set, launch) an MT5 terminal, log in, and yield a connected `MT5Client` that shuts down on exit.
- **SQLite export helpers**: use `export_dataframe_to_sqlite()` for append mode, optional index export, and post-write deduplication by key columns.
- **Recent ticks and margins**: `recent_ticks()` and `minimum_margins()` SDK helpers (and matching CLI commands) cover common downstream read-only queries.
## Requirements
@@ -80,6 +375,63 @@ Use `order-check` to validate a request payload before running `order-send --yes
- Windows OS (MetaTrader 5 requirement)
- MetaTrader 5 platform installed
### Migration note for downstream trading apps
Replace local MT5 lifecycle and trading helper code with mt5cli imports:
```python
# Before (local application helpers)
# with local_mt5_trading_session(config) as client:
# side = local_detect_position_side(client, symbol)
# sizing = local_calculate_margin_and_volume(client, symbol, unit_ratio, preserved_ratio)
# limits = local_determine_order_limits(client, symbol, side, sl_ratio, tp_ratio)
# After (mt5cli shared layer)
from pdmt5 import Mt5Config
from mt5cli import (
calculate_margin_and_volume,
detect_position_side,
determine_order_limits,
mt5_trading_session,
)
with mt5_trading_session(
Mt5Config(path=terminal_path, login=login), retry_count=2
) as client:
side = detect_position_side(client, symbol)
sizing = calculate_margin_and_volume(
client, symbol, unit_margin_ratio=0.5, preserved_margin_ratio=0.2
)
if side is not None:
limits = determine_order_limits(
client,
symbol,
side,
stop_loss_limit_ratio=0.01,
take_profit_limit_ratio=0.02,
)
```
Throttled history updates use a separate read-only session:
```python
from pdmt5 import Mt5Config, Mt5DataClient
from mt5cli import ThrottledHistoryUpdater
updater = ThrottledHistoryUpdater(
output="history.db", interval_seconds=60, suppress_errors=True
)
client = Mt5DataClient(config=Mt5Config(login=login))
client.initialize_and_login_mt5()
try:
updater.update(client, ["EURUSD"])
finally:
client.shutdown()
```
Read-only collectors can keep using `mt5_session()` and `MT5Client`.
## Development
```bash
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# Client
::: mt5cli.client
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# Converters
::: mt5cli.converters
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# Exceptions
::: mt5cli.exceptions
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# History Collection (SQLite)
::: mt5cli.history
## `collect-history` schema
The `collect-history` command (and the matching `collect_history` SDK function) writes
selected MT5 datasets into one SQLite database. Each dataset becomes a table; column
names and types mirror the pdmt5 DataFrame schema for that export, with two additions:
- `symbol` is prepended on every table.
- `timeframe` is prepended on `rates` so appended runs at different bar sizes stay
distinguishable.
SQLite does not declare foreign keys. Rows are linked logically by `symbol`, time
windows, and (for deals) `position_id` / `order`. Duplicate rows are removed on
append using dataset-specific keys (for example `ticket` on history tables, or
`(symbol, timeframe, time)` on rates).
Optional views are created when `--with-views` is set and the `history-deals` dataset
was written.
### Entity-relationship diagram
Sample layout for a full collection with `--with-views`:
```mermaid
erDiagram
rates {
TEXT symbol "dedup key"
INTEGER timeframe "dedup key"
TEXT time "dedup key"
REAL open
REAL high
REAL low
REAL close
INTEGER tick_volume
INTEGER spread
INTEGER real_volume
}
ticks {
TEXT symbol "dedup key"
TEXT time "dedup key"
INTEGER time_msc "dedup key (preferred)"
REAL bid
REAL ask
REAL last
INTEGER volume
INTEGER flags
REAL volume_real
}
history_orders {
INTEGER ticket "dedup key"
TEXT symbol
TEXT time
INTEGER type
INTEGER state
REAL volume_initial
REAL price_open
REAL price_current
INTEGER magic
}
history_deals {
INTEGER ticket "dedup key"
INTEGER order
INTEGER position_id "groups position view"
TEXT symbol
TEXT time
INTEGER type "0/1 trade, else cash event"
INTEGER entry "0 IN, 1 OUT, 2 INOUT, 3 OUT_BY"
REAL volume
REAL price
REAL profit
REAL commission
REAL swap
REAL fee
}
cash_events {
INTEGER ticket
TEXT symbol
TEXT time
INTEGER type
REAL profit
}
positions_reconstructed {
INTEGER position_id
TEXT symbol
TEXT open_time
TEXT close_time
INTEGER direction
REAL volume_open
REAL volume_close
REAL volume_reversal
REAL open_price
REAL close_price
REAL total_profit
INTEGER reversal_count
INTEGER deals_count
}
rates ||--o{ history_deals : "symbol (logical)"
ticks ||--o{ history_deals : "symbol (logical)"
history_orders ||--o{ history_deals : "order ~ ticket (logical)"
history_deals ||--|| cash_events : "VIEW: type NOT IN (0,1)"
history_deals ||--o{ positions_reconstructed : "VIEW: GROUP BY position_id"
```
### Tables and views
| Object | Kind | Source | Notes |
| ------------------------- | ----- | -------------------- | ------------------------------------------------------------------------------------------- |
| `rates` | table | `copy_rates_range` | Indexed on `(symbol, timeframe, time)` when columns exist. |
| `ticks` | table | `copy_ticks_range` | Indexed on `(symbol, time)` when columns exist. |
| `history_orders` | table | `history_orders_get` | Fetched per `--symbol`, then concatenated. |
| `history_deals` | table | `history_deals_get` | Fetched per `--symbol`, then concatenated. Indexed on `(position_id, symbol)` when present. |
| `cash_events` | view | `history_deals` | Non-trade deal types (deposits, balance ops, etc.). Requires `type` column. |
| `positions_reconstructed` | view | `history_deals` | One row per closed `position_id`; volume-weighted prices and reversal stats. |
Column sets can vary with terminal and pdmt5 version. Views are skipped with a warning
when required columns are missing.
### Incremental collection
The `update_history` SDK path uses the same base tables and optional
`cash_events` / `positions_reconstructed` views. It additionally maintains
`rate_<symbol>__<timeframe>` compatibility views when `create_rate_views=True`.
### Rate view resolution
Downstream tools can resolve mt5cli-managed compatibility view names from an
existing SQLite history database without creating files or guessing naming
schemes:
```python
from pathlib import Path
from mt5cli.history import resolve_rate_view_name, resolve_rate_view_names
# Single symbol and granularity
view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1")
# Batch resolution in row-major order
views = resolve_rate_view_names(
Path("history.db"),
["EURUSD", "GBPUSD"],
["M1", "H1"],
)
```
Resolution rules:
- Returns `rate_<symbol>__<timeframe>` when a symbol stores one timeframe.
- Returns `rate_<symbol>__<granularity>_<timeframe>` when multiple timeframes
are stored for the same symbol.
- When multiple naming candidates apply, prefers an existing managed
`rate_*__*` view from the candidate list.
- Falls back to single-timeframe naming when the database path is missing or
`rates` metadata is unavailable.
- Pass `require_existing=True` to raise `ValueError` instead of returning a
best-guess name when the database or view is missing.
- Accepts either a SQLite path or an open `sqlite3.Connection`.
### Rate data loading
The canonical normalized rate table is `rates`; compatibility views are named
with `rate_<symbol>__<timeframe>` for single-timeframe symbols or
`rate_<symbol>__<granularity>_<timeframe>` when a symbol has multiple stored
timeframes. `resolve_rate_table_name()` returns `rates`, while
`resolve_rate_view_name()` returns the per-symbol compatibility view name.
Use `load_rate_data()` or `load_rate_series_from_sqlite(..., table=...)` to load
a single table or view from a SQLite path. Use
`load_rate_series_by_granularity()` to load multiple instrument/granularity
targets without hard-coding view names:
```python
from pathlib import Path
from mt5cli import (
load_rate_series_by_granularity,
load_rate_series_from_sqlite,
)
from mt5cli.history import (
load_rate_data,
resolve_rate_table_name,
resolve_rate_view_name,
)
view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1", require_existing=True)
rates = load_rate_data(Path("history.db"), view, count=1000)
same_rates = load_rate_series_from_sqlite(Path("history.db"), table=view, count=1000)
table = resolve_rate_table_name("EURUSD", "M1") # "rates"
series = load_rate_series_by_granularity(
Path("history.db"),
symbols=["EURUSD", "GBPUSD"],
granularities=["M1", "H1"],
count=500,
)
```
`count` returns the latest rows while preserving chronological order. Missing
tables/views and mismatched `explicit_tables` lengths raise `ValueError` with
the requested database target in the message.
The loader accepts close-based OHLC rate data or tick-like bid/ask data. It
validates that `time` exists, parses timestamps with pandas, and returns a
DataFrame indexed by ascending `DatetimeIndex` named `time`.
### Multi-series rate loading
For loading many rate series at once, build neutral `RateTarget` pairs and load
them from SQLite in one call. View names are resolved via the same
compatibility-view rules, or you can pass `explicit_tables` to bypass resolution:
```python
from pathlib import Path
from mt5cli import build_rate_targets, load_rate_series_from_sqlite
targets = build_rate_targets(["EURUSD", "GBPUSD"], ["M1", "H1"])
series = load_rate_series_from_sqlite(Path("history.db"), targets, count=1000)
frame = series["EURUSD", 1] # keyed by (symbol, integer timeframe)
```
- `build_rate_targets()` returns `RateTarget(symbol, timeframe)` pairs in
row-major order, normalizing timeframe names such as `"M1"` to their integer
values; set `allow_missing_symbol=True` to address series solely by
`explicit_tables` (targets carry `symbol=None`).
- `resolve_rate_tables()` maps targets to table or view names and validates that
any `explicit_tables` count matches the target count. Pass
`require_existing=True` to raise `ValueError` instead of returning a
best-guess name when the database or managed view is missing. When
`explicit_tables` is provided, names are returned as-is and
`require_existing` is ignored.
- `load_rate_series_from_sqlite()` returns a mapping keyed by
`(symbol, integer timeframe)`. Unless `explicit_tables` is supplied, it
requires existing managed `rate_*` compatibility views and raises
`ValueError` when they are missing. Duplicate `(symbol, timeframe)` targets
are rejected.
- `load_rate_series_by_granularity()` is a thin wrapper that builds the targets,
loads the series, and rekeys the result by granularity name to avoid
converting integer timeframes downstream:
```python
from mt5cli import load_rate_series_by_granularity
series = load_rate_series_by_granularity(
"history.db", ["EURUSD"], ["M1", "H1"], count=1000
)
frame = series["EURUSD", "M1"] # keyed by (symbol | None, granularity_name)
```
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# API Reference
This section contains the complete API documentation for mt5cli.
This section documents the mt5cli public Python API and CLI modules.
## Modules
Start with the [Public API Contract](public-contract.md) for the stable
downstream SDK surface, CLI boundary, internal modules, and out-of-scope strategy
responsibilities.
The mt5cli package consists of the following modules:
## Public API layers
### [CLI](cli.md)
| Module | Purpose |
| ----------------------------------------- | ------------------------------------------------------------------------- |
| [Public API Contract](public-contract.md) | Stable downstream SDK exports, CLI boundary, and out-of-scope items |
| [Client](client.md) | `MT5Client` session abstraction for data access and order primitives |
| [Schemas](schemas.md) | Canonical DataFrame contracts and normalization helpers |
| [Converters](converters.md) | Symbol, timeframe, timezone, and date-range utilities |
| [Exceptions](exceptions.md) | Stable mt5cli exception types and MT5 error normalization |
| [SDK](sdk.md) | Module-level fetch helpers, multi-account collectors, incremental history |
| [Trading](trading.md) | Trading-capable sessions and operational helpers |
| [History Collection (SQLite)](history.md) | SQLite schema, incremental writes, dedup, and rate views |
| [CLI](cli.md) | Typer commands that delegate to the Python API |
| [Utils](utils.md) | Parsing helpers and Click parameter types |
Command-line interface module providing typer-based commands for exporting MetaTrader 5 data to CSV, JSON, Parquet, and SQLite3 formats.
## Architecture overview
## Architecture Overview
The package follows a simple architecture built on top of pdmt5:
1. **CLI Layer** (`cli.py`): Typer application with subcommands for each data type, custom Click parameter types for datetime/timeframe/tick flags parsing, and format detection/export utilities.
2. **Data Layer** (via `pdmt5`): Uses `Mt5DataClient` and `Mt5Config` from the pdmt5 package for all MetaTrader 5 data access.
## Usage Guidelines
All modules follow these conventions:
- **Type Safety**: All functions include comprehensive type hints
- **Error Handling**: User-friendly error messages via typer
- **Documentation**: Google-style docstrings with examples
- **Validation**: Custom Click parameter types for input validation
## Quick Start
```bash
# Export account information to CSV
mt5cli -o account.csv account-info
# Export EURUSD H1 rates to Parquet
mt5cli -o rates.parquet rates-from --symbol EURUSD --timeframe H1 \
--date-from 2024-01-01 --count 1000
# Export ticks to JSON
mt5cli -o ticks.json ticks-from --symbol EURUSD \
--date-from 2024-01-01 --count 500 --flags ALL
# Export to SQLite3 with custom table name
mt5cli -o data.db --table symbols symbols --group "*USD*"
```mermaid
flowchart TD
App["Downstream application"] --> Client["MT5Client"]
CLI["mt5cli CLI"] --> Client
Client --> SDK["sdk / pdmt5"]
Client --> Schemas["schemas"]
History["history SQLite"] --> Utils["utils export"]
SDK --> PDMT5["pdmt5.Mt5DataClient"]
```
## Python API
Downstream packages should depend on the package root exports documented in the
[Public API Contract](public-contract.md) (`MT5Client`,
`collect_history`, `load_rate_series_from_sqlite`, etc.) rather than private
modules. Lower-level helpers are accessible directly from their owning modules.
`MT5Client.order_send()` is a live execution primitive that can place real trades. mt5cli exposes minimal execution helpers only; strategy logic, signals, backtests, and optimization remain out of scope and must be implemented downstream with explicit execution gating.
## Quick start
```python
from mt5cli import detect_format, export_dataframe
import pandas as pd
from mt5cli import MT5Client, build_config, mt5_session
# Detect output format from file extension
fmt = detect_format(Path("output.parquet")) # Returns "parquet"
# Export a DataFrame
df = pd.DataFrame({"symbol": ["EURUSD"], "bid": [1.1234]})
export_dataframe(df, Path("output.csv"), "csv")
with mt5_session(build_config(login=12345)) as client:
rates = client.copy_rates_range("EURUSD", "H1", "2024-01-01", "2024-02-01")
positions = client.positions()
```
## Examples
```bash
mt5cli -o account.csv account-info
mt5cli -o rates.parquet rates-range --symbol EURUSD --timeframe H1 \
--date-from 2024-01-01 --date-to 2024-02-01
```
See individual module pages for detailed usage examples and code samples.
See individual module pages for detailed usage examples.
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# Public API Contract
mt5cli is the canonical operational trading SDK and CLI/batch layer over pdmt5.
The intended dependency direction is:
```text
downstream app -> mt5cli -> pdmt5 -> MetaTrader 5
```
## Responsibility boundary
| Layer | Owns |
| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **pdmt5** | MT5 core wrapper; DataFrame/dict conversion; canonical MT5 constants and parsers; direct low-level order primitives |
| **mt5cli** | CLI/batch workflows; SQLite history collection; normalized datasets; closed-bar helpers; small downstream operational SDK; generic broker-facing margin/volume/order orchestration |
| **downstream** | Strategy logic; signals; risk policy; backtesting; optimization; YAML/application semantics |
Downstream code should import raw pdmt5 types and constants (such as
`Mt5Config`, `Mt5RuntimeError`, `TIMEFRAME_MAP`, `COPY_TICKS_MAP`) directly
from `pdmt5` when needed. mt5cli does not serve as a pass-through compatibility
namespace for pdmt5. mt5cli's trading helpers type their client parameter against
an internal protocol backed by `pdmt5.Mt5DataClient`; `Mt5TradingClient` is no
longer required. `Mt5TradingError` is conditionally imported where still present
in pdmt5, but mt5cli raises `Mt5OperationError` for all trading-related failures.
Note: the former `mt5cli` re-export `TICK_FLAG_MAP` corresponds to `COPY_TICKS_MAP`
in pdmt5 — the name changed, it was not simply moved.
Downstream packages should import from the package root (`from mt5cli import
...`). The contract set `STABLE_SDK_EXPORTS` in `mt5cli.contract` enumerates
every package-root symbol. Lower-level helpers (schema utilities, export
functions, parser helpers, low-level MT5 wrappers) are available directly from
their owning modules (`mt5cli.schemas`, `mt5cli.utils`, `mt5cli.converters`,
`mt5cli.sdk`, etc.) and are not part of the root SDK surface.
## Stable downstream SDK API
These names are exported from `mt5cli` and enumerated in
`mt5cli.STABLE_SDK_EXPORTS` (defined in `mt5cli.contract`).
### Session lifecycle and configuration
| Symbol | Role |
| ----------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `MT5Client` | Read-only data client with optional `order_check` / `order_send` |
| `build_config` | Build `pdmt5.Mt5Config` from connection fields; `login` accepts `int \| str \| None` — numeric strings are coerced to `int`, blank strings are treated as unset, and `${ENV_VAR}` / `$ENV_NAME` placeholders in string parameters are expanded when `allow_whole_dollar_env=True` |
| `mt5_session` | Context manager: initialize, login, yield client, shutdown |
| `create_trading_client`, `mt5_trading_session` | Trading-capable MT5 client lifecycle; returns a client supporting order execution and account management |
| `AccountSpec` | Generic account group: symbols plus optional credentials |
| `resolve_account_spec`, `resolve_account_specs` | Merge overrides and expand `${ENV_VAR}` placeholders; opt-in `allow_whole_dollar_env` for bare `$NAME` |
### Closed-bar rate helpers
MetaTrader 5 returns the still-forming bar as the last row when
`start_pos=0`. Use these helpers instead of reimplementing bar trimming or
timestamp normalization in downstream apps.
| Symbol | Role |
| ------------------------------------------------ | ------------------------------------------------------------------------------- |
| `drop_forming_rate_bar` | Remove the last row from chronologically ordered rate data |
| `fetch_latest_closed_rates` | Single connected client: fetch `count + 1`, drop forming bar |
| `fetch_latest_closed_rates_for_trading_client` | Closed bars from an active trading client session; returns RangeIndex |
| `fetch_latest_closed_rates_indexed` | Same as above but returns a UTC `DatetimeIndex` named `"time"` (no time column) |
| `collect_latest_closed_rates_for_accounts` | Multi-account closed bars with optional retry wrapper |
| `collect_latest_closed_rates_by_granularity` | Same data keyed by `(symbol, granularity_name)` |
| `collect_latest_rates_for_accounts_with_retries` | Bounded exponential backoff for transient MT5 errors |
### SQLite history collection and rate loading
| Symbol | Role |
| ----------------------------------------------------------------- | -------------------------------------------------------------------------------------------- |
| `collect_history` | One-shot date-range export into SQLite |
| `update_history`, `update_history_with_config` | Incremental append from `MAX(time)` cursors |
| `ThrottledHistoryUpdater` | Minimum interval between successful incremental updates; optional `update_backend` injection |
| `RateTarget`, `build_rate_targets` | Neutral `(symbol, timeframe)` series descriptors |
| `load_rate_series_from_sqlite`, `load_rate_series_by_granularity` | Load one or many series; fail clearly when managed views are missing |
See [History Collection (SQLite)](history.md) for schema, view naming, and ER
diagrams.
### Trading and sizing primitives (generic)
These helpers implement broker-facing calculations only. They do not encode
strategy entries, exits, Kelly sizing, or signal logic.
| Symbol | Role |
| ------------------------------------------------------------------------------------------------------------------------------ | ----------------------------------------------------------------- |
| `get_account_snapshot`, `get_symbol_snapshot`, `get_tick_snapshot`, `get_positions_frame` | Normalized account/symbol/tick/position views |
| `extract_tick_price` | Positive finite bid/ask extraction from tick mappings |
| `detect_position_side` | Net long / short / flat from open positions |
| `calculate_spread_ratio` | Relative bid-ask spread |
| `calculate_margin_and_volume`, `calculate_volume_by_margin`, `calculate_new_position_margin_ratio` | Margin budget and volume sizing |
| `normalize_order_volume`, `estimate_order_margin`, `calculate_positions_margin` | Broker volume normalization and margin totals |
| `calculate_positions_margin_by_symbol` | Per-symbol margin map (resilient, first-seen order) |
| `calculate_positions_margin_safe` | Summed total margin across symbols (failed symbols skipped) |
| `calculate_projected_margin_ratio` | Estimated symbol-scoped margin/equity after optional new exposure |
| `calculate_account_projected_margin_ratio` | Account snapshot margin/equity after optional new exposure |
| `calculate_symbol_group_margin_ratio` | Estimated symbol-group margin/equity with optional exposure |
| `determine_order_limits` | SL/TP price levels from ratios |
| `calculate_trailing_stop_updates` | Per-ticket generic trailing stop-loss update plan |
| `ensure_symbol_selected` | Select/verify Market Watch visibility |
| `place_market_order`, `close_open_positions`, `update_sltp_for_open_positions`, `update_trailing_stop_loss_for_open_positions` | Order execution helpers (`dry_run` supported) |
| `MarginVolume`, `OrderLimits`, `OrderExecutionResult` | Typed return contracts for order helpers |
| `OrderSide`, `OrderFillingMode`, `OrderTimeMode`, `PositionSide`, `ExecutionStatus` | Typed enums for order helpers |
| `ProjectionMode` | Literal type for `calculate_symbol_group_margin_ratio` projection |
`calculate_symbol_group_margin_ratio` accepts an optional `projection_mode`
parameter (`"add"` by default). Pass `projection_mode="replace_symbol"` to
subtract current exposure for `new_symbol` before adding the candidate margin —
useful for reversal-style projections. mt5cli only calculates broker-facing
exposure; downstream applications own thresholds, risk guard actions, and
strategy policy.
`MT5Client.order_send()` and CLI `order-send --yes` are live execution paths.
Order helpers validate broker stop-level distance in `determine_order_limits()` and
raise `Mt5OperationError` when computed SL/TP prices are too close to the entry
quote. Validation uses `trade_stops_level * point` from the current quote and
symbol metadata as a pre-check only; it does not guarantee live order acceptance
after price movement and does not inspect `trade_freeze_level`. Live
`place_market_order()` and SL/TP updates call
`ensure_symbol_selected()` so hidden symbols are added to Market Watch before
sending requests. Failed, malformed, or unknown broker retcodes are fail-closed
and returned as `status="failed"` with normalized `request` / `response` details;
`dry_run=True` never calls `ensure_symbol_selected()` or `order_send()`.
### Grafana observability (SQLite read model)
These helpers prepare a SQLite database as a Grafana datasource. All DDL is
idempotent (`CREATE TABLE IF NOT EXISTS`, `DROP VIEW IF EXISTS` + `CREATE
VIEW`, `CREATE INDEX IF NOT EXISTS`). Missing source tables are skipped with a
warning rather than raising an error.
| Symbol | Role |
| ---------------------------------- | ----------------------------------------------------------------------------------------------- |
| `update_observability` | Append one timestamped snapshot row per data type; accepts an already-connected `Mt5DataClient` |
| `update_observability_with_config` | Standalone wrapper: opens/closes MT5 connection automatically around `update_observability` |
Both functions write to the SQLite path given by `output=`. The optional
`symbols` parameter filters `positions_get` / `orders_get` by symbol.
`with_grafana_schema=False` (default) skips Grafana view/index setup; run
`grafana-schema` once to set up the schema, then call `snapshot` repeatedly
without this flag.
**Snapshot tables** (created by `create_snapshot_tables` in `mt5cli.grafana`):
| Table | Content |
| -------------------- | ----------------------------------------- |
| `account_snapshots` | Balance, equity, margin, free-margin, P&L |
| `position_snapshots` | Open positions: symbol, volume, profit, … |
| `order_snapshots` | Active orders: symbol, type, price, … |
| `terminal_snapshots` | Terminal connectivity and build info |
| `snapshot_runs` | Per-run status (`ok` / `error`) timestamp |
**Grafana time-series views** (integer epoch-second `time` column; snapshot views also expose `run_id`):
| View | Source |
| ---------------------------- | -------------------------------- |
| `grafana_rates` | `rates` table |
| `grafana_ticks` | `ticks` table |
| `grafana_history_deals` | `history_deals` |
| `grafana_history_orders` | `history_orders` |
| `grafana_trade_deals` | `history_deals` trade types only |
| `grafana_cash_events` | `history_deals` non-trade events |
| `grafana_symbol_pnl` | Per-close-deal P&L per symbol |
| `grafana_account_snapshots` | `account_snapshots` |
| `grafana_position_snapshots` | `position_snapshots` |
| `grafana_order_snapshots` | `order_snapshots` |
| `grafana_terminal_snapshots` | `terminal_snapshots` |
**Grafana static summary views** (no `time` column; use for table/stat panels, not time-series):
| View | Source |
| ---------------------- | ------------------------------------- |
| `grafana_realized_pnl` | Cumulative realized PnL per symbol |
| `grafana_trade_stats` | Win/loss counts and profit per symbol |
Lower-level helpers (`ensure_grafana_schema`, `create_grafana_views`,
`create_grafana_indexes`, `create_snapshot_tables`, `start_snapshot_run`,
`insert_account_snapshot`, `insert_position_snapshots`, `insert_order_snapshots`,
`insert_terminal_snapshot`, `record_snapshot_run`) are available directly from
`mt5cli.grafana` and are not part of the package-root stable surface.
### Errors
| Symbol | Role |
| -------------------------------------------------------------------------- | ----------------------------- |
| `Mt5CliError`, `Mt5ConnectionError`, `Mt5OperationError`, `Mt5SchemaError` | Stable mt5cli exception types |
## Module-scoped helpers
Lower-level helpers are available from their owning modules and are not part
of the package-root stable surface. Import them directly when needed:
| Module | Examples |
| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `mt5cli.grafana` | `ensure_grafana_schema`, `create_grafana_views`, `create_grafana_indexes`, `create_snapshot_tables`, `start_snapshot_run`, `insert_account_snapshot`, `record_snapshot_run` |
| `mt5cli.history` | `resolve_rate_view_name`, `resolve_rate_tables`, `load_rate_data`, `build_rate_view_name` |
| `mt5cli.sdk` | `copy_rates_from`, `copy_ticks_from`, `account_info`, `symbols`, `mt5_summary`, `latest_rates` |
| `mt5cli.schemas` | `DataKind`, `normalize_dataframe`, `validate_schema`, `DEDUP_KEYS` |
| `mt5cli.utils` | `Dataset`, `IfExists`, `detect_format`, `export_dataframe`, `export_dataframe_to_sqlite` |
| `mt5cli.converters` | `normalize_symbol`, `ensure_utc`, `parse_date_range`, `granularity_name` |
| `mt5cli.exceptions` | `normalize_mt5_exception`, `call_with_normalized_errors`, `is_recoverable_mt5_error` |
## CLI commands
The Typer application in `mt5cli.cli` exposes file-export commands documented in
[CLI Module](cli.md) and the project README. CLI commands:
- Require `-o/--output` and write CSV, JSON, Parquet, or SQLite.
- Accept global MT5 connection options (`--login`, `--password`, `--server`,
`--path`, `--timeout`).
- Delegate to the same Python APIs described here; they are not duplicated
business logic.
`grafana-schema` initializes Grafana views, indexes, and snapshot tables in the
target SQLite database without connecting to MT5. It is idempotent and safe to
run repeatedly.
`snapshot` appends one timestamped row per enabled data type
(`--with-account`, `--with-positions`, `--with-orders`, `--with-terminal`) and
never places orders or modifies trading state. Both commands require
`-o/--output` to point at a `.db` / SQLite file.
`order-send` is the expert raw-request path; it requires `--yes` and a fully
constructed request payload. `close-positions` is the safer high-level helper
that closes open positions by `--symbol` or `--ticket` using
`close_open_positions()`. Both `order-send --yes` and `close-positions --yes`
are live execution paths. `close-positions --dry-run` previews close orders
without placing them and does not require `--yes`.
## Internal helpers (not stable)
Do not import these for downstream contracts; they may change without a semver
notice:
| Module | Examples |
| ------------------------ | ------------------------------------------------------------------------- |
| `mt5cli.sdk` | `connected_client`, `_run_with_client`, private coercion helpers |
| `mt5cli.history` | `write_*_dataset`, `deduplicate_history_tables`, `parse_sqlite_timestamp` |
| `mt5cli.retry` | `retry_with_backoff` |
| `mt5cli.cli` | Typer command handlers and Click parameter types |
| Leading-underscore names | Any `_`-prefixed function or method |
Use the package-root stable exports instead of reaching into submodule
internals.
## Explicitly out of scope
mt5cli must **not** implement downstream strategy or research responsibilities.
The following belong in consuming applications, not in mt5cli:
- Signal detection (for example AR-GARCH or other model-specific triggers)
- Backtesting, walk-forward analysis, or parameter optimization
- Strategy-specific risk policy, position sizing systems, or Kelly fractions
- Entry/exit decision logic or YAML strategy semantics
- Application-specific credential schema keys wired into mt5cli internals
mt5cli provides connection lifecycle, normalized data access, SQLite history
machinery, closed-bar helpers, generic margin/volume/spread/SL/TP utilities, and
optional order primitives so downstream apps can focus on strategy code behind
their own adapter layer.
## Contract verification
`tests/test_contracts.py` asserts that every name in `STABLE_SDK_EXPORTS` is
importable from `mt5cli`, that all package-root exports are covered by the
stable set, and documents key closed-bar, SQLite loading, account-resolution,
and trading-session behaviors.
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# Schemas
::: mt5cli.schemas
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# SDK Module
::: mt5cli.sdk
## Resilient multi-account orchestration
The SDK ships strategy-agnostic helpers for building long-running collectors on
top of the read-only client. None of them depend on a particular trading
application.
### Retrying transient rate collection
`collect_latest_rates_for_accounts_with_retries()` wraps
`collect_latest_rates_for_accounts()` with bounded exponential backoff. Only
`pdmt5.Mt5TradingError` and `pdmt5.Mt5RuntimeError` are retried; the final
failure is re-raised once `retry_count` is exhausted.
```python
from mt5cli import AccountSpec, collect_latest_rates_for_accounts_with_retries
accounts = [AccountSpec(symbols=["EURUSD"], login=12345)]
rates = collect_latest_rates_for_accounts_with_retries(
accounts,
["M1", "H1"],
count=500,
retry_count=3,
backoff_base=2, # sleeps 2s, 4s, 8s between attempts
)
```
### Latest closed rate bars
MetaTrader 5 `start_pos=0` includes the still-forming current bar as the last
row. `fetch_latest_closed_rates()` handles one connected `MT5Client`; use
`fetch_latest_closed_rates_for_trading_client()` from an active
`Mt5TradingClient` session. Multi-account helpers fetch `count + 1` bars, drop
that row with `drop_forming_rate_bar()`, and validate each series is non-empty. Returned frames are ordered
oldest-to-newest and may contain fewer than `count` rows only when MT5 returns
fewer closed bars.
```python
from mt5cli import (
AccountSpec,
collect_latest_closed_rates_by_granularity,
fetch_latest_closed_rates,
)
closed = fetch_latest_closed_rates(
client,
symbol="EURUSD",
granularity="M1",
count=500,
)
rates = collect_latest_closed_rates_by_granularity(
[AccountSpec(symbols=["EURUSD"], login=12345)],
["M1", "H1"],
count=500,
retry_count=3,
)
closed_m1 = rates["EURUSD", "M1"]
```
Use `collect_latest_closed_rates_by_granularity()` when callers prefer keys such
as `("EURUSD", "M1")` instead of integer timeframes.
### Resolving credentials and `${ENV_VAR}` placeholders
`resolve_account_spec()` / `resolve_account_specs()` merge explicit override
values over `AccountSpec` fields and expand `${ENV_VAR}` placeholders, keeping
secrets out of plan/config files. A missing environment variable raises
`ValueError`.
```python
import os
from mt5cli import AccountSpec, resolve_account_specs
os.environ["MT5_LOGIN"] = "12345"
os.environ["MT5_PASSWORD"] = "secret"
accounts = [
AccountSpec(symbols=["EURUSD"], login="${MT5_LOGIN}", password="${MT5_PASSWORD}")
]
resolved = resolve_account_specs(accounts, server="Broker-Demo")
# resolved[0].login == "12345", resolved[0].server == "Broker-Demo"
```
Pass `allow_whole_dollar_env=True` to also expand strings whose **entire value**
is a bare `$ENV_NAME` identifier (no braces). This opt-in covers
`substitute_env_placeholders()`, `resolve_account_spec()`,
`resolve_account_specs()`, and `build_config()`. Note: `build_config` cannot
expand `login` because that parameter is `int | None`; use
`resolve_account_spec` for a string `login` placeholder. Partial strings such as
`"plan$pass"`, `"abc$ENV"`, or `"$ENV-suffix"` are never expanded — only an
exact `$IDENTIFIER` whole-string match qualifies. The default is `False` to
preserve backward compatibility.
```python
import os
from mt5cli import AccountSpec, resolve_account_specs
os.environ["MT5_PASSWORD"] = "secret"
accounts = [AccountSpec(symbols=["EURUSD"], password="$MT5_PASSWORD")]
resolved = resolve_account_specs(accounts, allow_whole_dollar_env=True)
# resolved[0].password == "secret"
```
### Throttled incremental history updates
`ThrottledHistoryUpdater` wraps `update_history()` with a minimum interval
between successful runs (using a monotonic clock), so an application loop can
call it every iteration without over-fetching.
```python
from pdmt5 import Mt5Config, Mt5DataClient
from mt5cli import ThrottledHistoryUpdater
from mt5cli.utils import Dataset
updater = ThrottledHistoryUpdater(
output="history.db",
datasets={Dataset.rates},
timeframes=["M1"],
interval_seconds=60, # <= 0 updates on every call
)
client = Mt5DataClient(config=Mt5Config(login=12345))
client.initialize_and_login_mt5()
try:
while True:
updater.update(client, ["EURUSD", "GBPUSD"]) # no-op until 60s elapse
# ... do other work; break when shutting down ...
finally:
client.shutdown()
```
Pass `update_backend` to substitute the default `update_history` implementation
without monkey-patching `mt5cli.sdk.update_history`. The callable receives the
same keyword arguments as `update_history` (`client`, `output`, `symbols`,
`datasets`, `timeframes`, `flags`, `lookback_hours`, `with_views`,
`include_account_events`). The resolved backend is stored on
`updater.update_backend` for inspection or subclassing.
```python
from mt5cli import ThrottledHistoryUpdater, update_history
def app_update_history(**kwargs) -> None:
update_history(**kwargs) # or delegate to application-specific logic
updater = ThrottledHistoryUpdater(
output="history.db",
interval_seconds=60,
update_backend=app_update_history,
)
```
By default recoverable errors (`Mt5TradingError`, `Mt5RuntimeError`,
`sqlite3.Error`, `ValueError`, `OSError`, and MT5 client capability
`AttributeError` / `TypeError` for history API methods) propagate so the caller
controls logging; pass `suppress_errors=True` to swallow them and return
`False` without advancing the throttle. Other `AttributeError` / `TypeError`
values always propagate. Input validation (`_resolve_update_history_request`)
runs before any MT5 or SQLite calls, but when `suppress_errors=True` the
resulting `ValueError` is suppressed along with other recoverable errors.
## Trading-capable sessions
For order placement and trading calculations, use the dedicated
[Trading module](trading.md). Use `mt5_session()` / `MT5Client` for read-only
collection.
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# Trading Module
::: mt5cli.trading
## Trading-capable MT5 sessions
`create_trading_client()` and `mt5_trading_session()` complement the read-only
`mt5_session()` helper in `sdk.py`. They return or yield an initialized
client supporting order execution and account management, use `Mt5Config.path`
to launch the terminal when configured, and `mt5_trading_session()` always
calls `shutdown()` on exit.
```python
from mt5cli import create_trading_client, mt5_trading_session
with mt5_trading_session(
path=r"C:\Program Files\MetaTrader 5\terminal64.exe",
login="12345",
password="secret",
server="Broker-Demo",
retry_count=2,
) as client:
positions = client.positions_get_as_df(symbol="EURUSD")
client = create_trading_client(login=12345, server="Broker-Demo")
try:
account = client.account_info_as_dict()
finally:
client.shutdown()
```
`login` accepts `int`, numeric `str`, or an empty string; empty strings are
treated as unset. `path`, `password`, `server`, and `timeout` are forwarded to
`pdmt5.Mt5Config`, and omitted `timeout` values keep the lower-level default.
Use `mt5_session()` / `MT5Client` for read-only data collection.
## State and order helpers
These helpers are strategy-agnostic and do not depend on signal detection,
betting logic, or scheduling code in downstream applications.
```python
from mt5cli import (
calculate_positions_margin,
calculate_spread_ratio,
calculate_margin_and_volume,
close_open_positions,
detect_position_side,
determine_order_limits,
estimate_order_margin,
fetch_latest_closed_rates_for_trading_client,
fetch_latest_closed_rates_indexed,
get_account_snapshot,
get_positions_frame,
get_symbol_snapshot,
get_tick_snapshot,
normalize_order_volume,
place_market_order,
)
account = get_account_snapshot(client)
symbol = get_symbol_snapshot(client, "EURUSD")
tick = get_tick_snapshot(client, "EURUSD")
positions = get_positions_frame(client, "EURUSD")
side = detect_position_side(client, "EURUSD")
spread_ratio = calculate_spread_ratio(client, "EURUSD")
volume = normalize_order_volume(
0.15,
volume_min=symbol["volume_min"],
volume_max=symbol["volume_max"],
volume_step=symbol["volume_step"],
)
buy_margin = (
estimate_order_margin(client, "EURUSD", "BUY", volume) if volume > 0 else 0.0
)
open_margin = calculate_positions_margin(client, symbols=["EURUSD"])
closed_bars = fetch_latest_closed_rates_for_trading_client(
client,
symbol="EURUSD",
granularity="M1",
count=100,
)
# Or fetch with a UTC DatetimeIndex instead of a "time" column:
indexed_bars = fetch_latest_closed_rates_indexed(
client,
symbol="EURUSD",
granularity="M1",
count=100,
)
# indexed_bars.index is a UTC-aware DatetimeIndex named "time"
sizing = calculate_margin_and_volume(
client,
"EURUSD",
unit_margin_ratio=0.5,
preserved_margin_ratio=0.2,
)
limits = determine_order_limits(
client,
"EURUSD",
side="long",
stop_loss_limit_ratio=0.01,
take_profit_limit_ratio=0.02,
)
preview = place_market_order(
client,
symbol="EURUSD",
volume=sizing["buy_volume"],
order_side="BUY",
sl=limits["stop_loss"],
tp=limits["take_profit"],
dry_run=True,
)
closed = close_open_positions(client, symbols="EURUSD", dry_run=True)
```
`detect_position_side()` returns `long` for buy-only exposure, `short` for
sell-only exposure, and `None` for no positions or mixed long/short exposure.
`calculate_spread_ratio()` uses `(ask - bid) / ((ask + bid) / 2)` and raises
`Mt5OperationError` when bid or ask is missing or non-positive.
`normalize_order_volume()` returns `0.0` for invalid constraints or
sub-minimum requests; check the result before calling `estimate_order_margin()`,
which requires a positive finite volume. `calculate_positions_margin()` silently
skips rows with missing symbols, non-positive volumes, non-finite volumes, or
unsupported position types, but propagates `Mt5OperationError` from `estimate_order_margin()` when a valid row
encounters invalid tick data or margin results from the broker.
SL/TP ratios for `determine_order_limits()` must satisfy `0 <= ratio < 1`; `0`
omits that level. SL/TP prices are rounded with symbol `digits` metadata when
available. `determine_order_limits()` pre-validates computed SL/TP prices against
available `trade_stops_level * point` metadata when present; violations raise
`Mt5OperationError`. This is a planning helper only: it does not guarantee broker
acceptance because live validation can still depend on price movement, bid/ask
side, freeze levels, and server-side rules, and it does not validate
`trade_freeze_level`. When symbol metadata cannot be loaded, protective prices
still round with `digits=8` and stop-level validation is skipped.
`unit_margin_ratio` and `preserved_margin_ratio` for `calculate_margin_and_volume()`
accept `0 <= ratio <= 1`; `unit_margin_ratio=0` requests one minimum valid unit
when the post-reserve margin can afford it. Negative `margin_free` is clamped to
`0.0` before sizing. Execution helpers return normalized `OrderExecutionResult`
dictionaries containing the request, response, status, retcode, and `dry_run`
flag; `dry_run=True` never sends an order or mutates Market Watch visibility.
`ensure_symbol_selected()` adds hidden symbols to Market Watch before live order
placement and SL/TP updates. Failed, malformed, or unknown broker retcodes are
fail-closed and returned as `status="failed"` while keeping the normalized
response for inspection.
## Order planning return contracts
```python
from mt5cli import MarginVolume, OrderLimits, OrderExecutionResult
sizing: MarginVolume = calculate_margin_and_volume(
client,
"EURUSD",
unit_margin_ratio=0.5,
preserved_margin_ratio=0.2,
)
limits: OrderLimits = determine_order_limits(
client,
"EURUSD",
side="long",
stop_loss_limit_ratio=0.01,
take_profit_limit_ratio=0.02,
)
preview: OrderExecutionResult = place_market_order(
client,
symbol="EURUSD",
volume=sizing["buy_volume"],
order_side="BUY",
sl=limits["stop_loss"],
tp=limits["take_profit"],
dry_run=True,
)
updates: list[OrderExecutionResult] = update_sltp_for_open_positions(
client,
symbol="EURUSD",
stop_loss=limits["stop_loss"],
dry_run=True,
)
```
Closes issue #33: strategy-neutral order planning and execution helpers exposed
through the stable package root without embedding entry/exit policy.
## Migration from application-local helpers
| Application-local concern | mt5cli replacement |
| -------------------------------------------------------- | --------------------------------------------------------------------------------------- |
| Manual terminal spawn/kill around trading code | `mt5_trading_session()` |
| Local position-side detection | `detect_position_side()` |
| Local margin/volume sizing | `calculate_margin_and_volume()` |
| Local broker volume step normalization | `normalize_order_volume()` |
| Local order or position margin estimation | `estimate_order_margin()`, `calculate_positions_margin()` |
| Local closed-bar fetch from a trading session | `fetch_latest_closed_rates_for_trading_client()`, `fetch_latest_closed_rates_indexed()` |
| Local SL/TP price derivation | `determine_order_limits()` |
| Throttled SQLite history loop with ad-hoc error handling | `ThrottledHistoryUpdater(suppress_errors=True)` |
Keep read-only data collection on `mt5_session()` / `MT5Client`; use
`mt5_trading_session()` only where order placement or trading calculations are
required.
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# Utils Module
::: mt5cli.utils
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# mt5cli
Command-line tool for MetaTrader 5 data export.
Generic MT5 data and execution infrastructure for Python applications.
## Overview
mt5cli is a CLI application that exports MetaTrader 5 trading data to multiple file formats. It is built on top of [pdmt5](https://github.com/dceoy/pdmt5), a pandas-based data handler for MetaTrader 5.
mt5cli provides a stable `MT5Client` Python API, standardized dataset schemas, storage helpers, and a CLI for exporting MetaTrader 5 data. It is built on top of [pdmt5](https://github.com/dceoy/pdmt5), a pandas-based data handler for MetaTrader 5.
## Architecture
- **pdmt5** — canonical MT5 client, DataFrame/trading primitives, and MT5 constant parsing (`TIMEFRAME_*`, `COPY_TICKS_*`, order types).
- **mt5cli** — public `MT5Client` API, schema contracts, storage helpers, CLI commands, and SQLite history collection built on pdmt5.
- **mt5api** — sibling HTTP adapter for remote MT5 access; not a dependency of mt5cli.
## Features
@@ -13,6 +19,7 @@ mt5cli is a CLI application that exports MetaTrader 5 trading data to multiple f
- **Comprehensive data access**: Rates, ticks, account info, symbols, orders, positions, and trading history
- **Flexible timeframes**: Named timeframes (M1, H1, D1, etc.) and numeric values
- **Connection management**: Optional credentials, server, and timeout configuration
- **SQLite rate loading**: Load mt5cli-managed rate tables/views for offline workflows
## Installation
@@ -20,6 +27,71 @@ mt5cli is a CLI application that exports MetaTrader 5 trading data to multiple f
pip install mt5cli
```
Parquet export is not included by default. To enable it, install the `parquet` extra:
```bash
pip install "mt5cli[parquet]"
```
## Python API for downstream packages
Import `MT5Client` for generic MT5 data access, schema normalization, and optional order primitives.
```python
from datetime import UTC, datetime
from pathlib import Path
from mt5cli import (
MT5Client,
build_config,
collect_history,
mt5_session,
)
from mt5cli.history import load_rate_data, resolve_rate_view_name
from mt5cli.schemas import DataKind, normalize_dataframe
from mt5cli.sdk import minimum_margins, recent_ticks
from mt5cli.utils import Dataset, export_dataframe
# Persistent session for multiple calls
with mt5_session(build_config(login=12345, server="Broker-Demo")) as client:
rates = client.copy_rates_range(
"EURUSD",
timeframe="H1",
date_from="2024-01-01",
date_to="2024-02-01",
)
positions = client.positions()
check = client.order_check({"action": 1, "symbol": "EURUSD", "volume": 0.1})
# Normalize MT5 frames to the public schema contract before storage
closed_rates = normalize_dataframe(
rates, DataKind.rates, symbol="EURUSD", timeframe="H1"
)
export_dataframe(closed_rates, Path("rates.csv"), "csv")
# Offline rate loading from mt5cli-managed SQLite history
view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1", require_existing=True)
offline_rates = load_rate_data(Path("history.db"), view, count=1000)
# One-off helpers still work without instantiating a client
ticks = recent_ticks("EURUSD", seconds=300)
margins = minimum_margins("EURUSD")
collect_history(
Path("history.db"),
symbols=["EURUSD", "GBPUSD"],
date_from=datetime(2024, 1, 1, tzinfo=UTC),
date_to=datetime(2024, 2, 1, tzinfo=UTC),
datasets={Dataset.rates, Dataset.history_deals},
)
```
Schema contracts live in `mt5cli.schemas` (`DataKind`, `validate_schema`, `normalize_dataframe`). Export and storage helpers are in `mt5cli.utils` (`Dataset`, `export_dataframe`) and `mt5cli.history`.
`MT5Client.order_send()` is a live execution primitive: it can place real trades on the connected account. mt5cli does not implement strategy logic, signal generation, backtesting, or optimization — downstream applications must gate live execution explicitly (the CLI requires `--yes` for `order-send`).
`MT5Client.mt5_summary()` returns structured nested Python values. Use `MT5Client.mt5_summary_as_df()` when you need a one-row DataFrame for export.
## Quick Start
```bash
@@ -50,14 +122,16 @@ mt5cli --login 12345 --password mypass --server MyBroker-Demo \
| ---------------- | ---------------------------------- |
| `rates-from` | Export rates from a start date |
| `rates-from-pos` | Export rates from a start position |
| `latest-rates` | Export latest rates |
| `rates-range` | Export rates for a date range |
### Ticks
| Command | Description |
| ------------- | ------------------------------ |
| `ticks-from` | Export ticks from a start date |
| `ticks-range` | Export ticks for a date range |
| Command | Description |
| -------------- | ----------------------------------- |
| `ticks-from` | Export ticks from a start date |
| `ticks-range` | Export ticks for a date range |
| `ticks-recent` | Export ticks from a trailing window |
### Information
@@ -70,20 +144,66 @@ mt5cli --login 12345 --password mypass --server MyBroker-Demo \
| `symbols` | Export symbol list |
| `symbol-info` | Export symbol details |
| `symbol-info-tick` | Export the last tick for a symbol |
| `minimum-margins` | Export minimum-volume margin summary |
| `market-book` | Export market depth (order book) |
### Trading
### Trading State
| Command | Description |
| ---------------- | ------------------------------------------- |
| `orders` | Export active orders |
| `positions` | Export open positions |
| `history-orders` | Export historical orders |
| `history-deals` | Export historical deals |
| `order-check` | Check funds sufficiency for a trade request |
| `order-send` | Send a trade request to the trade server (`--yes` required) |
| Command | Description |
| ---------------------- | ------------------------------------------------------------------- |
| `orders` | Export active orders |
| `positions` | Export open positions |
| `history-orders` | Export historical orders |
| `history-deals` | Export historical deals |
| `recent-history-deals` | Export historical deals from a trailing window |
| `mt5-summary` | Export terminal/account status summary |
| `order-check` | Check funds sufficiency for a trade request (read-only, no `--yes`) |
Use `order-check` to validate a request payload before running `order-send --yes`.
### Execution (live / mutating)
These commands send requests to the live trade server and can place or close
real trades. Both require `--yes` for live execution.
| Command | Description |
| ----------------- | ---------------------------------------------------------------------------------------------------- |
| `order-send` | Send a **raw** trade request directly to MT5 (`--yes` required; expert path — no extra validation) |
| `close-positions` | Close open positions by `--symbol` or `--ticket` (`--yes` required for live; `--dry-run` to preview) |
Use `order-check` (Trading State) to validate funds before running `order-send --yes`.
`close-positions` is the safer high-level alternative that builds correct close
requests automatically. `order-send` is the expert raw path — downstream
applications should prefer dedicated closing helpers or their own risk controls.
### Bulk Collection
| Command | Description |
| ----------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `collect-history` | Collect rates, history-orders, and history-deals (ticks opt-in via `--dataset ticks`) for one or more symbols into a single SQLite database (optional cash-event/position views) |
```bash
mt5cli -o history.db collect-history \
--symbol EURUSD --symbol GBPUSD \
--date-from 2024-01-01 --date-to 2024-02-01 \
--dataset rates --dataset history-deals \
--timeframe M1 --flags ALL --if-exists append --with-views
```
`collect-history` options:
| Option | Default | Description |
| -------------- | ------------------------------------ | -------------------------------------------------------------------------------------------------------------------------- |
| `--symbol/-s` | _required_ | Symbol to collect (repeat for multiple). |
| `--date-from` | _required_ | Start date in ISO 8601. |
| `--date-to` | _required_ | End date in ISO 8601. |
| `--dataset` | rates, history-orders, history-deals | Repeatable: `rates`, `ticks`, `history-orders`, `history-deals`. Ticks are opt-in: pass `--dataset ticks` to include them. |
| `--timeframe` | `M1` | Rates timeframe; recorded in a `timeframe` column on the `rates` table. |
| `--flags` | `ALL` | Tick copy flags forwarded to `copy_ticks_range`. |
| `--if-exists` | `fail` | `append`, `replace`, or `fail` when a target table already exists. |
| `--with-views` | off | Add `cash_events` and `positions_reconstructed` views (requires the `history-deals` dataset). |
History orders and deals are fetched per symbol and concatenated, so the symbol filter is applied consistently across all datasets. The `cash_events` view is derived from symbol-filtered `history_deals`, so account-level cash events with empty or non-matching symbols may be excluded. The `positions_reconstructed` view excludes positions with no closing deal, uses volume-weighted open/close prices, and reports reversal deals (`DEAL_ENTRY_INOUT`) via `volume_reversal` / `reversal_count`.
See the [History schema diagram](api/history.md#entity-relationship-diagram) for a sample ER layout of the resulting database.
## Global Options
@@ -109,7 +229,9 @@ Use `order-check` to validate a request payload before running `order-send --yes
Browse the API documentation for detailed module information:
- [CLI Module](api/cli.md) - CLI application with export commands and utility functions
- [CLI Module](api/cli.md) - CLI application with data export and execution commands
- [SDK Module](api/sdk.md) - Programmatic read-only data collection API
- [Utils Module](api/utils.md) - Constants, parameter types, parsers, and export utilities
## Development
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# Grafana Integration for mt5cli
This directory contains example configuration and dashboard files for visualising
mt5cli SQLite data in [Grafana](https://grafana.com/) using the
[Grafana SQLite datasource plugin](https://grafana.com/grafana/plugins/frser-sqlite-datasource/).
## Prerequisites
- mt5cli installed and able to connect to MetaTrader 5
- Grafana 10+ with the `frser-sqlite-datasource` plugin installed
- (Optional) Docker and Docker Compose for the containerised setup
## Generating the SQLite database
Collect historical data and snapshot current account state:
```sh
# Collect OHLCV history
mt5cli -o history.db collect-history --symbol EURUSD --date-from 2024-01-01 --date-to 2024-12-31
# Create Grafana-ready views and indexes
mt5cli -o history.db grafana-schema
# Snapshot current account, positions, and orders
mt5cli -o history.db snapshot --with-grafana-schema
```
## Publishing a Grafana-readable copy
Grafana reads the SQLite file directly. To avoid read/write conflicts, publish
a consistent copy after each update:
```sh
mt5cli -o history.db grafana-schema --publish-copy history.mt5cli.db
mt5cli -o history.db snapshot --publish-copy history.mt5cli.db
```
The `--publish-copy` option uses the SQLite online backup API, which is safe
even when the source database uses WAL journal mode.
## Configuring the datasource path
Edit `provisioning/datasources/mt5cli-sqlite.yml` and set the `path` field
to the absolute path of your published `.db` file:
```yaml
jsonData:
path: /absolute/path/to/history.mt5cli.db
```
## Running Grafana on Windows (native)
1. Download and install Grafana from <https://grafana.com/grafana/download/>.
2. Install the SQLite plugin: `grafana-cli plugins install frser-sqlite-datasource`.
3. Copy `provisioning/datasources/mt5cli-sqlite.yml` into
`%ProgramFiles%\GrafanaLabs\grafana\conf\provisioning\datasources\`.
Do not copy `provisioning/dashboards/mt5cli.yml` — it contains a
Docker-specific dashboard path that is not valid on Windows.
4. Import the dashboards from `dashboards/` via the Grafana UI
(Dashboards → Import → Upload JSON file).
## Running with Docker Compose
Set `MT5CLI_DB_PATH` to the absolute path of your published `.db` file, then
start the stack:
```sh
# From the examples/grafana directory
MT5CLI_DB_PATH=/absolute/path/to/history.mt5cli.db docker compose up -d
```
Alternatively, create a `.env` file in `examples/grafana/` containing
`MT5CLI_DB_PATH=/absolute/path/to/history.mt5cli.db` and run
`docker compose up -d`. Compose refuses to start if the variable is unset or
empty.
Then open <http://localhost:3000> (default credentials: admin / admin).
## Dashboard overview
| Dashboard | Description |
| ---------------------- | ------------------------------------------------------- |
| `mt5cli-overview.json` | Account balance, equity, margin, and snapshot freshness |
| `mt5cli-trades.json` | Trade P/L, win rate, symbol breakdown |
| `mt5cli-market.json` | OHLCV rates, spreads, and tick volume |
All panel queries use the `grafana_*` views; they do not read internal storage
tables directly.
## Importing dashboards
1. Open Grafana and navigate to **Dashboards → Import**.
2. Click **Upload JSON file** and select one of the files in `dashboards/`.
3. Select the `mt5cli-SQLite` datasource when prompted.
4. Click **Import**.
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@@ -0,0 +1,26 @@
# Docker Compose for Grafana with mt5cli SQLite datasource.
#
# MT5CLI_DB_PATH must be set to the absolute host path of your published .db
# file before running `docker compose up -d`. Compose will refuse to start if
# the variable is missing or empty.
#
# Example:
# MT5CLI_DB_PATH=/home/user/history.mt5cli.db docker compose up -d
services:
grafana:
image: grafana/grafana:latest
ports:
- "3000:3000"
environment:
GF_PATHS_PROVISIONING: /etc/grafana/provisioning
GF_INSTALL_PLUGINS: frser-sqlite-datasource
volumes:
- ./provisioning:/etc/grafana/provisioning:ro
- ./dashboards:/var/lib/grafana/dashboards:ro
- grafana-storage:/var/lib/grafana
- ${MT5CLI_DB_PATH:?Set MT5CLI_DB_PATH to the path of your published mt5cli SQLite DB}:/data/mt5cli.db:ro
user: "472"
volumes:
grafana-storage:
@@ -0,0 +1,98 @@
{
"__inputs": [
{
"name": "DS_MT5CLI_SQLITE",
"label": "mt5cli-SQLite",
"description": "",
"type": "datasource",
"pluginId": "frser-sqlite-datasource",
"pluginName": "SQLite"
}
],
"__requires": [
{
"type": "datasource",
"id": "frser-sqlite-datasource",
"name": "SQLite",
"version": "1.0.0"
}
],
"annotations": { "list": [] },
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": null,
"links": [],
"panels": [
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": { "defaults": {}, "overrides": [] },
"gridPos": { "h": 8, "w": 24, "x": 0, "y": 0 },
"id": 1,
"title": "Close Price Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"symbol\", \"close\" FROM grafana_rates WHERE \"time\" >= $__from / 1000 AND \"time\" < $__to / 1000 ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": { "defaults": {}, "overrides": [] },
"gridPos": { "h": 8, "w": 12, "x": 0, "y": 8 },
"id": 2,
"title": "Spread Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"symbol\", \"spread\" FROM grafana_rates WHERE \"time\" >= $__from / 1000 AND \"time\" < $__to / 1000 ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": { "defaults": {}, "overrides": [] },
"gridPos": { "h": 8, "w": 12, "x": 12, "y": 8 },
"id": 3,
"title": "Tick Volume Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"symbol\", \"tick_volume\" FROM grafana_rates WHERE \"time\" >= $__from / 1000 AND \"time\" < $__to / 1000 ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
}
],
"refresh": "1m",
"schemaVersion": 36,
"tags": ["mt5cli", "market"],
"templating": {
"list": [
{
"current": {},
"hide": 0,
"includeAll": false,
"label": "Data Source",
"multi": false,
"name": "DS_MT5CLI_SQLITE",
"options": [],
"query": "frser-sqlite-datasource",
"refresh": 1,
"type": "datasource"
}
]
},
"time": { "from": "now-24h", "to": "now" },
"timepicker": {},
"timezone": "browser",
"title": "MT5CLI - Market Data",
"uid": "mt5cli-market",
"version": 1
}
@@ -0,0 +1,254 @@
{
"__inputs": [
{
"name": "DS_MT5CLI_SQLITE",
"label": "mt5cli-SQLite",
"description": "",
"type": "datasource",
"pluginId": "frser-sqlite-datasource",
"pluginName": "SQLite"
}
],
"__requires": [
{
"type": "datasource",
"id": "frser-sqlite-datasource",
"name": "SQLite",
"version": "1.0.0"
}
],
"annotations": {
"list": []
},
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": null,
"links": [],
"panels": [
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {
"unit": "currencyUSD"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 0,
"y": 0
},
"id": 1,
"options": {
"reduceOptions": {
"calcs": ["lastNotNull"]
}
},
"title": "Balance",
"type": "stat",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"balance\" FROM grafana_account_snapshots ORDER BY time DESC LIMIT 1",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {
"unit": "currencyUSD"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 6,
"y": 0
},
"id": 2,
"options": {
"reduceOptions": {
"calcs": ["lastNotNull"]
}
},
"title": "Equity",
"type": "stat",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"equity\" FROM grafana_account_snapshots ORDER BY time DESC LIMIT 1",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {
"unit": "currencyUSD"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 12,
"y": 0
},
"id": 3,
"options": {
"reduceOptions": {
"calcs": ["lastNotNull"]
}
},
"title": "Free Margin",
"type": "stat",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"margin_free\" FROM grafana_account_snapshots ORDER BY time DESC LIMIT 1",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {
"unit": "percent"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 18,
"y": 0
},
"id": 4,
"options": {
"reduceOptions": {
"calcs": ["lastNotNull"]
}
},
"title": "Margin Level",
"type": "stat",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"margin_level\" FROM grafana_account_snapshots ORDER BY time DESC LIMIT 1",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {
"unit": "dateTimeFromNow"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 24,
"x": 0,
"y": 4
},
"id": 7,
"options": {
"reduceOptions": {
"calcs": ["lastNotNull"]
}
},
"title": "Last Snapshot",
"type": "stat",
"targets": [
{
"rawSql": "SELECT MAX(\"time\") * 1000 AS \"Last Snapshot\" FROM grafana_account_snapshots",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 24,
"x": 0,
"y": 8
},
"id": 5,
"title": "Account Balance Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"balance\" FROM grafana_account_snapshots ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 24,
"x": 0,
"y": 16
},
"id": 6,
"title": "Equity Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"equity\" FROM grafana_account_snapshots ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
}
],
"refresh": "1m",
"schemaVersion": 36,
"tags": ["mt5cli", "account"],
"templating": {
"list": [
{
"current": {},
"hide": 0,
"includeAll": false,
"label": "Data Source",
"multi": false,
"name": "DS_MT5CLI_SQLITE",
"options": [],
"query": "frser-sqlite-datasource",
"refresh": 1,
"type": "datasource"
}
]
},
"time": {
"from": "now-7d",
"to": "now"
},
"timepicker": {},
"timezone": "browser",
"title": "MT5CLI - Account Overview",
"uid": "mt5cli-overview",
"version": 1
}
@@ -0,0 +1,167 @@
{
"__inputs": [
{
"name": "DS_MT5CLI_SQLITE",
"label": "mt5cli-SQLite",
"description": "",
"type": "datasource",
"pluginId": "frser-sqlite-datasource",
"pluginName": "SQLite"
}
],
"__requires": [
{
"type": "datasource",
"id": "frser-sqlite-datasource",
"name": "SQLite",
"version": "1.0.0"
}
],
"annotations": {
"list": []
},
"editable": true,
"fiscalYearStartMonth": 0,
"graphTooltip": 0,
"id": null,
"links": [],
"panels": [
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 0
},
"id": 1,
"title": "Realized P/L by Symbol",
"type": "table",
"targets": [
{
"rawSql": "SELECT \"symbol\", \"cumulative_pnl\", \"deal_count\" FROM grafana_realized_pnl ORDER BY cumulative_pnl DESC",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {},
"overrides": [
{
"matcher": {
"id": "byName",
"options": "win_rate_pct"
},
"properties": [
{
"id": "unit",
"value": "percent"
},
{
"id": "displayName",
"value": "Win Rate (%)"
}
]
}
]
},
"gridPos": {
"h": 8,
"w": 12,
"x": 12,
"y": 0
},
"id": 2,
"title": "Trade Statistics by Symbol",
"type": "table",
"targets": [
{
"rawSql": "SELECT \"symbol\", \"total_deals\", \"winning_deals\", \"losing_deals\", \"total_profit\", \"avg_profit\", 100.0 * \"winning_deals\" / NULLIF(\"total_deals\", 0) AS \"win_rate_pct\" FROM grafana_trade_stats ORDER BY total_profit DESC",
"format": "table",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 24,
"x": 0,
"y": 8
},
"id": 3,
"title": "Open Position Profit Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"symbol\", SUM(\"profit\") AS profit FROM grafana_position_snapshots GROUP BY time, symbol ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
},
{
"datasource": "${DS_MT5CLI_SQLITE}",
"fieldConfig": {
"defaults": {},
"overrides": []
},
"gridPos": {
"h": 8,
"w": 24,
"x": 0,
"y": 16
},
"id": 4,
"title": "Cash Events Over Time",
"type": "timeseries",
"targets": [
{
"rawSql": "SELECT \"time\" AS time, \"profit\" FROM grafana_cash_events ORDER BY time",
"format": "time_series",
"refId": "A"
}
]
}
],
"refresh": "5m",
"schemaVersion": 36,
"tags": ["mt5cli", "trades"],
"templating": {
"list": [
{
"current": {},
"hide": 0,
"includeAll": false,
"label": "Data Source",
"multi": false,
"name": "DS_MT5CLI_SQLITE",
"options": [],
"query": "frser-sqlite-datasource",
"refresh": 1,
"type": "datasource"
}
]
},
"time": {
"from": "now-30d",
"to": "now"
},
"timepicker": {},
"timezone": "browser",
"title": "MT5CLI - Trade Analytics",
"uid": "mt5cli-trades",
"version": 1
}
@@ -0,0 +1,13 @@
# Grafana dashboard provisioning for mt5cli dashboards.
apiVersion: 1
providers:
- name: mt5cli
type: file
disableDeletion: false
updateIntervalSeconds: 30
allowUiUpdates: true
options:
path: /var/lib/grafana/dashboards
foldersFromFilesStructure: false
@@ -0,0 +1,16 @@
# Grafana datasource provisioning for mt5cli SQLite.
#
# Requires the frser-sqlite-datasource plugin:
# grafana-cli plugins install frser-sqlite-datasource
#
# Set `path` to the absolute path of your published history.mt5cli.db file.
apiVersion: 1
datasources:
- name: mt5cli-SQLite
type: frser-sqlite-datasource
access: proxy
isDefault: true
jsonData:
path: /data/mt5cli.db
+11 -1
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@@ -1,5 +1,5 @@
site_name: mt5cli API Documentation
site_description: Command-line tool for MetaTrader 5
site_description: Generic MT5 data and execution infrastructure for Python
site_author: dceoy
site_url: https://github.com/dceoy/mt5cli
@@ -24,6 +24,7 @@ theme:
features:
- content.code.annotate
- content.code.copy
- content.code.mermaid
- navigation.indexes
- navigation.sections
- navigation.tabs
@@ -55,7 +56,16 @@ nav:
- Home: index.md
- API Reference:
- Overview: api/index.md
- Public API Contract: api/public-contract.md
- Client: api/client.md
- Schemas: api/schemas.md
- Converters: api/converters.md
- Exceptions: api/exceptions.md
- CLI: api/cli.md
- SDK: api/sdk.md
- Trading: api/trading.md
- History Collection (SQLite): api/history.md
- Utils: api/utils.md
markdown_extensions:
- admonition
+141 -4
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@@ -1,12 +1,149 @@
"""mt5cli: Command-line tool for MetaTrader 5."""
"""mt5cli: Generic MT5 data and execution infrastructure for Python applications.
Downstream packages should import from this module (``from mt5cli import ...``)
rather than private submodule helpers. See ``docs/api/public-contract.md`` for
the stable SDK contract, CLI surface, internal modules, and out-of-scope
strategy responsibilities.
"""
from importlib.metadata import version
from .cli import detect_format, export_dataframe
from .client import MT5Client, build_config, mt5_session
from .contract import STABLE_SDK_EXPORTS
from .exceptions import (
Mt5CliError,
Mt5ConnectionError,
Mt5OperationError,
Mt5SchemaError,
)
from .history import (
RateTarget,
build_rate_targets,
drop_forming_rate_bar,
load_rate_series_by_granularity,
load_rate_series_from_sqlite,
)
from .sdk import (
AccountSpec,
ThrottledHistoryUpdater,
collect_history,
collect_latest_closed_rates_by_granularity,
collect_latest_closed_rates_for_accounts,
collect_latest_rates_for_accounts_with_retries,
fetch_latest_closed_rates,
resolve_account_spec,
resolve_account_specs,
update_history,
update_history_with_config,
update_observability,
update_observability_with_config,
)
from .trading import (
ExecutionStatus,
MarginVolume,
OrderExecutionResult,
OrderFillingMode,
OrderLimits,
OrderSide,
OrderTimeMode,
PositionSide,
ProjectionMode,
calculate_account_projected_margin_ratio,
calculate_margin_and_volume,
calculate_new_position_margin_ratio,
calculate_positions_margin,
calculate_positions_margin_by_symbol,
calculate_positions_margin_safe,
calculate_projected_margin_ratio,
calculate_spread_ratio,
calculate_symbol_group_margin_ratio,
calculate_trailing_stop_updates,
calculate_volume_by_margin,
close_open_positions,
create_trading_client,
detect_position_side,
determine_order_limits,
ensure_symbol_selected,
estimate_order_margin,
extract_tick_price,
fetch_latest_closed_rates_for_trading_client,
fetch_latest_closed_rates_indexed,
get_account_snapshot,
get_positions_frame,
get_symbol_snapshot,
get_tick_snapshot,
mt5_trading_session,
normalize_order_volume,
place_market_order,
update_sltp_for_open_positions,
update_trailing_stop_loss_for_open_positions,
)
__version__ = version(__package__) if __package__ else None
__all__ = [
"detect_format",
"export_dataframe",
"STABLE_SDK_EXPORTS",
"AccountSpec",
"ExecutionStatus",
"MT5Client",
"MarginVolume",
"Mt5CliError",
"Mt5ConnectionError",
"Mt5OperationError",
"Mt5SchemaError",
"OrderExecutionResult",
"OrderFillingMode",
"OrderLimits",
"OrderSide",
"OrderTimeMode",
"PositionSide",
"ProjectionMode",
"RateTarget",
"ThrottledHistoryUpdater",
"build_config",
"build_rate_targets",
"calculate_account_projected_margin_ratio",
"calculate_margin_and_volume",
"calculate_new_position_margin_ratio",
"calculate_positions_margin",
"calculate_positions_margin_by_symbol",
"calculate_positions_margin_safe",
"calculate_projected_margin_ratio",
"calculate_spread_ratio",
"calculate_symbol_group_margin_ratio",
"calculate_trailing_stop_updates",
"calculate_volume_by_margin",
"close_open_positions",
"collect_history",
"collect_latest_closed_rates_by_granularity",
"collect_latest_closed_rates_for_accounts",
"collect_latest_rates_for_accounts_with_retries",
"create_trading_client",
"detect_position_side",
"determine_order_limits",
"drop_forming_rate_bar",
"ensure_symbol_selected",
"estimate_order_margin",
"extract_tick_price",
"fetch_latest_closed_rates",
"fetch_latest_closed_rates_for_trading_client",
"fetch_latest_closed_rates_indexed",
"get_account_snapshot",
"get_positions_frame",
"get_symbol_snapshot",
"get_tick_snapshot",
"load_rate_series_by_granularity",
"load_rate_series_from_sqlite",
"mt5_session",
"mt5_trading_session",
"normalize_order_volume",
"place_market_order",
"resolve_account_spec",
"resolve_account_specs",
"update_history",
"update_history_with_config",
"update_observability",
"update_observability_with_config",
"update_sltp_for_open_positions",
"update_trailing_stop_loss_for_open_positions",
]
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@@ -0,0 +1,86 @@
"""Stable public client abstraction for MT5 data and execution operations."""
from __future__ import annotations
from contextlib import contextmanager
from typing import TYPE_CHECKING, Any, Self
from .sdk import Mt5CliClient, build_config, connected_client
if TYPE_CHECKING:
from collections.abc import Iterator
import pandas as pd
from pdmt5 import Mt5Config, Mt5DataClient
__all__ = [
"MT5Client",
"build_config",
"mt5_session",
]
class MT5Client(Mt5CliClient):
"""Public client for generic MT5 data access and order primitives.
Extends the read-only SDK client with optional order check/send helpers and
exposes the same connection lifecycle as :func:`mt5_session`.
mt5cli intentionally exposes minimal execution primitives only. Trading
decisions, signals, strategies, backtests, and optimization remain the
responsibility of downstream applications.
"""
def order_check(self, request: dict[str, Any]) -> pd.DataFrame:
"""Check funds sufficiency for a trade request.
Args:
request: MT5 order request dictionary.
Returns:
One-row DataFrame with the order-check result.
"""
return self._fetch(lambda client: client.order_check_as_df(request=request))
def order_send(self, request: dict[str, Any]) -> pd.DataFrame:
"""Send a live trade request to the MT5 trade server.
Warning:
This is a live execution primitive. A successful call can place,
modify, or close real trades on the connected account. Downstream
applications must gate usage explicitly (for example behind manual
confirmation or application-specific risk controls). mt5cli does
not implement strategy logic, signal generation, or trade sizing.
Args:
request: MT5 order request dictionary.
Returns:
One-row DataFrame with the order-send result.
"""
return self._fetch(lambda client: client.order_send_as_df(request=request))
@classmethod
def from_connected_client(cls, client: Mt5DataClient) -> Self:
"""Bind to an already-connected ``Mt5DataClient`` without owning it.
Returns:
Client wrapper bound to the injected connection.
"""
return cls(client=client)
@contextmanager
def mt5_session(config: Mt5Config | None = None) -> Iterator[MT5Client]:
"""Open an MT5 terminal session and yield a connected :class:`MT5Client`.
Args:
config: MT5 connection configuration. Defaults to an empty config that
attaches to a running terminal.
Yields:
Connected :class:`MT5Client` bound to the session.
"""
mt5_config = config or build_config()
with connected_client(mt5_config) as client:
yield MT5Client.from_connected_client(client)
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"""Downstream SDK export tier for mt5cli."""
from __future__ import annotations
STABLE_SDK_EXPORTS: frozenset[str] = frozenset({
"AccountSpec",
"MT5Client",
"Mt5CliError",
"Mt5ConnectionError",
"Mt5OperationError",
"Mt5SchemaError",
"OrderFillingMode",
"OrderSide",
"OrderTimeMode",
"PositionSide",
"ProjectionMode",
"ExecutionStatus",
"MarginVolume",
"OrderExecutionResult",
"OrderLimits",
"RateTarget",
"ThrottledHistoryUpdater",
"build_config",
"build_rate_targets",
"calculate_account_projected_margin_ratio",
"calculate_margin_and_volume",
"calculate_new_position_margin_ratio",
"calculate_projected_margin_ratio",
"calculate_positions_margin",
"calculate_positions_margin_by_symbol",
"calculate_positions_margin_safe",
"calculate_spread_ratio",
"calculate_symbol_group_margin_ratio",
"calculate_trailing_stop_updates",
"calculate_volume_by_margin",
"close_open_positions",
"collect_history",
"collect_latest_closed_rates_by_granularity",
"collect_latest_closed_rates_for_accounts",
"collect_latest_rates_for_accounts_with_retries",
"create_trading_client",
"detect_position_side",
"determine_order_limits",
"drop_forming_rate_bar",
"ensure_symbol_selected",
"estimate_order_margin",
"extract_tick_price",
"fetch_latest_closed_rates",
"fetch_latest_closed_rates_for_trading_client",
"fetch_latest_closed_rates_indexed",
"get_account_snapshot",
"get_positions_frame",
"get_symbol_snapshot",
"get_tick_snapshot",
"load_rate_series_by_granularity",
"load_rate_series_from_sqlite",
"mt5_session",
"mt5_trading_session",
"normalize_order_volume",
"place_market_order",
"resolve_account_spec",
"resolve_account_specs",
"update_history",
"update_history_with_config",
"update_observability",
"update_observability_with_config",
"update_sltp_for_open_positions",
"update_trailing_stop_loss_for_open_positions",
})
__all__ = ["STABLE_SDK_EXPORTS"]
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"""Shared conversion helpers for MT5 symbols, timeframes, and date ranges."""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
from typing import TYPE_CHECKING
from pdmt5 import get_timeframe_name as _get_timeframe_name
from .utils import parse_datetime, parse_tick_flags, parse_timeframe
if TYPE_CHECKING:
from collections.abc import Sequence
__all__ = [
"ensure_utc",
"granularity_name",
"normalize_symbol",
"normalize_symbols",
"parse_date_range",
"parse_datetime",
"parse_tick_flags",
"parse_timeframe",
"recent_window",
]
def normalize_symbol(symbol: str) -> str:
"""Normalize a broker symbol name for MT5 API calls.
Strips surrounding whitespace while preserving broker-specific casing and
suffixes (for example ``XAUUSDm``, ``US500.cash``, or ``EURUSD.r``).
Args:
symbol: Raw symbol name.
Returns:
Normalized symbol string.
Raises:
ValueError: If the symbol is empty after normalization.
"""
normalized = symbol.strip()
if not normalized:
msg = "Symbol must not be empty."
raise ValueError(msg)
return normalized
def normalize_symbols(symbols: Sequence[str]) -> list[str]:
"""Normalize a sequence of broker symbol names.
Args:
symbols: Raw symbol names.
Returns:
List of normalized, de-duplicated symbols preserving first-seen order.
"""
seen: set[str] = set()
resolved: list[str] = []
for symbol in symbols:
normalized = normalize_symbol(symbol)
if normalized not in seen:
seen.add(normalized)
resolved.append(normalized)
return resolved
def ensure_utc(value: datetime | str) -> datetime:
"""Return a timezone-aware UTC datetime.
Args:
value: Datetime instance or ISO 8601 string.
Returns:
UTC-aware datetime.
"""
if isinstance(value, str):
return parse_datetime(value)
if value.tzinfo is None:
return value.replace(tzinfo=UTC)
return value.astimezone(UTC)
def parse_date_range(
date_from: datetime | str,
date_to: datetime | str,
) -> tuple[datetime, datetime]:
"""Parse and validate an inclusive UTC date range.
Args:
date_from: Range start as datetime or ISO 8601 string.
date_to: Range end as datetime or ISO 8601 string.
Returns:
Tuple of UTC-aware ``(start, end)`` datetimes.
Raises:
ValueError: If ``date_from`` is after ``date_to``.
"""
start = ensure_utc(date_from)
end = ensure_utc(date_to)
if start > end:
msg = (
f"date_from ({start.isoformat()}) must not be after "
f"date_to ({end.isoformat()})."
)
raise ValueError(msg)
return start, end
def recent_window(
*,
hours: float | None = None,
seconds: float | None = None,
date_to: datetime | str | None = None,
) -> tuple[datetime, datetime]:
"""Build a trailing UTC window ending at ``date_to`` or now.
Exactly one of ``hours`` or ``seconds`` must be provided.
Args:
hours: Trailing window length in hours.
seconds: Trailing window length in seconds.
date_to: Window end. Defaults to current UTC time.
Returns:
Tuple of UTC-aware ``(start, end)`` datetimes.
Raises:
ValueError: If neither or both window lengths are provided, or if a
length is not positive.
"""
if (hours is None) == (seconds is None):
msg = "Provide exactly one of hours or seconds."
raise ValueError(msg)
if hours is not None:
length = timedelta(hours=hours)
else:
length = timedelta(seconds=seconds if seconds is not None else 0)
if length.total_seconds() <= 0:
msg = "Window length must be positive."
raise ValueError(msg)
end = ensure_utc(date_to) if date_to is not None else datetime.now(UTC)
return end - length, end
def granularity_name(timeframe: int | str) -> str:
"""Return a short granularity label for a timeframe integer or name.
Args:
timeframe: MT5 timeframe as integer or name (for example ``M1``).
Returns:
Short name such as ``M1`` or the stringified integer when unknown.
"""
tf = parse_timeframe(timeframe)
try:
name = _get_timeframe_name(tf)
except ValueError:
return str(tf)
return name.removeprefix("TIMEFRAME_")
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"""Normalized exception types for MT5 and mt5cli operations."""
from __future__ import annotations
from typing import TYPE_CHECKING, TypeVar
from pdmt5 import Mt5RuntimeError
if TYPE_CHECKING:
from collections.abc import Callable
try:
from pdmt5 import Mt5TradingError
except ImportError: # pragma: no cover
Mt5TradingError = None # type: ignore[assignment]
T = TypeVar("T")
__all__ = [
"Mt5CliError",
"Mt5ConnectionError",
"Mt5OperationError",
"Mt5SchemaError",
"call_with_normalized_errors",
"is_recoverable_mt5_error",
"normalize_mt5_exception",
]
_RECOVERABLE_MT5_ERRORS: tuple[type[BaseException], ...] = (
*([Mt5TradingError] if Mt5TradingError is not None else []), # type: ignore[misc]
Mt5RuntimeError,
)
class Mt5CliError(Exception):
"""Base exception for mt5cli public API errors."""
class Mt5ConnectionError(Mt5CliError):
"""Raised when MT5 initialization, login, or shutdown fails."""
class Mt5OperationError(Mt5CliError):
"""Raised when an MT5 data or trading operation fails."""
class Mt5SchemaError(Mt5CliError):
"""Raised when a DataFrame does not match an expected dataset schema."""
def is_recoverable_mt5_error(exc: BaseException) -> bool:
"""Return whether an exception is a transient MT5 failure worth retrying.
Args:
exc: Exception raised by MT5 or pdmt5.
Returns:
True for ``Mt5RuntimeError`` and ``Mt5TradingError`` (if available).
"""
return isinstance(exc, _RECOVERABLE_MT5_ERRORS)
def normalize_mt5_exception(exc: BaseException) -> Mt5CliError:
"""Map pdmt5/MT5 exceptions to stable mt5cli exception types.
Args:
exc: Original exception from MT5 or pdmt5.
Returns:
``Mt5ConnectionError`` for runtime failures, ``Mt5OperationError`` for
trading failures, or the original exception when it is not recognized.
"""
if Mt5TradingError is not None and isinstance(exc, Mt5TradingError):
return Mt5OperationError(str(exc))
if isinstance(exc, Mt5RuntimeError):
return Mt5ConnectionError(str(exc))
if isinstance(exc, Mt5CliError):
return exc
return Mt5CliError(str(exc))
def call_with_normalized_errors(fn: Callable[[], T]) -> T:
"""Run ``fn`` and map recoverable MT5 errors to mt5cli types.
Args:
fn: Callable performing MT5 work.
Returns:
Value returned by ``fn``.
"""
try:
return fn()
except _RECOVERABLE_MT5_ERRORS as exc:
normalized = normalize_mt5_exception(exc)
raise normalized from exc
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"""Grafana-oriented SQLite views, indexes, and snapshot tables."""
from __future__ import annotations
import contextlib
import datetime
import logging
import os
import sqlite3
import tempfile
from pathlib import Path
from typing import cast
from .history import get_table_columns
logger = logging.getLogger(__name__)
_TRADE_DEAL_TYPES_SQL = "(0, 1)"
_GRAFANA_VIEW_NAMES = (
"grafana_rates",
"grafana_ticks",
"grafana_history_deals",
"grafana_history_orders",
"grafana_trade_deals",
"grafana_cash_events",
"grafana_realized_pnl",
"grafana_symbol_pnl",
"grafana_trade_stats",
"grafana_account_snapshots",
"grafana_position_snapshots",
"grafana_order_snapshots",
"grafana_terminal_snapshots",
)
def _to_epoch_int(value: object) -> int | None:
if value is None:
return None
if isinstance(value, datetime.datetime):
return int(value.timestamp())
if isinstance(value, (int, float)):
return int(value)
return None
def _time_col_expr(col: str) -> str:
return (
f"CASE WHEN typeof(\"{col}\") IN ('integer', 'real')"
f' THEN CAST("{col}" AS INTEGER)'
f" ELSE CAST(strftime('%s', \"{col}\") AS INTEGER) END"
)
def _create_view_safe(
conn: sqlite3.Connection,
name: str,
select_sql: str,
) -> None:
try:
conn.execute(f'DROP VIEW IF EXISTS "{name}"')
conn.execute(f'CREATE VIEW "{name}" AS {select_sql}')
except sqlite3.Error as exc:
logger.warning("Skipping view %s: %s", name, exc)
def _other_cols(all_cols: set[str], exclude: set[str]) -> list[str]:
return sorted(all_cols - exclude)
# ---------------------------------------------------------------------------
# Snapshot table DDL
# ---------------------------------------------------------------------------
_SNAPSHOT_TABLE_DDLS: list[str] = [
"""CREATE TABLE IF NOT EXISTS snapshot_runs (
run_id INTEGER PRIMARY KEY,
observed_at INTEGER NOT NULL,
status TEXT NOT NULL,
detail TEXT
)""",
"""CREATE TABLE IF NOT EXISTS account_snapshots (
run_id INTEGER NOT NULL,
login INTEGER,
currency TEXT,
balance REAL,
equity REAL,
margin REAL,
margin_free REAL,
margin_level REAL,
profit REAL,
leverage INTEGER
)""",
"""CREATE TABLE IF NOT EXISTS position_snapshots (
run_id INTEGER NOT NULL,
login INTEGER,
ticket INTEGER,
position_id INTEGER,
symbol TEXT,
type INTEGER,
volume REAL,
price_open REAL,
price_current REAL,
profit REAL,
swap REAL,
comment TEXT,
magic INTEGER
)""",
"""CREATE TABLE IF NOT EXISTS order_snapshots (
run_id INTEGER NOT NULL,
login INTEGER,
ticket INTEGER,
symbol TEXT,
type INTEGER,
volume_current REAL,
price_open REAL,
price_current REAL,
state INTEGER,
comment TEXT,
magic INTEGER,
time_setup INTEGER
)""",
"""CREATE TABLE IF NOT EXISTS terminal_snapshots (
run_id INTEGER NOT NULL,
name TEXT,
connected INTEGER,
community_account INTEGER,
trade_allowed INTEGER,
trade_expert INTEGER,
path TEXT,
company TEXT,
language TEXT
)""",
]
def create_snapshot_tables(conn: sqlite3.Connection) -> None:
"""Create snapshot tables idempotently."""
for ddl in _SNAPSHOT_TABLE_DDLS:
conn.execute(ddl)
def start_snapshot_run(conn: sqlite3.Connection, observed_at: int) -> int:
"""Insert a snapshot_runs row with status 'running' and return its run_id.
Returns:
The auto-assigned run_id for the new row.
"""
cursor = conn.execute(
"INSERT INTO snapshot_runs (observed_at, status) VALUES (?, 'running')",
(observed_at,),
)
return cast("int", cursor.lastrowid)
# ---------------------------------------------------------------------------
# View builders
# ---------------------------------------------------------------------------
def _build_grafana_rates(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "rates")
required = {"time", "symbol", "timeframe"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_rates: rates table missing columns %s",
sorted(required - cols),
)
return
time_expr = _time_col_expr("time")
others = _other_cols(cols, {"time"})
other_sql = ", ".join(f'"{c}"' for c in others)
_create_view_safe(
conn,
"grafana_rates",
f'SELECT {time_expr} AS "time", {other_sql} FROM "rates"', # noqa: S608
)
def _build_grafana_ticks(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "ticks")
required = {"time", "symbol"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_ticks: ticks table missing columns %s",
sorted(required - cols),
)
return
time_expr = _time_col_expr("time")
others = _other_cols(cols, {"time"})
other_sql = ", ".join(f'"{c}"' for c in others)
_create_view_safe(
conn,
"grafana_ticks",
f'SELECT {time_expr} AS "time", {other_sql} FROM "ticks"', # noqa: S608
)
def _build_grafana_history_deals(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_deals")
if "time" not in cols:
logger.warning("Skipping grafana_history_deals: history_deals.time is missing")
return
time_expr = _time_col_expr("time")
others = _other_cols(cols, {"time"})
other_sql = ", ".join(f'"{c}"' for c in others)
_create_view_safe(
conn,
"grafana_history_deals",
f'SELECT {time_expr} AS "time", {other_sql} FROM "history_deals"', # noqa: S608
)
def _build_grafana_history_orders(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_orders")
if "time_setup" not in cols:
logger.warning(
"Skipping grafana_history_orders: history_orders.time_setup is missing"
)
return
time_expr = _time_col_expr("time_setup")
others = _other_cols(cols, set())
other_sql = ", ".join(f'"{c}"' for c in others)
_create_view_safe(
conn,
"grafana_history_orders",
f'SELECT {time_expr} AS "time", {other_sql} FROM "history_orders"', # noqa: S608
)
def _build_grafana_trade_deals(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_deals")
required = {"time", "type"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_trade_deals: history_deals missing columns %s",
sorted(required - cols),
)
return
time_expr = _time_col_expr("time")
others = _other_cols(cols, {"time"})
other_sql = ", ".join(f'"{c}"' for c in others)
_create_view_safe(
conn,
"grafana_trade_deals",
f'SELECT {time_expr} AS "time", {other_sql}' # noqa: S608
f' FROM "history_deals" WHERE "type" IN {_TRADE_DEAL_TYPES_SQL}',
)
def _build_grafana_cash_events(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_deals")
required = {"time", "type"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_cash_events: history_deals missing columns %s",
sorted(required - cols),
)
return
time_expr = _time_col_expr("time")
others = _other_cols(cols, {"time"})
other_sql = ", ".join(f'"{c}"' for c in others)
_create_view_safe(
conn,
"grafana_cash_events",
f'SELECT {time_expr} AS "time", {other_sql}' # noqa: S608
f' FROM "history_deals" WHERE "type" NOT IN {_TRADE_DEAL_TYPES_SQL}',
)
def _build_grafana_realized_pnl(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_deals")
required = {"symbol", "profit", "type", "entry"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_realized_pnl: history_deals missing columns %s",
sorted(required - cols),
)
return
_create_view_safe(
conn,
"grafana_realized_pnl",
'SELECT "symbol",' # noqa: S608
' SUM("profit") AS cumulative_pnl, COUNT(*) AS deal_count'
' FROM "history_deals"'
f' WHERE "type" IN {_TRADE_DEAL_TYPES_SQL}'
' AND "entry" IN (1, 2, 3)'
' AND "symbol" IS NOT NULL AND "symbol" != \'\''
' GROUP BY "symbol"',
)
def _build_grafana_symbol_pnl(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_deals")
required = {"time", "symbol", "profit", "type", "entry"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_symbol_pnl: history_deals missing columns %s",
sorted(required - cols),
)
return
time_expr = _time_col_expr("time")
select_parts = [f'{time_expr} AS "time"', '"symbol"', '"profit"']
if "volume" in cols:
select_parts.append('"volume"')
if "price" in cols:
select_parts.append('"price"')
select_sql = ", ".join(select_parts)
_create_view_safe(
conn,
"grafana_symbol_pnl",
f'SELECT {select_sql} FROM "history_deals"' # noqa: S608
f' WHERE "type" IN {_TRADE_DEAL_TYPES_SQL}'
' AND "entry" IN (1, 2, 3)'
' AND "symbol" IS NOT NULL AND "symbol" != \'\'',
)
def _build_grafana_trade_stats(conn: sqlite3.Connection) -> None:
cols = get_table_columns(conn, "history_deals")
required = {"symbol", "profit", "type"}
if not required.issubset(cols):
logger.warning(
"Skipping grafana_trade_stats: history_deals missing columns %s",
sorted(required - cols),
)
return
has_entry = "entry" in cols
entry_filter = ' AND "entry" IN (1, 2, 3)' if has_entry else ""
_create_view_safe(
conn,
"grafana_trade_stats",
'SELECT "symbol",' # noqa: S608
" COUNT(*) AS total_deals,"
' SUM(CASE WHEN "profit" > 0 THEN 1 ELSE 0 END) AS winning_deals,'
' SUM(CASE WHEN "profit" <= 0 THEN 1 ELSE 0 END) AS losing_deals,'
' SUM("profit") AS total_profit,'
' AVG("profit") AS avg_profit,'
' MAX("profit") AS max_profit,'
' MIN("profit") AS min_profit'
' FROM "history_deals"'
f' WHERE "type" IN {_TRADE_DEAL_TYPES_SQL}'
f"{entry_filter}"
' AND "symbol" IS NOT NULL AND "symbol" != \'\''
' GROUP BY "symbol"',
)
def _build_snapshot_view(
conn: sqlite3.Connection,
view_name: str,
table_name: str,
) -> None:
cols = get_table_columns(conn, table_name)
if not cols:
logger.warning("Skipping %s: %s table missing", view_name, table_name)
return
if "run_id" not in cols:
logger.warning("Skipping %s: %s missing run_id column", view_name, table_name)
return
others = _other_cols(cols, {"run_id"})
run_cols = get_table_columns(conn, "snapshot_runs")
if {"run_id", "observed_at", "status"}.issubset(run_cols):
other_sql = (", " + ", ".join(f's."{c}"' for c in others)) if others else ""
select_cols = f'r."observed_at" AS "time", s."run_id"{other_sql}'
_create_view_safe(
conn,
view_name,
f'SELECT {select_cols} FROM "{table_name}" s' # noqa: S608
f' JOIN "snapshot_runs" r ON s."run_id" = r."run_id"'
f" WHERE r.\"status\" = 'ok'",
)
else:
logger.warning("Skipping %s: snapshot_runs missing required columns", view_name)
def _build_grafana_account_snapshots(conn: sqlite3.Connection) -> None:
_build_snapshot_view(conn, "grafana_account_snapshots", "account_snapshots")
def _build_grafana_position_snapshots(conn: sqlite3.Connection) -> None:
_build_snapshot_view(conn, "grafana_position_snapshots", "position_snapshots")
def _build_grafana_order_snapshots(conn: sqlite3.Connection) -> None:
_build_snapshot_view(conn, "grafana_order_snapshots", "order_snapshots")
def _build_grafana_terminal_snapshots(conn: sqlite3.Connection) -> None:
_build_snapshot_view(conn, "grafana_terminal_snapshots", "terminal_snapshots")
# ---------------------------------------------------------------------------
# Public API
# ---------------------------------------------------------------------------
def create_grafana_views(conn: sqlite3.Connection) -> None:
"""Create all Grafana-facing views idempotently.
Missing source tables cause the affected view to be skipped with a warning;
other views are unaffected. Stale views whose source table or required
columns have disappeared are dropped before rebuild.
"""
for name in _GRAFANA_VIEW_NAMES:
conn.execute(f'DROP VIEW IF EXISTS "{name}"')
_build_grafana_rates(conn)
_build_grafana_ticks(conn)
_build_grafana_history_deals(conn)
_build_grafana_history_orders(conn)
_build_grafana_trade_deals(conn)
_build_grafana_cash_events(conn)
_build_grafana_realized_pnl(conn)
_build_grafana_symbol_pnl(conn)
_build_grafana_trade_stats(conn)
_build_grafana_account_snapshots(conn)
_build_grafana_position_snapshots(conn)
_build_grafana_order_snapshots(conn)
_build_grafana_terminal_snapshots(conn)
def create_grafana_indexes(conn: sqlite3.Connection) -> None:
"""Create Grafana query performance indexes idempotently."""
rates_cols = get_table_columns(conn, "rates")
if {"time", "symbol", "timeframe"}.issubset(rates_cols):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_rates_time_symbol_timeframe"
' ON "rates"("time", "symbol", "timeframe")',
)
ticks_cols = get_table_columns(conn, "ticks")
if {"time", "symbol"}.issubset(ticks_cols):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_ticks_time_symbol"
' ON "ticks"("time", "symbol")',
)
deals_cols = get_table_columns(conn, "history_deals")
if {"time", "symbol"}.issubset(deals_cols):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_history_deals_time_symbol"
' ON "history_deals"("time", "symbol")',
)
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_history_deals_symbol_time"
' ON "history_deals"("symbol", "time")',
)
orders_cols = get_table_columns(conn, "history_orders")
if {"time_setup", "symbol"}.issubset(orders_cols):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_history_orders_time_setup_symbol"
' ON "history_orders"("time_setup", "symbol")',
)
if {"run_id", "login"}.issubset(get_table_columns(conn, "account_snapshots")):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_account_snapshots_time_login"
' ON "account_snapshots"("run_id", "login")',
)
if {"run_id", "symbol"}.issubset(get_table_columns(conn, "position_snapshots")):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_position_snapshots_time_symbol"
' ON "position_snapshots"("run_id", "symbol")',
)
if {"run_id", "symbol"}.issubset(get_table_columns(conn, "order_snapshots")):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_order_snapshots_time_symbol"
' ON "order_snapshots"("run_id", "symbol")',
)
if {"observed_at", "status"}.issubset(get_table_columns(conn, "snapshot_runs")):
conn.execute(
"CREATE INDEX IF NOT EXISTS idx_snapshot_runs_time_status"
' ON "snapshot_runs"("observed_at", "status")',
)
def ensure_grafana_schema(conn: sqlite3.Connection) -> None:
"""Create snapshot tables, Grafana views, and indexes idempotently."""
create_snapshot_tables(conn)
create_grafana_views(conn)
create_grafana_indexes(conn)
def publish_grafana_copy(
source: str | Path,
target: str | Path,
) -> Path:
"""Publish a consistent SQLite copy for Grafana using the backup API.
Uses the SQLite online backup API for a WAL-safe, consistent snapshot of
the source database. Writes to a temporary file beside the target, then
atomically replaces it so that a previous published copy is preserved if
publishing fails.
Args:
source: Path to the source SQLite database.
target: Destination path for the published copy.
Returns:
The resolved absolute target path.
Raises:
FileNotFoundError: If the source database does not exist.
ValueError: If source and target resolve to the same path.
"""
source_path = Path(source)
target_path = Path(target)
if source_path.resolve() == target_path.resolve():
msg = "--publish-copy target must differ from the source database: " + str(
source_path
)
raise ValueError(msg)
if not source_path.exists():
raise FileNotFoundError(source_path)
target_path.parent.mkdir(parents=True, exist_ok=True)
tmp_fd, tmp_str = tempfile.mkstemp(
dir=target_path.parent,
suffix=".tmp",
prefix=target_path.name + ".",
)
tmp_path = Path(tmp_str)
try:
os.close(tmp_fd)
with (
contextlib.closing(sqlite3.connect(source_path)) as src,
contextlib.closing(sqlite3.connect(tmp_path)) as dst,
):
src.backup(dst)
try:
target_mode = target_path.stat().st_mode & 0o777
except FileNotFoundError:
target_mode = 0o644
Path(tmp_path).chmod(target_mode)
tmp_path.replace(target_path)
except Exception:
with contextlib.suppress(OSError):
tmp_path.unlink()
raise
logger.info("Published Grafana copy: %s -> %s", source_path, target_path)
return target_path.resolve()
# ---------------------------------------------------------------------------
# Snapshot insert helpers
# ---------------------------------------------------------------------------
def insert_account_snapshot(
conn: sqlite3.Connection,
run_id: int,
row: dict[str, object],
) -> None:
"""Append one account state row to account_snapshots."""
conn.execute(
"INSERT INTO account_snapshots"
" (run_id, login, currency, balance, equity,"
" margin, margin_free, margin_level, profit, leverage)"
" VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
(
run_id,
row.get("login"),
row.get("currency"),
row.get("balance"),
row.get("equity"),
row.get("margin"),
row.get("margin_free"),
row.get("margin_level"),
row.get("profit"),
row.get("leverage"),
),
)
def insert_position_snapshots(
conn: sqlite3.Connection,
run_id: int,
login: int | None,
rows: list[dict[str, object]],
) -> None:
"""Append position rows to position_snapshots; no-op when rows is empty."""
if not rows:
return
conn.executemany(
"INSERT INTO position_snapshots"
" (run_id, login, ticket, position_id, symbol, type, volume,"
" price_open, price_current, profit, swap, comment, magic)"
" VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
[
(
run_id,
login,
r.get("ticket"),
r.get("position_id"),
r.get("symbol"),
r.get("type"),
r.get("volume"),
r.get("price_open"),
r.get("price_current"),
r.get("profit"),
r.get("swap"),
r.get("comment"),
r.get("magic"),
)
for r in rows
],
)
def insert_order_snapshots(
conn: sqlite3.Connection,
run_id: int,
login: int | None,
rows: list[dict[str, object]],
) -> None:
"""Append order rows to order_snapshots; no-op when rows is empty."""
if not rows:
return
conn.executemany(
"INSERT INTO order_snapshots"
" (run_id, login, ticket, symbol, type, volume_current,"
" price_open, price_current, state, comment, magic, time_setup)"
" VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
[
(
run_id,
login,
r.get("ticket"),
r.get("symbol"),
r.get("type"),
r.get("volume_current"),
r.get("price_open"),
r.get("price_current"),
r.get("state"),
r.get("comment"),
r.get("magic"),
_to_epoch_int(r.get("time_setup")),
)
for r in rows
],
)
def insert_terminal_snapshot(
conn: sqlite3.Connection,
run_id: int,
row: dict[str, object],
) -> None:
"""Append one terminal state row to terminal_snapshots."""
conn.execute(
"INSERT INTO terminal_snapshots"
" (run_id, name, connected, community_account,"
" trade_allowed, trade_expert, path, company, language)"
" VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)",
(
run_id,
row.get("name"),
row.get("connected"),
row.get("community_account"),
row.get("trade_allowed"),
row.get("trade_expert"),
row.get("path"),
row.get("company"),
row.get("language"),
),
)
def record_snapshot_run(
conn: sqlite3.Connection,
run_id: int,
status: str,
detail: str | None = None,
) -> None:
"""Finalize a snapshot run by setting its status."""
conn.execute(
"UPDATE snapshot_runs SET status = ?, detail = ? WHERE run_id = ?",
(status, detail, run_id),
)
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"""Retry and reconnect helpers for transient MT5 failures."""
from __future__ import annotations
import logging
import time
from typing import TYPE_CHECKING, TypeVar
from .exceptions import is_recoverable_mt5_error
if TYPE_CHECKING:
from collections.abc import Callable
T = TypeVar("T")
logger = logging.getLogger(__name__)
__all__ = [
"retry_with_backoff",
]
def retry_with_backoff(
fn: Callable[[], T],
*,
retry_count: int = 0,
backoff_base: float = 2.0,
operation: str = "MT5 operation",
) -> T:
"""Call ``fn`` with bounded exponential backoff on recoverable MT5 errors.
Only ``pdmt5.Mt5RuntimeError`` and ``pdmt5.Mt5TradingError`` are retried.
Other exceptions propagate immediately. The final failure is re-raised once
retries are exhausted.
Args:
fn: Callable performing MT5 work.
retry_count: Maximum number of retries after the first attempt. ``0``
disables retries.
backoff_base: Base for exponential backoff. The delay before retry
attempt ``n`` (1-indexed) is ``backoff_base ** n`` seconds.
operation: Label used in warning logs.
Returns:
Value returned by ``fn`` on success.
"""
attempts = max(retry_count, 0) + 1
for attempt in range(attempts - 1):
try:
return fn()
except Exception as exc:
if not is_recoverable_mt5_error(exc):
raise
delay = backoff_base ** (attempt + 1)
logger.warning(
"%s failed (attempt %d/%d): %s; retrying in %.1fs",
operation,
attempt + 1,
attempts,
exc,
delay,
)
time.sleep(delay)
return fn()
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"""Canonical DataFrame schemas for MT5 market and account datasets."""
from __future__ import annotations
from enum import StrEnum
from typing import TYPE_CHECKING, Final
import pandas as pd
from .converters import normalize_symbol, parse_timeframe
from .exceptions import Mt5SchemaError
if TYPE_CHECKING:
from collections.abc import Iterable
__all__ = [
"DEDUP_KEYS",
"KNOWN_MT5_TIME_COLUMNS",
"REQUIRED_COLUMNS",
"TIME_COLUMNS",
"DataKind",
"normalize_dataframe",
"normalize_time_columns",
"schema_columns",
"validate_schema",
]
KNOWN_MT5_TIME_COLUMNS: Final[frozenset[str]] = frozenset({
"time",
"time_setup",
"time_setup_msc",
"time_done",
"time_done_msc",
"time_msc",
})
_TIME_COLUMN_NAMES = KNOWN_MT5_TIME_COLUMNS
class DataKind(StrEnum):
"""Supported MT5 dataset kinds with canonical column contracts."""
rates = "rates"
ticks = "ticks"
orders = "orders"
positions = "positions"
history_orders = "history_orders"
history_deals = "history_deals"
REQUIRED_COLUMNS: dict[DataKind, frozenset[str]] = {
DataKind.rates: frozenset({
"time",
"open",
"high",
"low",
"close",
"tick_volume",
"spread",
"real_volume",
}),
DataKind.ticks: frozenset({
"time",
"bid",
"ask",
"last",
"volume",
"time_msc",
"flags",
"volume_real",
}),
DataKind.orders: frozenset({
"ticket",
"time_setup",
"type",
"state",
"symbol",
"volume_current",
"price_open",
}),
DataKind.positions: frozenset({
"ticket",
"time",
"type",
"symbol",
"volume",
"price_open",
"price_current",
"profit",
}),
DataKind.history_orders: frozenset({
"ticket",
"time_setup",
"type",
"state",
"symbol",
"volume_initial",
"price_open",
}),
DataKind.history_deals: frozenset({
"ticket",
"order",
"time",
"type",
"entry",
"symbol",
"volume",
"price",
"profit",
}),
}
_OPTIONAL_TIME_COLUMNS_BY_KIND: dict[DataKind, frozenset[str]] = {
DataKind.orders: frozenset({
"time_setup_msc",
"time_done",
"time_done_msc",
}),
DataKind.history_orders: frozenset({
"time_setup_msc",
"time_done",
"time_done_msc",
}),
DataKind.positions: frozenset({"time_msc"}),
}
TIME_COLUMNS: dict[DataKind, frozenset[str]] = {
kind: (REQUIRED_COLUMNS[kind] & _TIME_COLUMN_NAMES)
| _OPTIONAL_TIME_COLUMNS_BY_KIND.get(kind, frozenset())
for kind in DataKind
}
DEDUP_KEYS: dict[DataKind, tuple[tuple[str, ...], ...]] = {
DataKind.rates: (("symbol", "timeframe", "time"), ("symbol", "time")),
DataKind.ticks: (("symbol", "time_msc"), ("symbol", "time")),
DataKind.history_orders: (("ticket",), ("symbol", "time", "type")),
DataKind.history_deals: (("ticket",), ("symbol", "time", "type", "entry")),
}
def schema_columns(kind: DataKind) -> frozenset[str]:
"""Return required column names for a dataset kind.
Args:
kind: Dataset kind.
Returns:
Required column names for ``kind``.
"""
return REQUIRED_COLUMNS[kind]
def validate_schema(
frame: pd.DataFrame,
kind: DataKind,
*,
extra_required: Iterable[str] | None = None,
) -> None:
"""Validate that a DataFrame includes required columns for a dataset kind.
Args:
frame: DataFrame to validate.
kind: Expected dataset kind.
extra_required: Additional columns that must be present (for example
``symbol`` and ``timeframe`` on stored rate history).
Raises:
Mt5SchemaError: If required columns are missing.
"""
if frame.empty and len(frame.columns) == 0:
return
required = set(REQUIRED_COLUMNS[kind])
if extra_required is not None:
required.update(extra_required)
missing = required - set(frame.columns)
if missing:
msg = (
f"{kind.value} schema is missing required columns: "
f"{', '.join(sorted(missing))}."
)
raise Mt5SchemaError(msg)
def _coerce_mt5_time_column(series: pd.Series, column: str) -> pd.Series:
"""Coerce one MT5 time column to UTC-aware datetimes.
Returns:
Series with UTC-aware datetime values.
"""
if pd.api.types.is_datetime64_any_dtype(series):
return pd.to_datetime(series, utc=True, errors="coerce")
if pd.api.types.is_numeric_dtype(series):
unit = "ms" if column.endswith("_msc") else "s"
return pd.to_datetime(series, unit=unit, utc=True, errors="coerce")
return pd.to_datetime(series, utc=True, errors="coerce")
def normalize_time_columns(frame: pd.DataFrame, kind: DataKind) -> pd.DataFrame:
"""Coerce dataset time columns to UTC-aware datetimes when present.
Any column in :data:`KNOWN_MT5_TIME_COLUMNS` that is present in ``frame``
is normalized. Numeric MT5 epoch values use seconds for ``time``,
``time_setup``, and ``time_done``, and milliseconds for ``*_msc`` columns.
Args:
frame: Source DataFrame from MT5 or pdmt5.
kind: Dataset kind (retained for API compatibility).
Returns:
DataFrame copy with normalized time columns.
"""
del kind
normalized = frame.copy()
for column in normalized.columns:
if column not in _TIME_COLUMN_NAMES:
continue
normalized[column] = _coerce_mt5_time_column(normalized[column], column)
return normalized
def normalize_dataframe(
frame: pd.DataFrame,
kind: DataKind,
*,
symbol: str | None = None,
timeframe: int | str | None = None,
sort: bool = True,
) -> pd.DataFrame:
"""Normalize MT5 DataFrame columns, timestamps, and storage metadata.
Ensures UTC timestamps, optionally injects ``symbol`` / ``timeframe`` for
storage-oriented datasets, and sorts chronologically when a ``time`` column
exists.
Args:
frame: Source DataFrame from MT5 or pdmt5.
kind: Dataset kind guiding normalization rules.
symbol: Optional symbol to inject when missing.
timeframe: Optional timeframe integer or name to inject for rates.
sort: Whether to sort by ``time`` or ``time_msc`` when present.
Returns:
Normalized DataFrame copy.
"""
if frame.empty and len(frame.columns) == 0:
return frame.copy()
normalized = normalize_time_columns(frame, kind)
if symbol is not None and "symbol" not in normalized.columns:
normalized.insert(0, "symbol", normalize_symbol(symbol))
if timeframe is not None and kind is DataKind.rates:
tf = parse_timeframe(timeframe)
if "timeframe" not in normalized.columns:
insert_at = 1 if "symbol" in normalized.columns else 0
normalized.insert(insert_at, "timeframe", tf)
validate_schema(normalized, kind)
if sort:
if "time" in normalized.columns:
normalized = normalized.sort_values("time", kind="stable")
elif "time_msc" in normalized.columns:
normalized = normalized.sort_values("time_msc", kind="stable")
normalized = normalized.reset_index(drop=True)
return normalized
def ensure_utc_columns(frame: pd.DataFrame, columns: Iterable[str]) -> pd.DataFrame:
"""Return a copy with selected columns coerced to UTC datetimes.
Args:
frame: Source DataFrame.
columns: Column names to coerce.
Returns:
DataFrame copy with UTC-aware datetime columns.
"""
normalized = frame.copy()
for column in columns:
if column not in normalized.columns:
continue
if column in _TIME_COLUMN_NAMES:
normalized[column] = _coerce_mt5_time_column(normalized[column], column)
else:
normalized[column] = pd.to_datetime(
normalized[column], utc=True, errors="coerce"
)
return normalized
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"""Optional OpenTelemetry metrics for MT5 history and snapshot observability."""
from __future__ import annotations
import logging
import time
from contextlib import contextmanager
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from collections.abc import Iterator
logger = logging.getLogger(__name__)
_otel_available_flag = False
try:
import opentelemetry.metrics as _otel_metrics_mod
from opentelemetry.sdk.metrics import MeterProvider as _OtelMeterProvider
from opentelemetry.sdk.metrics.export import (
PeriodicExportingMetricReader as _OtelPeriodicReader,
)
from opentelemetry.sdk.resources import Resource as _OtelResource
_otel_available_flag = True
except ImportError: # pragma: no cover
_otel_metrics_mod = None # type: ignore[assignment]
_OtelMeterProvider = None # type: ignore[assignment]
_OtelPeriodicReader = None # type: ignore[assignment]
_OtelResource = None # type: ignore[assignment]
_OTEL_AVAILABLE: bool = _otel_available_flag
try:
from opentelemetry.exporter.otlp.proto.http.metric_exporter import ( # type: ignore[import]
OTLPMetricExporter as _OtelOTLPExporter, # type: ignore[reportUnknownVariableType]
)
except ImportError: # pragma: no cover
_OtelOTLPExporter = None # type: ignore[assignment, misc]
class _NoOp:
"""No-op instrument that silently ignores all calls."""
def add(
self,
amount: float,
attributes: dict[str, str] | None = None,
) -> None:
"""No-op add."""
def set(
self,
amount: float,
attributes: dict[str, str] | None = None,
) -> None:
"""No-op set."""
def record(
self,
amount: float,
attributes: dict[str, str] | None = None,
) -> None:
"""No-op record."""
_NOOP: _NoOp = _NoOp()
class _Mt5Metrics:
"""MT5 metric instrument registry.
Holds references to OTel instruments. All instruments are no-op until
:meth:`configure` is called with a compatible meter object.
"""
def __init__(self) -> None:
self._history_duration: Any = _NOOP
self._history_rows: Any = _NOOP
self._history_failures: Any = _NOOP
self._snapshot_duration: Any = _NOOP
self._snapshot_failures: Any = _NOOP
self._account_balance: Any = _NOOP
self._account_equity: Any = _NOOP
self._account_margin: Any = _NOOP
self._account_margin_free: Any = _NOOP
self._account_margin_level: Any = _NOOP
self._position_profit: Any = _NOOP
self._position_volume: Any = _NOOP
self._terminal_connected: Any = _NOOP
self._terminal_trade_allowed: Any = _NOOP
self._terminal_trade_expert: Any = _NOOP
self._last_successful_update: Any = _NOOP
def configure(self, meter: Any) -> None: # noqa: ANN401
"""Set up metric instruments from a meter object.
Args:
meter: An OpenTelemetry ``Meter`` or duck-typed compatible object
that supports ``create_counter``, ``create_histogram``, and
``create_gauge``.
"""
self._history_duration = meter.create_histogram(
"mt5_history_update_duration_seconds",
unit="s",
description="Duration of incremental history update operations.",
)
self._history_rows = meter.create_counter(
"mt5_history_update_rows_total",
description="Rows written during incremental history updates.",
)
self._history_failures = meter.create_counter(
"mt5_history_update_failures_total",
description="Number of incremental history update failures.",
)
self._snapshot_duration = meter.create_histogram(
"mt5_snapshot_update_duration_seconds",
unit="s",
description="Duration of snapshot update operations.",
)
self._snapshot_failures = meter.create_counter(
"mt5_snapshot_update_failures_total",
description="Number of snapshot update failures.",
)
self._account_balance = meter.create_gauge(
"mt5_account_balance",
description="Account balance.",
)
self._account_equity = meter.create_gauge(
"mt5_account_equity",
description="Account equity.",
)
self._account_margin = meter.create_gauge(
"mt5_account_margin",
description="Account margin used.",
)
self._account_margin_free = meter.create_gauge(
"mt5_account_margin_free",
description="Account free margin.",
)
self._account_margin_level = meter.create_gauge(
"mt5_account_margin_level",
description="Account margin level as a percentage.",
)
self._position_profit = meter.create_gauge(
"mt5_position_profit",
description="Floating profit for an open position.",
)
self._position_volume = meter.create_gauge(
"mt5_position_volume",
description="Volume of an open position.",
)
self._terminal_connected = meter.create_gauge(
"mt5_terminal_connected",
description="1 if the terminal is connected to the broker, 0 otherwise.",
)
self._terminal_trade_allowed = meter.create_gauge(
"mt5_terminal_trade_allowed",
description="1 if trading is allowed by the broker server, 0 otherwise.",
)
self._terminal_trade_expert = meter.create_gauge(
"mt5_terminal_trade_expert",
description="1 if Expert Advisor trading is enabled, 0 otherwise.",
)
self._last_successful_update = meter.create_gauge(
"mt5_last_successful_update_timestamp",
description="Unix timestamp of the last successful history update.",
)
@contextmanager
def record_history_update(
self,
*,
dataset: str,
) -> Iterator[None]:
"""Context manager recording history update duration and failures.
Args:
dataset: Dataset label (e.g. ``"rates"``).
Yields:
None inside the update operation.
"""
attrs = {"dataset": dataset}
start = time.monotonic()
try:
yield
self._history_duration.record(time.monotonic() - start, attrs)
self._last_successful_update.set(time.time(), attrs)
except Exception:
self._history_failures.add(1, attrs)
raise
def add_history_rows(self, count: int, *, dataset: str) -> None:
"""Increment the history rows-written counter.
Args:
count: Number of rows written during this update.
dataset: Dataset label (e.g. ``"rates"``).
"""
self._history_rows.add(count, {"dataset": dataset})
@contextmanager
def record_snapshot_update(self) -> Iterator[None]:
"""Context manager recording snapshot update duration and failures.
Yields:
None inside the snapshot operation.
"""
start = time.monotonic()
try:
yield
self._snapshot_duration.record(time.monotonic() - start, {})
except Exception:
self._snapshot_failures.add(1, {})
raise
def record_account_state(
self,
*,
login: str,
server: str,
balance: float,
equity: float,
margin: float,
margin_free: float,
margin_level: float,
) -> None:
"""Emit account metric gauges.
Args:
login: Account login number (as string; not a password or secret).
server: Broker server name.
balance: Account balance.
equity: Account equity.
margin: Margin used.
margin_free: Free margin.
margin_level: Margin level percentage.
"""
attrs: dict[str, str] = {"login": login, "server": server}
self._account_balance.set(balance, attrs)
self._account_equity.set(equity, attrs)
self._account_margin.set(margin, attrs)
self._account_margin_free.set(margin_free, attrs)
self._account_margin_level.set(margin_level, attrs)
def record_position_state(
self,
*,
login: str,
server: str,
symbol: str,
profit: float,
volume: float,
) -> None:
"""Emit position metric gauges.
Args:
login: Account login number (as string).
server: Broker server name.
symbol: Position symbol.
profit: Floating profit/loss.
volume: Position volume.
"""
attrs: dict[str, str] = {"login": login, "server": server, "symbol": symbol}
self._position_profit.set(profit, attrs)
self._position_volume.set(volume, attrs)
def record_terminal_state(
self,
*,
connected: float,
trade_allowed: float,
trade_expert: float,
) -> None:
"""Emit terminal connection and trading status gauges.
Args:
connected: 1.0 if connected to the broker, 0.0 otherwise.
trade_allowed: 1.0 if broker server allows trading, 0.0 otherwise.
trade_expert: 1.0 if Expert Advisor trading is enabled, 0.0 otherwise.
"""
self._terminal_connected.set(connected, {})
self._terminal_trade_allowed.set(trade_allowed, {})
self._terminal_trade_expert.set(trade_expert, {})
_metrics = _Mt5Metrics()
def configure_metrics(meter: Any) -> None: # noqa: ANN401
"""Configure MT5 metrics using the provided meter.
Args:
meter: An OpenTelemetry ``Meter`` or duck-typed compatible object.
"""
_metrics.configure(meter)
def enable_otel_metrics(
service_name: str = "mt5cli",
readers: list[Any] | None = None,
) -> None:
"""Enable OTel metrics by wiring up an SDK ``MeterProvider`` pipeline.
Requires the ``otel`` optional dependency group:
``pip install "mt5cli[otel]"``.
Args:
service_name: OTel meter/service name used for the ``Resource`` and
the meter itself.
readers: Optional list of metric readers. When *None* (the default),
a :class:`~opentelemetry.sdk.metrics.export.PeriodicExportingMetricReader`
backed by an OTLP HTTP exporter is created automatically
(reads the endpoint from ``OTEL_EXPORTER_OTLP_ENDPOINT``).
Pass a custom list (e.g. ``InMemoryMetricReader`` for tests)
to override.
Raises:
ImportError: If ``opentelemetry-api`` is not installed, or if
``readers`` is *None* and
``opentelemetry-exporter-otlp-proto-http`` is not installed.
"""
if not _OTEL_AVAILABLE:
msg = (
"opentelemetry-api is not installed. "
'Install it with: pip install "mt5cli[otel]"'
)
raise ImportError(msg)
if readers is None:
if _OtelOTLPExporter is None:
msg = (
"opentelemetry-exporter-otlp-proto-http is required for the "
"default OTLP export pipeline. "
'Install it with: pip install "mt5cli[otel]" or pass a '
"custom readers list."
)
raise ImportError(msg)
readers = [_OtelPeriodicReader(_OtelOTLPExporter())] # type: ignore[misc]
resource = _OtelResource.create({"service.name": service_name}) # type: ignore[union-attr]
provider = _OtelMeterProvider(resource=resource, metric_readers=readers) # type: ignore[misc]
_otel_metrics_mod.set_meter_provider(provider) # type: ignore[union-attr]
meter = provider.get_meter(service_name)
configure_metrics(meter)
def get_metrics() -> _Mt5Metrics:
"""Return the global :class:`_Mt5Metrics` instance.
Returns:
The global metric registry (no-op until :func:`configure_metrics` is
called).
"""
return _metrics
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+456
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@@ -0,0 +1,456 @@
"""Utility constants, types, and functions for the mt5cli package."""
from __future__ import annotations
import json
import sqlite3
from contextlib import closing
from datetime import UTC, datetime
from enum import StrEnum
from pathlib import Path
from typing import TYPE_CHECKING, Any, TypeGuard
import click
from pdmt5 import COPY_TICKS_MAP as _COPY_TICKS_MAP
from pdmt5 import TIMEFRAME_MAP as _TIMEFRAME_MAP
from pdmt5 import parse_copy_ticks as _parse_copy_ticks
from pdmt5 import parse_timeframe as _parse_timeframe
if TYPE_CHECKING:
from collections.abc import Sequence
import pandas as pd
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
TIMEFRAME_NAMES: tuple[str, ...] = tuple(
name for name in _TIMEFRAME_MAP if not name.startswith("TIMEFRAME_")
)
_TICK_FLAG_NAMES: tuple[str, ...] = tuple(
name for name in _COPY_TICKS_MAP if not name.startswith("COPY_TICKS_")
)
_FORMAT_EXTENSIONS: dict[str, str] = {
".csv": "csv",
".json": "json",
".parquet": "parquet",
".pq": "parquet",
".db": "sqlite3",
".sqlite": "sqlite3",
".sqlite3": "sqlite3",
}
# ---------------------------------------------------------------------------
# Enums
# ---------------------------------------------------------------------------
class OutputFormat(StrEnum):
"""Supported output file formats."""
csv = "csv"
json = "json"
parquet = "parquet"
sqlite3 = "sqlite3"
class LogLevel(StrEnum):
"""Logging verbosity levels."""
DEBUG = "DEBUG"
INFO = "INFO"
WARNING = "WARNING"
ERROR = "ERROR"
class Dataset(StrEnum):
"""Datasets supported by the ``collect-history`` command."""
rates = "rates"
ticks = "ticks"
history_orders = "history-orders"
history_deals = "history-deals"
@property
def table_name(self) -> str:
"""Return the SQLite table name for this dataset."""
return self.value.replace("-", "_")
class IfExists(StrEnum):
"""SQLite table conflict behavior for the ``collect-history`` command."""
APPEND = "append"
REPLACE = "replace"
FAIL = "fail"
# ---------------------------------------------------------------------------
# Click parameter types
# ---------------------------------------------------------------------------
class _DateTimeType(click.ParamType):
"""Click parameter type for ISO 8601 datetime strings."""
name = "DATETIME"
def convert(
self,
value: object,
param: click.Parameter | None,
ctx: click.Context | None,
) -> datetime:
"""Convert a string value to a timezone-aware datetime.
Args:
value: Raw value from the command line.
param: Click parameter instance.
ctx: Click context.
Returns:
Parsed datetime.
"""
if isinstance(value, datetime):
return value
try:
return parse_datetime(str(value))
except ValueError as exc:
self.fail(str(exc), param, ctx)
class _TimeframeType(click.ParamType):
"""Click parameter type for MT5 timeframe values."""
name = "TIMEFRAME"
def convert(
self,
value: object,
param: click.Parameter | None,
ctx: click.Context | None,
) -> int:
"""Convert a string or integer value to a timeframe integer.
Args:
value: Raw value from the command line.
param: Click parameter instance.
ctx: Click context.
Returns:
Integer timeframe value.
"""
try:
return parse_timeframe(value)
except ValueError as exc:
self.fail(str(exc), param, ctx)
class _TickFlagsType(click.ParamType):
"""Click parameter type for MT5 tick copy flags."""
name = "FLAGS"
def convert(
self,
value: object,
param: click.Parameter | None,
ctx: click.Context | None,
) -> int:
"""Convert a string or integer value to a tick flags integer.
Args:
value: Raw value from the command line.
param: Click parameter instance.
ctx: Click context.
Returns:
Integer tick flag value.
"""
try:
return parse_tick_flags(value)
except ValueError as exc:
self.fail(str(exc), param, ctx)
class _RequestType(click.ParamType):
"""Click parameter type for JSON order requests."""
name = "REQUEST"
def convert(
self,
value: object,
param: click.Parameter | None,
ctx: click.Context | None,
) -> dict[str, Any]:
"""Convert a raw CLI value to an order request dictionary.
Args:
value: Raw value from the command line.
param: Click parameter instance.
ctx: Click context.
Returns:
Parsed request dictionary.
"""
try:
return parse_request(str(value))
except ValueError as exc:
self.fail(str(exc), param, ctx)
DATETIME_TYPE = _DateTimeType()
TIMEFRAME_TYPE = _TimeframeType()
TICK_FLAGS_TYPE = _TickFlagsType()
REQUEST_TYPE = _RequestType()
# ---------------------------------------------------------------------------
# Public utility functions
# ---------------------------------------------------------------------------
def detect_format(
output_path: Path,
explicit_format: str | None = None,
) -> str:
"""Detect the output format from a file extension or explicit format string.
Args:
output_path: Path to the output file.
explicit_format: Explicitly specified format, if any.
Returns:
The detected format string.
Raises:
ValueError: If the format cannot be determined.
"""
if explicit_format is not None:
return explicit_format
suffix = output_path.suffix.lower()
if suffix in _FORMAT_EXTENSIONS:
return _FORMAT_EXTENSIONS[suffix]
msg = (
f"Cannot detect format from extension '{suffix}'."
" Use --format to specify the output format."
)
raise ValueError(msg)
def coerce_login(login: int | str | None) -> int | None:
"""Coerce a login value to int, treating empty strings as unset.
Returns:
Integer login, or None when unset or an empty string.
"""
if login is None or isinstance(login, int):
return login
text = login.strip()
if not text:
return None
return int(text)
def export_dataframe_to_sqlite(
df: pd.DataFrame,
output_path: Path,
table_name: str = "data",
*,
if_exists: IfExists = IfExists.APPEND,
index: bool = False,
index_label: str | None = None,
deduplicate_on: Sequence[str] | None = None,
) -> None:
"""Write a DataFrame to SQLite with configurable append and deduplication.
Args:
df: DataFrame to export.
output_path: SQLite database path.
table_name: Target table name.
if_exists: Conflict behavior when the table already exists.
index: Whether to write the DataFrame index as a column.
index_label: Column name for the index when ``index=True``.
deduplicate_on: Optional key columns to deduplicate after writing,
keeping the latest ``ROWID`` per key group. Deduplication scans the
full table, so repeated appends cost O(table size); index the key
columns when appending frequently.
"""
with closing(sqlite3.connect(output_path)) as conn, conn:
df.to_sql( # type: ignore[reportUnknownMemberType]
table_name,
conn,
if_exists=if_exists.value,
index=index,
index_label=index_label,
)
if deduplicate_on:
from .history import drop_duplicates_in_table # noqa: PLC0415
drop_duplicates_in_table(
conn.cursor(),
table_name,
list(deduplicate_on),
keep="last",
)
conn.commit()
def export_dataframe(
df: pd.DataFrame,
output_path: Path,
output_format: str,
table_name: str = "data",
) -> None:
"""Export a pandas DataFrame to the specified file format.
Args:
df: DataFrame to export.
output_path: Path to the output file.
output_format: Output format (csv, json, parquet, or sqlite3).
table_name: Table name for SQLite3 output.
Raises:
ImportError: If the parquet format is requested but pyarrow is not installed.
ValueError: If the output format is not supported.
"""
if output_format == "csv":
df.to_csv(output_path, index=False)
elif output_format == "json":
df.to_json(
output_path,
orient="records",
date_format="iso",
indent=2,
)
elif output_format == "parquet":
try:
__import__("pyarrow")
except ImportError as exc:
msg = (
"Parquet export requires the optional dependency pyarrow. "
'Install it with: pip install "mt5cli[parquet]"'
)
raise ImportError(msg) from exc
df.to_parquet(output_path, index=False)
elif output_format == "sqlite3":
export_dataframe_to_sqlite(
df,
output_path,
table_name,
if_exists=IfExists.REPLACE,
index=False,
)
else:
msg = f"Unsupported output format: {output_format}"
raise ValueError(msg)
def parse_datetime(value: str) -> datetime:
"""Parse an ISO 8601 datetime string to a timezone-aware datetime.
Args:
value: ISO 8601 datetime string (e.g., '2024-01-01' or
'2024-01-01T12:00:00+00:00').
Returns:
Parsed datetime with UTC timezone if no timezone is specified.
Raises:
ValueError: If the string cannot be parsed.
"""
try:
dt = datetime.fromisoformat(value)
except ValueError:
msg = f"Invalid datetime format: '{value}'. Use ISO 8601 format."
raise ValueError(msg) from None
if dt.tzinfo is None:
dt = dt.replace(tzinfo=UTC)
return dt
def parse_timeframe(value: object) -> int:
"""Parse a timeframe string or integer value.
Args:
value: Timeframe name (e.g., 'M1', 'H1', 'D1') or integer value.
Returns:
Integer timeframe value.
Raises:
ValueError: If the timeframe is invalid.
"""
try:
return _parse_timeframe(value)
except ValueError:
display = value if isinstance(value, str) else repr(value)
valid = ", ".join(TIMEFRAME_NAMES)
msg = (
f"Invalid timeframe: '{display}'. "
f"Use one of: {valid}, or a supported integer."
)
raise ValueError(msg) from None
def parse_tick_flags(value: object) -> int:
"""Parse tick flags string or integer value.
Args:
value: Tick flag name (ALL, INFO, TRADE, COPY_TICKS_*) or integer value.
Returns:
Integer tick flag value compatible with MetaTrader 5 ``COPY_TICKS_*``.
Raises:
ValueError: If the flag is invalid.
"""
try:
return _parse_copy_ticks(value)
except ValueError:
display = value if isinstance(value, str) else repr(value)
valid = ", ".join(_TICK_FLAG_NAMES)
msg = (
f"Invalid tick flags: '{display}'. "
f"Use one of: {valid}, or a supported integer."
)
raise ValueError(msg) from None
def _is_request_dict(value: object) -> TypeGuard[dict[str, Any]]:
return isinstance(value, dict)
def parse_request(value: str) -> dict[str, Any]:
"""Parse a JSON-formatted order request string or file reference.
Args:
value: JSON object string, or '@path' to read JSON from a file.
Returns:
Parsed request dictionary.
Raises:
ValueError: If the request file cannot be read or the value is not a
JSON object.
"""
if value.startswith("@"):
path = Path(value[1:])
try:
text = path.read_text(encoding="utf-8")
except (OSError, UnicodeDecodeError) as exc:
msg = f"Failed to read JSON request file '{path}': {exc}"
raise ValueError(msg) from exc
else:
text = value
try:
parsed: object = json.loads(text)
except json.JSONDecodeError as exc:
msg = f"Invalid JSON request: {exc}"
raise ValueError(msg) from exc
if not _is_request_dict(parsed):
msg = "Order request must be a JSON object."
raise ValueError(msg)
return parsed
+18 -9
View File
@@ -1,7 +1,7 @@
[project]
name = "mt5cli"
version = "0.2.0"
description = "Command-line tool for MetaTrader 5"
version = "1.1.0"
description = "Generic MT5 data and execution infrastructure for Python applications"
authors = [{name = "dceoy", email = "dceoy@users.noreply.github.com"}]
maintainers = [{name = "dceoy", email = "dceoy@users.noreply.github.com"}]
license = "MIT"
@@ -9,9 +9,8 @@ license-files = ["LICENSE"]
readme = "README.md"
requires-python = ">= 3.11, < 3.14"
dependencies = [
"pdmt5 >= 0.2.3",
"pdmt5>=1.0.0",
"click >= 8.1.0",
"pyarrow >= 19.0.0",
"typer >= 0.15.0",
]
classifiers = [
@@ -25,6 +24,14 @@ classifiers = [
"Topic :: Office/Business :: Financial :: Investment",
]
[project.optional-dependencies]
parquet = ["pyarrow >= 19.0.0"]
otel = [
"opentelemetry-api",
"opentelemetry-sdk",
"opentelemetry-exporter-otlp-proto-http",
]
[project.scripts]
mt5cli = "mt5cli.cli:main"
@@ -42,16 +49,15 @@ dev = [
"pytest-mock >= 3.12.0",
"pytest-cov >= 5.0.0",
"pandas-stubs >= 2.2.3.250527",
"pyarrow >= 19.0.0",
"opentelemetry-api",
"opentelemetry-sdk",
"mkdocs >= 1.6.1",
"mkdocs-material >= 9.7.6",
"mkdocstrings[python] >= 1.0.4",
"pymdown-extensions >= 10.21.2",
]
[tool.uv.build-backend]
source-include = ["mt5cli/**", "LICENSE"]
source-exclude = ["tests/**"]
[tool.ruff]
line-length = 88
exclude = ["build", ".venv"]
@@ -179,7 +185,10 @@ omit = [
[tool.coverage.report]
show_missing = true
fail_under = 100
exclude_lines = ["if TYPE_CHECKING:"]
exclude_also = [
"if TYPE_CHECKING:",
"^\\s+\\.\\.\\.$",
]
[build-system]
requires = ["hatchling"]
+24 -15
View File
@@ -50,21 +50,22 @@ Global options MUST precede the subcommand.
## Commands
| Command | Required options | Optional options |
| ---------------- | ----------------------------------------------------- | --------------------------------------------------------------------------- |
| `rates-from` | `--symbol`, `--timeframe`, `--date-from`, `--count` | — |
| `rates-from-pos` | `--symbol`, `--timeframe`, `--start-pos`, `--count` | — |
| `rates-range` | `--symbol`, `--timeframe`, `--date-from`, `--date-to` | — |
| `ticks-from` | `--symbol`, `--date-from`, `--count`, `--flags` | — |
| `ticks-range` | `--symbol`, `--date-from`, `--date-to`, `--flags` | — |
| `account-info` | — | — |
| `terminal-info` | — | — |
| `symbols` | — | `--group` (e.g., `*USD*`) |
| `symbol-info` | `--symbol` | — |
| `orders` | — | `--symbol`, `--group`, `--ticket` |
| `positions` | — | `--symbol`, `--group`, `--ticket` |
| `history-orders` | — | `--date-from`, `--date-to`, `--group`, `--symbol`, `--ticket`, `--position` |
| `history-deals` | — | `--date-from`, `--date-to`, `--group`, `--symbol`, `--ticket`, `--position` |
| Command | Required options | Optional options |
| ----------------- | ----------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `rates-from` | `--symbol`, `--timeframe`, `--date-from`, `--count` | — |
| `rates-from-pos` | `--symbol`, `--timeframe`, `--start-pos`, `--count` | — |
| `rates-range` | `--symbol`, `--timeframe`, `--date-from`, `--date-to` | — |
| `ticks-from` | `--symbol`, `--date-from`, `--count`, `--flags` | — |
| `ticks-range` | `--symbol`, `--date-from`, `--date-to`, `--flags` | — |
| `account-info` | — | — |
| `terminal-info` | — | — |
| `symbols` | — | `--group` (e.g., `*USD*`) |
| `symbol-info` | `--symbol` | — |
| `orders` | — | `--symbol`, `--group`, `--ticket` |
| `positions` | — | `--symbol`, `--group`, `--ticket` |
| `history-orders` | — | `--date-from`, `--date-to`, `--group`, `--symbol`, `--ticket`, `--position` |
| `history-deals` | — | `--date-from`, `--date-to`, `--group`, `--symbol`, `--ticket`, `--position` |
| `collect-history` | `--symbol` (repeatable), `--date-from`, `--date-to` | `--dataset` (repeatable; rates/ticks/history-orders/history-deals; default all), `--timeframe` (M1; recorded on rates), `--flags` (ALL), `--if-exists` (append/replace/fail; default fail), `--with-views` (SQLite3 output only) |
## Examples
@@ -85,6 +86,14 @@ mt5cli -o data.db --table symbols symbols --group "*USD*"
# Historical deals filtered by symbol (using an already-logged-in MT5 terminal).
mt5cli -o deals.csv history-deals --symbol EURUSD --date-from 2024-01-01
# Bundle selected historical datasets into one SQLite db, appending to any
# existing tables, plus cash_events and positions_reconstructed views.
mt5cli -o history.db collect-history \
--symbol EURUSD --symbol GBPUSD \
--date-from 2024-01-01 --date-to 2024-02-01 \
--dataset rates --dataset history-deals \
--timeframe M1 --flags ALL --if-exists append --with-views
```
## Guidelines
+90
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@@ -0,0 +1,90 @@
"""Shared pytest fixtures for mt5cli tests."""
from __future__ import annotations
import sqlite3
from typing import TYPE_CHECKING, Any, Literal
from unittest.mock import MagicMock
import pandas as pd
import pytest
from pytest_mock import MockerFixture # noqa: TC002
if TYPE_CHECKING:
from types import TracebackType
_DATAFRAME_METHODS = (
"copy_rates_from_as_df",
"copy_rates_from_pos_as_df",
"copy_rates_range_as_df",
"copy_ticks_from_as_df",
"copy_ticks_range_as_df",
"account_info_as_df",
"terminal_info_as_df",
"symbols_get_as_df",
"symbol_info_as_df",
"orders_get_as_df",
"positions_get_as_df",
"history_orders_get_as_df",
"history_deals_get_as_df",
"version_as_df",
"last_error_as_df",
"symbol_info_tick_as_df",
"market_book_get_as_df",
"order_check_as_df",
"order_send_as_df",
)
_ORIGINAL_SQLITE_CONNECT = sqlite3.connect
class ClosingSqliteConnection(sqlite3.Connection):
"""SQLite connection that closes after context-manager exit in tests."""
def __exit__(
self,
exc_type: type[BaseException] | None,
exc_value: BaseException | None,
traceback: TracebackType | None,
) -> Literal[False]:
"""Commit or roll back the transaction, then close the connection."""
try:
super().__exit__(exc_type, exc_value, traceback)
finally:
self.close()
return False
def build_mock_mt5_data_client() -> MagicMock:
"""Return a MagicMock Mt5DataClient with common DataFrame stubs."""
client = MagicMock()
sample_df = pd.DataFrame({"col": [1]})
for method_name in _DATAFRAME_METHODS:
getattr(client, method_name).return_value = sample_df
client.version.return_value = (5, 0, 1)
client.terminal_info.return_value = {"connected": True, "paths": ["terminal.exe"]}
client.account_info.return_value = {"login": 123, "limits": {"modes": ["demo"]}}
client.symbols_total.return_value = 42
return client
@pytest.fixture
def mock_client(mocker: MockerFixture) -> MagicMock:
"""Create and patch a mock Mt5DataClient for CLI and SDK tests."""
client = build_mock_mt5_data_client()
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
return client
@pytest.fixture(autouse=True)
def close_sqlite_context_connections(monkeypatch: pytest.MonkeyPatch) -> None:
"""Make test SQLite context managers close their connection handles."""
def connect(
*args: Any, # noqa: ANN401
**kwargs: Any, # noqa: ANN401
) -> sqlite3.Connection:
kwargs.setdefault("factory", ClosingSqliteConnection)
return _ORIGINAL_SQLITE_CONNECT(*args, **kwargs)
monkeypatch.setattr(sqlite3, "connect", connect)
+1421 -340
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+861
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@@ -0,0 +1,861 @@
"""Contract tests for the mt5cli public API and dataset schemas."""
from __future__ import annotations
import importlib
import sqlite3
from datetime import UTC, datetime
from importlib.metadata import requires
from typing import TYPE_CHECKING, get_type_hints
from unittest.mock import MagicMock
if TYPE_CHECKING:
from pathlib import Path
import pandas as pd
import pytest
from pdmt5 import Mt5RuntimeError, Mt5TradingError
from pytest_mock import MockerFixture # noqa: TC002
import mt5cli
from mt5cli import (
STABLE_SDK_EXPORTS,
AccountSpec,
ExecutionStatus,
MarginVolume,
MT5Client,
Mt5CliError,
Mt5ConnectionError,
Mt5OperationError,
Mt5SchemaError,
OrderExecutionResult,
OrderLimits,
RateTarget,
build_config,
build_rate_targets,
calculate_account_projected_margin_ratio,
calculate_margin_and_volume,
calculate_positions_margin,
calculate_projected_margin_ratio,
calculate_symbol_group_margin_ratio,
calculate_trailing_stop_updates,
drop_forming_rate_bar,
ensure_symbol_selected,
extract_tick_price,
fetch_latest_closed_rates,
fetch_latest_closed_rates_for_trading_client,
fetch_latest_closed_rates_indexed,
load_rate_series_from_sqlite,
mt5_session,
mt5_trading_session,
normalize_order_volume,
place_market_order,
resolve_account_spec,
resolve_account_specs,
)
from mt5cli.converters import (
ensure_utc,
granularity_name,
normalize_symbol,
normalize_symbols,
parse_date_range,
recent_window,
)
from mt5cli.exceptions import (
call_with_normalized_errors,
is_recoverable_mt5_error,
normalize_mt5_exception,
)
from mt5cli.history import (
create_rate_compatibility_views,
load_rate_data,
resolve_rate_view_name,
)
from mt5cli.retry import retry_with_backoff
from mt5cli.schemas import (
DEDUP_KEYS,
REQUIRED_COLUMNS,
TIME_COLUMNS,
DataKind,
ensure_utc_columns,
normalize_dataframe,
normalize_time_columns,
schema_columns,
validate_schema,
)
from mt5cli.utils import (
Dataset,
detect_format,
export_dataframe,
export_dataframe_to_sqlite,
)
def _sample_frame(kind: DataKind) -> pd.DataFrame:
if kind is DataKind.rates:
return pd.DataFrame({
"time": [datetime(2024, 1, 1, tzinfo=UTC)],
"open": [1.1],
"high": [1.2],
"low": [1.0],
"close": [1.15],
"tick_volume": [10],
"spread": [1],
"real_volume": [0],
})
if kind is DataKind.ticks:
return pd.DataFrame({
"time": [datetime(2024, 1, 1, tzinfo=UTC)],
"bid": [1.1],
"ask": [1.11],
"last": [1.105],
"volume": [1],
"time_msc": [datetime(2024, 1, 1, tzinfo=UTC)],
"flags": [2],
"volume_real": [0.0],
})
if kind is DataKind.orders:
return pd.DataFrame({
"ticket": [1],
"time_setup": [datetime(2024, 1, 1, tzinfo=UTC)],
"type": [0],
"state": [1],
"symbol": ["EURUSD"],
"volume_current": [0.1],
"price_open": [1.1],
})
if kind is DataKind.positions:
return pd.DataFrame({
"ticket": [1],
"time": [datetime(2024, 1, 1, tzinfo=UTC)],
"type": [0],
"symbol": ["EURUSD"],
"volume": [0.1],
"price_open": [1.1],
"price_current": [1.11],
"profit": [1.0],
})
if kind is DataKind.history_orders:
return pd.DataFrame({
"ticket": [1],
"time_setup": [datetime(2024, 1, 1, tzinfo=UTC)],
"type": [0],
"state": [3],
"symbol": ["EURUSD"],
"volume_initial": [0.1],
"price_open": [1.1],
})
return pd.DataFrame({
"ticket": [1],
"order": [2],
"time": [datetime(2024, 1, 1, tzinfo=UTC)],
"type": [0],
"entry": [0],
"symbol": ["EURUSD"],
"volume": [0.1],
"price": [1.1],
"profit": [0.0],
})
@pytest.mark.parametrize("kind", list(DataKind))
def test_required_columns_contract(kind: DataKind) -> None:
"""Each dataset kind exposes a non-empty required column contract."""
assert REQUIRED_COLUMNS[kind]
validate_schema(_sample_frame(kind), kind)
@pytest.mark.parametrize("kind", list(DataKind))
def test_normalize_dataframe_injects_storage_metadata(kind: DataKind) -> None:
"""Normalization accepts MT5 frames and optional storage metadata."""
frame = _sample_frame(kind)
normalized = normalize_dataframe(
frame,
kind,
symbol="eurusd",
timeframe="M1" if kind is DataKind.rates else None,
)
if kind is DataKind.rates:
assert normalized.loc[0, "symbol"] == "eurusd"
assert normalized.loc[0, "timeframe"] == 1
validate_schema(normalized, kind)
def test_validate_schema_raises_for_missing_columns() -> None:
"""Schema validation fails fast on missing required columns."""
with pytest.raises(Mt5SchemaError, match="missing required columns"):
validate_schema(pd.DataFrame({"time": [1]}), DataKind.rates)
def test_history_dedup_keys_match_schema_contract() -> None:
"""SQLite history dedup keys stay aligned with schema contracts."""
assert DEDUP_KEYS[DataKind.rates][0] == ("symbol", "timeframe", "time")
assert DEDUP_KEYS[DataKind.ticks][0] == ("symbol", "time_msc")
assert Dataset.rates.table_name == "rates"
@pytest.mark.parametrize(
("raw", "expected"),
[
(" eurusd ", "eurusd"),
("GbpJpy", "GbpJpy"),
("XAUUSDm", "XAUUSDm"),
("US500.cash", "US500.cash"),
("EURUSD.r", "EURUSD.r"),
],
)
def test_normalize_symbol(raw: str, expected: str) -> None:
"""Symbol normalization trims whitespace and preserves broker casing."""
assert normalize_symbol(raw) == expected
def test_normalize_symbols_deduplicates() -> None:
"""Symbol lists are normalized and de-duplicated in order."""
assert normalize_symbols(["XAUUSDm", " XAUUSDm ", "EURUSD.r", "eurusd"]) == [
"XAUUSDm",
"EURUSD.r",
"eurusd",
]
def test_parse_date_range_rejects_inverted_bounds() -> None:
"""Date ranges must not be inverted."""
with pytest.raises(ValueError, match="must not be after"):
parse_date_range("2024-02-01", "2024-01-01")
def test_recent_window_builds_trailing_bounds() -> None:
"""Recent windows end at the provided timestamp."""
end = datetime(2024, 1, 2, tzinfo=UTC)
start, resolved_end = recent_window(hours=24, date_to=end)
assert resolved_end == end
assert start < end
def test_granularity_name_maps_timeframe_alias() -> None:
"""Granularity labels resolve MT5 timeframe aliases."""
assert granularity_name("M1") == "M1"
@pytest.mark.parametrize(
"exc",
[Mt5RuntimeError("init failed"), Mt5TradingError("trade failed")],
)
def test_is_recoverable_mt5_error(exc: Exception) -> None:
"""Recoverable MT5 errors are classified consistently."""
assert is_recoverable_mt5_error(exc)
@pytest.mark.parametrize(
("exc", "expected_type"),
[
(Mt5RuntimeError("x"), Mt5ConnectionError),
(Mt5TradingError("x"), Mt5OperationError),
],
)
def test_normalize_mt5_exception_maps_types(
exc: Exception,
expected_type: type[Mt5ConnectionError | Mt5OperationError],
) -> None:
"""MT5 exceptions map to stable mt5cli types."""
assert isinstance(normalize_mt5_exception(exc), expected_type)
def test_call_with_normalized_errors_reraises_mapped_type() -> None:
"""Normalized error helper re-raises mapped mt5cli exceptions."""
def _raise() -> None:
message = "boom"
raise Mt5RuntimeError(message)
with pytest.raises(Mt5ConnectionError):
call_with_normalized_errors(_raise)
def test_retry_with_backoff_retries_recoverable_errors(
mocker: MockerFixture,
) -> None:
"""Retry helper retries recoverable MT5 failures."""
calls = {"count": 0}
def _flaky() -> str:
calls["count"] += 1
if calls["count"] == 1:
message = "transient"
raise Mt5RuntimeError(message)
return "ok"
mocker.patch("mt5cli.retry.time.sleep")
assert retry_with_backoff(_flaky, retry_count=1) == "ok"
assert calls["count"] == 2
def test_public_api_exports_mt5_client() -> None:
"""MT5Client is the primary importable client abstraction."""
client = MT5Client(config=build_config())
assert isinstance(client, MT5Client)
assert isinstance(client, MT5Client.__mro__[1])
def test_mt5_client_order_primitives_use_connected_client(
mock_client: object,
) -> None:
"""Order check/send route through the same client fetch path as exports."""
request = {"action": 1}
client = MT5Client()
client.order_check(request)
client.order_send(request)
assert mock_client.order_check_as_df.call_count == 1 # type: ignore[attr-defined]
assert mock_client.order_send_as_df.call_count == 1 # type: ignore[attr-defined]
def test_storage_export_round_trip_csv(tmp_path: Path) -> None:
"""Storage helpers export normalized rate frames to CSV."""
frame = normalize_dataframe(
_sample_frame(DataKind.rates),
DataKind.rates,
symbol="EURUSD",
timeframe="M1",
)
output = tmp_path / "rates.csv"
export_dataframe(frame, output, detect_format(output))
loaded = pd.read_csv(output)
assert len(loaded) == 1
assert "close" in loaded.columns
def test_normalize_symbol_rejects_empty_value() -> None:
"""Empty symbols are rejected after trimming."""
with pytest.raises(ValueError, match="must not be empty"):
normalize_symbol(" ")
def test_ensure_utc_handles_naive_and_aware_datetimes() -> None:
"""UTC coercion accepts naive and timezone-aware datetimes."""
naive = datetime(2024, 1, 1, tzinfo=UTC).replace(tzinfo=None)
aware = datetime(2024, 1, 1, tzinfo=UTC)
assert ensure_utc(naive).tzinfo == UTC
assert ensure_utc(aware).tzinfo == UTC
assert ensure_utc("2024-01-01T00:00:00+00:00").tzinfo == UTC
def test_recent_window_validation_errors() -> None:
"""Recent window helpers validate mutually exclusive length arguments."""
with pytest.raises(ValueError, match="exactly one"):
recent_window()
with pytest.raises(ValueError, match="exactly one"):
recent_window(hours=1, seconds=1)
with pytest.raises(ValueError, match="positive"):
recent_window(hours=0)
def test_recent_window_supports_seconds_argument() -> None:
"""Recent windows can be built from a seconds-based length."""
end = datetime(2024, 1, 2, tzinfo=UTC)
start, resolved_end = recent_window(seconds=3600, date_to=end)
assert resolved_end == end
assert start < end
def test_parse_date_range_returns_ordered_bounds() -> None:
"""Valid date ranges return UTC-aware bounds."""
start, end = parse_date_range("2024-01-01", "2024-02-01")
assert start < end
def test_granularity_name_falls_back_for_unknown_timeframe(
mocker: MockerFixture,
) -> None:
"""Unknown timeframe integers stringify as granularity labels."""
mocker.patch(
"mt5cli.converters._get_timeframe_name",
side_effect=ValueError("unknown"),
)
assert granularity_name(1) == "1"
def test_normalize_mt5_exception_passthrough_and_generic() -> None:
"""Normalization preserves mt5cli errors and wraps unknown exceptions."""
original = Mt5CliError("known")
assert normalize_mt5_exception(original) is original
assert isinstance(normalize_mt5_exception(ValueError("x")), Mt5CliError)
def test_schema_columns_and_extra_required_validation() -> None:
"""Schema helpers expose contracts and honor extra required columns."""
assert schema_columns(DataKind.rates) == REQUIRED_COLUMNS[DataKind.rates]
validate_schema(pd.DataFrame(), DataKind.rates)
frame = _sample_frame(DataKind.rates)
with pytest.raises(Mt5SchemaError, match="storage_symbol"):
validate_schema(frame, DataKind.rates, extra_required=["storage_symbol"])
def test_normalize_dataframe_empty_and_tick_sort_paths() -> None:
"""Normalization handles empty frames and tick time_msc sorting."""
empty = pd.DataFrame()
assert normalize_dataframe(empty, DataKind.rates).empty
ticks = _sample_frame(DataKind.ticks)
ticks = pd.concat([ticks, ticks], ignore_index=True)
sorted_ticks = normalize_dataframe(ticks, DataKind.ticks, sort=True)
assert len(sorted_ticks) == 2
unsorted_ticks = normalize_dataframe(ticks, DataKind.ticks, sort=False)
assert len(unsorted_ticks) == 2
def test_normalize_dataframe_rate_timeframe_without_symbol() -> None:
"""Rate normalization can inject timeframe without symbol metadata."""
frame = _sample_frame(DataKind.rates)
normalized = normalize_dataframe(frame, DataKind.rates, timeframe="M1")
assert "timeframe" in normalized.columns
def test_normalize_dataframe_keeps_existing_symbol_and_timeframe() -> None:
"""Normalization does not duplicate existing storage metadata columns."""
frame = normalize_dataframe(
_sample_frame(DataKind.rates),
DataKind.rates,
symbol="EURUSD",
timeframe="M1",
)
normalized = normalize_dataframe(
frame,
DataKind.rates,
symbol="GBPUSD",
timeframe="H1",
)
assert normalized.loc[0, "symbol"] == "EURUSD"
assert normalized.loc[0, "timeframe"] == 1
def test_normalize_time_columns_skips_absent_time_fields() -> None:
"""Time normalization ignores absent optional time columns."""
frame = pd.DataFrame({"open": [1.0]})
result = normalize_time_columns(frame, DataKind.rates)
assert list(result.columns) == ["open"]
@pytest.mark.parametrize(
("col", "value", "kind"),
[
("time", 1704067200, DataKind.rates),
("time_msc", 1704067200000, DataKind.ticks),
("time", datetime(2024, 1, 1, tzinfo=UTC), DataKind.rates),
("time", "2024-01-01T00:00:00+00:00", DataKind.rates),
],
)
def test_normalize_time_columns_coerces_value(
col: str,
value: object,
kind: DataKind,
) -> None:
"""Time column values are coerced to UTC timestamps regardless of input type."""
frame = pd.DataFrame({col: [value]})
result = normalize_time_columns(frame, kind)
assert result.loc[0, col] == pd.Timestamp("2024-01-01T00:00:00+00:00")
def test_normalize_time_columns_handles_optional_order_times() -> None:
"""Optional order/history time columns are normalized when present."""
frame = pd.DataFrame({
"time_setup": [1704067200],
"time_setup_msc": [1704067200000],
"time_done": [1704153600],
"time_done_msc": [1704153600000],
})
result = normalize_time_columns(frame, DataKind.orders)
assert result.loc[0, "time_setup"] == pd.Timestamp("2024-01-01T00:00:00+00:00")
assert result.loc[0, "time_setup_msc"] == pd.Timestamp(
"2024-01-01T00:00:00+00:00",
)
assert result.loc[0, "time_done"] == pd.Timestamp("2024-01-02T00:00:00+00:00")
assert result.loc[0, "time_done_msc"] == pd.Timestamp(
"2024-01-02T00:00:00+00:00",
)
def test_time_columns_include_optional_order_fields() -> None:
"""Schema contracts document optional MT5 time columns per dataset kind."""
assert "time_done" in TIME_COLUMNS[DataKind.orders]
assert "time_setup_msc" in TIME_COLUMNS[DataKind.history_orders]
def test_normalize_dataframe_sorts_ticks_by_time_msc(
mocker: MockerFixture,
) -> None:
"""Tick frames without ``time`` can still sort on ``time_msc``."""
mocker.patch("mt5cli.schemas.validate_schema")
ticks = pd.concat([_sample_frame(DataKind.ticks)] * 2, ignore_index=True).drop(
columns=["time"],
)
ticks.loc[0, "time_msc"] = datetime(2024, 1, 1, tzinfo=UTC)
ticks.loc[1, "time_msc"] = datetime(2024, 1, 2, tzinfo=UTC)
ticks = pd.concat([ticks.iloc[[1]], ticks.iloc[[0]]], ignore_index=True)
normalized = normalize_dataframe(ticks, DataKind.ticks, sort=True)
assert normalized.iloc[0]["time_msc"] <= normalized.iloc[1]["time_msc"]
def test_ensure_utc_columns_skips_missing_columns() -> None:
"""UTC column coercion ignores absent columns."""
frame = _sample_frame(DataKind.rates)
result = ensure_utc_columns(frame, ["time", "missing"])
assert "time" in result.columns
def test_ensure_utc_columns_coerces_non_mt5_columns() -> None:
"""Non-MT5 columns still coerce to UTC datetimes."""
frame = pd.DataFrame({"created_at": ["2024-01-01T00:00:00+00:00"]})
result = ensure_utc_columns(frame, ["created_at"])
assert result.loc[0, "created_at"] == pd.Timestamp("2024-01-01T00:00:00+00:00")
def test_mt5_session_yields_connected_client(mocker: MockerFixture) -> None:
"""Public mt5_session yields an MT5Client bound to a connected session."""
connected = mocker.MagicMock()
context = mocker.MagicMock()
context.__enter__.return_value = connected
context.__exit__.return_value = False
mocker.patch("mt5cli.client.connected_client", return_value=context)
with mt5_session(build_config()) as client:
assert isinstance(client, MT5Client)
def test_retry_with_backoff_reraises_non_recoverable_errors() -> None:
"""Non-MT5 errors are not retried."""
def _raise() -> None:
message = "fatal"
raise ValueError(message)
with pytest.raises(ValueError, match="fatal"):
retry_with_backoff(_raise, retry_count=2)
def test_storage_export_round_trip_sqlite(tmp_path: Path) -> None:
"""Storage helpers append deduplicated frames to SQLite."""
frame = normalize_dataframe(
_sample_frame(DataKind.rates),
DataKind.rates,
symbol="EURUSD",
timeframe="M1",
)
output = tmp_path / "rates.db"
export_dataframe_to_sqlite(
frame,
output,
"rates",
deduplicate_on=DEDUP_KEYS[DataKind.rates][0],
)
with __import__("sqlite3").connect(output) as conn:
count = conn.execute("SELECT COUNT(*) FROM rates").fetchone()[0]
assert count == 1
def test_storage_module_does_not_exist() -> None:
"""mt5cli.storage re-export module has been removed."""
with pytest.raises(ModuleNotFoundError):
importlib.import_module("mt5cli.storage")
class TestStableSdkContract:
"""Tests for the documented stable downstream SDK contract."""
def test_stable_exports_are_subset_of_all(self) -> None:
"""Every stable export is also listed in the package __all__."""
missing = sorted(STABLE_SDK_EXPORTS - set(mt5cli.__all__))
assert not missing, f"STABLE_SDK_EXPORTS missing from __all__: {missing}"
def test_stable_exports_cover_root_api(self) -> None:
"""STABLE_SDK_EXPORTS classifies every package-root symbol."""
tier_metadata = {"STABLE_SDK_EXPORTS"}
root_exports = set(mt5cli.__all__)
missing_from_root = sorted(STABLE_SDK_EXPORTS - root_exports)
assert not missing_from_root, (
f"STABLE_SDK_EXPORTS missing from __all__: {missing_from_root}"
)
unclassified = sorted(root_exports - STABLE_SDK_EXPORTS - tier_metadata)
assert not unclassified, (
f"Root exports not in STABLE_SDK_EXPORTS: {unclassified}"
)
@pytest.mark.parametrize("name", sorted(STABLE_SDK_EXPORTS))
def test_stable_exports_are_importable_from_package_root(self, name: str) -> None:
"""Stable SDK names resolve through ``from mt5cli import ...``."""
assert hasattr(mt5cli, name), f"{name!r} missing from mt5cli package root"
def test_drop_forming_rate_bar_from_package_root(self) -> None:
"""Closed-bar trimming is available from the stable package surface."""
frame = pd.DataFrame({"time": [1, 2, 3], "close": [1.0, 1.1, 1.2]})
closed = drop_forming_rate_bar(frame)
assert list(closed["close"]) == [1.0, 1.1]
assert len(closed) == 2
def test_fetch_latest_closed_rates_from_package_root(self) -> None:
"""Single-client closed-bar helper drops the forming row."""
client = MagicMock()
client.latest_rates.return_value = pd.DataFrame(
{"time": [1, 2, 3], "close": [1.0, 1.1, 1.2]},
)
result = fetch_latest_closed_rates(
client,
symbol="EURUSD",
granularity="M1",
count=2,
)
client.latest_rates.assert_called_once_with("EURUSD", "M1", 3, start_pos=0)
assert list(result["close"]) == [1.0, 1.1]
def test_fetch_latest_closed_rates_for_trading_client_from_package_root(
self,
) -> None:
"""Trading-client closed-bar helper is importable from the stable surface."""
client = MagicMock()
client.fetch_latest_rates_as_df.return_value = pd.DataFrame(
{"time": [1, 2, 3], "close": [1.0, 1.1, 1.2]},
)
result = fetch_latest_closed_rates_for_trading_client(
client,
symbol="EURUSD",
granularity="M1",
count=2,
)
assert list(result["close"]) == [1.0, 1.1]
def test_normalize_order_volume_from_package_root(self) -> None:
"""Volume normalization helper is importable from the stable surface."""
result = normalize_order_volume(
0.25,
volume_min=0.1,
volume_max=1.0,
volume_step=0.1,
)
assert abs(result - 0.2) < 1e-9
def test_calculate_positions_margin_from_package_root(self) -> None:
"""Position margin helper is importable from the stable surface."""
client = MagicMock()
client.mt5.POSITION_TYPE_BUY = 0
client.mt5.POSITION_TYPE_SELL = 1
client.mt5.ORDER_TYPE_BUY = 10
client.mt5.ORDER_TYPE_SELL = 11
client.positions_get_as_df.return_value = pd.DataFrame()
assert calculate_positions_margin(client) == 0
def test_generic_trading_helpers_from_package_root(self) -> None:
"""New generic trading helpers resolve through the stable surface."""
price = extract_tick_price({"bid": "1.2"}, "bid")
assert price is not None
assert abs(price - 1.2) < 1e-9
assert callable(calculate_trailing_stop_updates)
assert callable(calculate_account_projected_margin_ratio)
assert callable(calculate_projected_margin_ratio)
assert callable(calculate_symbol_group_margin_ratio)
def test_load_rate_series_from_sqlite_requires_managed_views(
self,
tmp_path: Path,
) -> None:
"""Multi-series loading fails clearly when managed views are absent."""
db_path = tmp_path / "empty-views.db"
with sqlite3.connect(db_path) as conn:
conn.execute(
"CREATE TABLE rates("
" symbol TEXT, timeframe INTEGER, time TEXT, close REAL)",
)
targets = build_rate_targets(["EURUSD"], ["M1"])
with pytest.raises(ValueError, match="No rate compatibility view exists"):
load_rate_series_from_sqlite(db_path, targets, count=10)
assert targets == [RateTarget(symbol="EURUSD", timeframe=1)]
def test_resolve_account_spec_from_package_root(
self,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Account credential resolution uses generic ${ENV_VAR} placeholders."""
monkeypatch.setenv("APP_MT5_LOGIN", "555")
monkeypatch.setenv("APP_MT5_PASSWORD", "secret")
account = AccountSpec(
symbols=["EURUSD"],
login="${APP_MT5_LOGIN}",
password="${APP_MT5_PASSWORD}",
server="Broker-Demo",
)
resolved = resolve_account_spec(account, timeout=3000)
assert resolved.login == "555"
assert resolved.password == "secret" # noqa: S105
assert resolved.timeout == 3000
batch = resolve_account_specs([account], server="Override")
assert batch[0].server == "Override"
def test_mt5_trading_session_lifecycle_from_package_root(
self,
mocker: MockerFixture,
) -> None:
"""Trading session helper initializes and always shuts down."""
mock_client = MagicMock()
mocker.patch(
"mt5cli.trading.Mt5DataClient",
return_value=mock_client,
)
with mt5_trading_session(login=12345, server="Broker-Demo") as client:
assert client is mock_client
mock_client.initialize_and_login_mt5.assert_called_once()
mock_client.shutdown.assert_called_once()
def test_trading_order_helpers_importable_from_package_root(self) -> None:
"""Order planning helpers resolve through the stable package surface."""
assert callable(calculate_margin_and_volume)
assert callable(ensure_symbol_selected)
assert callable(place_market_order)
margin_hints = get_type_hints(MarginVolume)
limits_hints = get_type_hints(OrderLimits)
execution_hints = get_type_hints(OrderExecutionResult)
assert margin_hints["buy_volume"] is float
assert limits_hints["stop_loss"] == float | None
assert execution_hints["status"] == ExecutionStatus
def test_mt5_trading_session_shuts_down_on_exception(
self,
mocker: MockerFixture,
) -> None:
"""Trading session helper shuts down even when the body raises."""
mock_client = MagicMock()
mocker.patch(
"mt5cli.trading.Mt5DataClient",
return_value=mock_client,
)
message = "strategy error"
with (
pytest.raises(RuntimeError, match=message),
mt5_trading_session(login=12345, server="Broker-Demo"),
):
raise RuntimeError(message)
mock_client.shutdown.assert_called_once()
def test_fetch_latest_closed_rates_indexed_from_package_root(
self,
mocker: MockerFixture,
) -> None:
"""Indexed closed-bar helper returns a UTC DatetimeIndex named 'time'."""
client = MagicMock()
mocker.patch(
"mt5cli.trading.fetch_latest_closed_rates_for_trading_client",
return_value=pd.DataFrame(
{
"time": [1704067200, 1704153600, 1704240000],
"close": [1.0, 1.1, 1.2],
},
),
)
result = fetch_latest_closed_rates_indexed(
client,
symbol="EURUSD",
granularity="M1",
count=2,
)
assert isinstance(result.index, pd.DatetimeIndex)
assert result.index.name == "time"
assert result.index.tz is not None
assert "time" not in result.columns
assert "close" in result.columns
def test_rate_view_helpers_in_history_module(self, tmp_path: Path) -> None:
"""Rate view helpers are available from mt5cli.history."""
db_path = tmp_path / "rates.db"
with sqlite3.connect(db_path) as conn:
conn.execute(
"CREATE TABLE rates("
" symbol TEXT, timeframe INTEGER, time TEXT, close REAL)",
)
conn.execute(
"INSERT INTO rates(symbol, timeframe, time, close) VALUES (?, ?, ?, ?)",
("EURUSD", 1, "2024-01-01T00:00:00+00:00", 1.0),
)
create_rate_compatibility_views(conn)
assert resolve_rate_view_name(db_path, "EURUSD", "M1") == "rate_EURUSD__1"
missing = tmp_path / "missing.db"
with pytest.raises(ValueError, match="SQLite database not found"):
resolve_rate_view_name(missing, "EURUSD", "M1", require_existing=True)
def test_load_rate_data_in_history_module(self, tmp_path: Path) -> None:
"""SQLite rate loading normalizes timestamps through mt5cli.history."""
db_path = tmp_path / "view.db"
with sqlite3.connect(db_path) as conn:
conn.execute(
'CREATE VIEW "rate_EURUSD__1" AS'
" SELECT '2024-01-01T00:00:00+00:00' AS time, 1.1 AS close",
)
frame = load_rate_data(db_path, "rate_EURUSD__1")
assert frame.index.name == "time"
assert abs(float(frame.iloc[0]["close"]) - 1.1) < 1e-9
@pytest.mark.parametrize(
"name",
[
"Mt5Config",
"Mt5RuntimeError",
"Mt5TradingClient",
"Mt5TradingError",
"TICK_FLAG_MAP",
"TIMEFRAME_MAP",
],
)
def test_pdmt5_pass_through_names_removed_from_public_contract(name: str) -> None:
"""Removed pdmt5 pass-through names are not part of the public contract."""
assert name not in STABLE_SDK_EXPORTS, (
f"{name!r} should not be in STABLE_SDK_EXPORTS"
)
assert name not in mt5cli.__all__, f"{name!r} should not be in mt5cli.__all__"
def test_mt5cli_does_not_import_high_level_trading_symbols() -> None:
"""mt5cli doesn't import Mt5TradingClient or Mt5TradingError at module level."""
trading_module = importlib.import_module("mt5cli.trading")
module_dict = vars(trading_module)
assert "Mt5TradingClient" not in module_dict, (
"mt5cli.trading should not import Mt5TradingClient at module level"
)
assert "Mt5TradingError" not in module_dict, (
"mt5cli.trading should not import Mt5TradingError at module level"
)
# ---------------------------------------------------------------------------
# Packaging metadata
# ---------------------------------------------------------------------------
def test_parquet_extra_declares_pyarrow() -> None:
"""Package metadata lists pyarrow under the parquet optional extra."""
reqs = requires("mt5cli") or []
parquet_reqs = [r for r in reqs if "pyarrow" in r and "parquet" in r]
assert parquet_reqs, "pyarrow not found in parquet optional extra"
def test_pyarrow_not_in_core_dependencies() -> None:
"""Pyarrow is not a core dependency; it belongs only in the parquet extra."""
reqs = requires("mt5cli") or []
core_reqs = [r for r in reqs if "extra ==" not in r]
assert not any("pyarrow" in r for r in core_reqs), (
"pyarrow should not appear in core dependencies"
)
+75
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@@ -0,0 +1,75 @@
"""Tests for example files in examples/grafana/."""
from __future__ import annotations
import json
from pathlib import Path
_EXAMPLES_DIR = Path(__file__).parent.parent / "examples" / "grafana"
_DASHBOARDS_DIR = _EXAMPLES_DIR / "dashboards"
class TestGrafanaExamples:
"""Validate structure and content of bundled Grafana example files."""
def test_dashboard_json_files_are_valid_json(self) -> None:
"""All dashboard JSON files parse without error."""
paths = list(_DASHBOARDS_DIR.glob("*.json"))
assert paths, "No dashboard JSON files found"
for path in paths:
content = path.read_text(encoding="utf-8")
obj = json.loads(content)
assert isinstance(obj, dict), f"{path.name} root must be a JSON object"
def test_dashboard_json_has_no_private_placeholders(self) -> None:
"""Dashboard JSON files contain no obvious credential placeholders."""
private_patterns = ["password", "api_key", "apikey"]
for path in _DASHBOARDS_DIR.glob("*.json"):
content = path.read_text(encoding="utf-8").lower()
for pat in private_patterns:
assert pat not in content, f"{path.name} contains {pat!r}"
def test_dashboard_json_uses_grafana_views(self) -> None:
"""All dashboard JSON files query grafana_* views."""
for path in _DASHBOARDS_DIR.glob("*.json"):
content = path.read_text(encoding="utf-8")
assert "grafana_" in content, (
f"{path.name} must contain queries against grafana_* views"
)
def test_dashboard_json_has_uid(self) -> None:
"""All dashboard JSON files have a non-empty uid field."""
for path in _DASHBOARDS_DIR.glob("*.json"):
obj = json.loads(path.read_text(encoding="utf-8"))
assert obj.get("uid"), f"{path.name} must have a uid"
def test_dashboard_json_has_title(self) -> None:
"""All dashboard JSON files have a non-empty title field."""
for path in _DASHBOARDS_DIR.glob("*.json"):
obj = json.loads(path.read_text(encoding="utf-8"))
assert obj.get("title"), f"{path.name} must have a title"
def test_expected_dashboards_present(self) -> None:
"""The three expected dashboard files are present."""
names = {p.name for p in _DASHBOARDS_DIR.glob("*.json")}
assert "mt5cli-overview.json" in names
assert "mt5cli-trades.json" in names
assert "mt5cli-market.json" in names
def test_readme_exists(self) -> None:
"""examples/grafana/README.md is present."""
assert (_EXAMPLES_DIR / "README.md").is_file()
def test_compose_file_exists(self) -> None:
"""examples/grafana/compose.yml is present."""
assert (_EXAMPLES_DIR / "compose.yml").is_file()
def test_datasource_provisioning_exists(self) -> None:
"""Datasource provisioning YAML is present."""
assert (
_EXAMPLES_DIR / "provisioning" / "datasources" / "mt5cli-sqlite.yml"
).is_file()
def test_dashboard_provisioning_exists(self) -> None:
"""Dashboard provisioning YAML is present."""
assert (_EXAMPLES_DIR / "provisioning" / "dashboards" / "mt5cli.yml").is_file()
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"""Tests for mt5cli.grafana module."""
from __future__ import annotations
import logging
import sqlite3
from pathlib import Path
from typing import TYPE_CHECKING
from unittest.mock import MagicMock, patch
import pandas as pd
import pytest
if TYPE_CHECKING:
from collections.abc import Iterator
from mt5cli.grafana import (
_build_snapshot_view, # type: ignore[reportPrivateUsage]
_create_view_safe, # type: ignore[reportPrivateUsage]
create_grafana_indexes,
create_grafana_views,
create_snapshot_tables,
ensure_grafana_schema,
insert_account_snapshot,
insert_order_snapshots,
insert_position_snapshots,
insert_terminal_snapshot,
publish_grafana_copy,
record_snapshot_run,
start_snapshot_run,
)
@pytest.fixture
def conn() -> Iterator[sqlite3.Connection]:
"""Yield an in-memory SQLite connection for each test."""
with sqlite3.connect(":memory:") as c:
yield c
def _get_names(conn: sqlite3.Connection, type_: str) -> set[str]:
return {
row[0]
for row in conn.execute(
"SELECT name FROM sqlite_master WHERE type=?",
(type_,),
).fetchall()
}
def _make_rates_table(conn: sqlite3.Connection) -> None:
conn.execute(
"CREATE TABLE rates"
" (time TEXT, symbol TEXT, timeframe INTEGER,"
" open REAL, high REAL, low REAL, close REAL)"
)
def _make_ticks_table(conn: sqlite3.Connection) -> None:
conn.execute("CREATE TABLE ticks (time TEXT, symbol TEXT, bid REAL, ask REAL)")
def _make_history_deals_full(conn: sqlite3.Connection) -> None:
conn.execute(
"CREATE TABLE history_deals"
" (time TEXT, symbol TEXT, profit REAL, type INTEGER,"
" entry INTEGER, volume REAL, price REAL, ticket INTEGER, position_id INTEGER)"
)
def _make_history_deals_minimal(conn: sqlite3.Connection) -> None:
"""history_deals with only time, type, symbol, profit — no entry/volume/price."""
conn.execute(
"CREATE TABLE history_deals (time TEXT, symbol TEXT, profit REAL, type INTEGER)"
)
def _make_history_orders_table(conn: sqlite3.Connection) -> None:
conn.execute(
"CREATE TABLE history_orders"
" (time_setup TEXT, symbol TEXT, ticket INTEGER, type INTEGER)"
)
# ---------------------------------------------------------------------------
# TestSnapshotTables
# ---------------------------------------------------------------------------
class TestSnapshotTables:
"""Tests for create_snapshot_tables."""
def test_creates_all_five_tables(self, conn: sqlite3.Connection) -> None:
"""All five snapshot tables are created."""
create_snapshot_tables(conn)
tables = _get_names(conn, "table")
assert "snapshot_runs" in tables
assert "account_snapshots" in tables
assert "position_snapshots" in tables
assert "order_snapshots" in tables
assert "terminal_snapshots" in tables
def test_is_idempotent(self, conn: sqlite3.Connection) -> None:
"""Calling create_snapshot_tables twice does not raise."""
create_snapshot_tables(conn)
create_snapshot_tables(conn)
tables = _get_names(conn, "table")
assert "snapshot_runs" in tables
# ---------------------------------------------------------------------------
# TestCreateViewSafe
# ---------------------------------------------------------------------------
class TestCreateViewSafe:
"""Tests for _create_view_safe."""
def test_creates_view_successfully(self, conn: sqlite3.Connection) -> None:
"""A valid select SQL creates the named view."""
_create_view_safe(conn, "test_view", "SELECT 1 AS val")
views = _get_names(conn, "view")
assert "test_view" in views
def test_replaces_existing_view(self, conn: sqlite3.Connection) -> None:
"""Calling again with a new SQL replaces the existing view."""
_create_view_safe(conn, "test_view", "SELECT 1 AS val")
_create_view_safe(conn, "test_view", "SELECT 2 AS val")
result = conn.execute("SELECT val FROM test_view").fetchone()
assert result == (2,)
def test_logs_warning_on_sqlite_error(
self,
caplog: pytest.LogCaptureFixture,
) -> None:
"""sqlite3.Error during CREATE VIEW logs a warning instead of raising."""
mock_conn = MagicMock()
mock_conn.execute.side_effect = [
None,
sqlite3.OperationalError("parse error"),
]
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
_create_view_safe(mock_conn, "bad_view", "SELECT 1")
assert "Skipping view bad_view" in caplog.text
assert "parse error" in caplog.text
# ---------------------------------------------------------------------------
# TestGrafanaViews
# ---------------------------------------------------------------------------
class TestGrafanaViews:
"""Tests for create_grafana_views and individual view builders."""
def test_all_views_created_with_full_schema(
self,
conn: sqlite3.Connection,
) -> None:
"""All 13 Grafana views are created when all source tables are present."""
_make_rates_table(conn)
_make_ticks_table(conn)
_make_history_deals_full(conn)
_make_history_orders_table(conn)
create_snapshot_tables(conn)
create_grafana_views(conn)
views = _get_names(conn, "view")
expected = {
"grafana_rates",
"grafana_ticks",
"grafana_history_deals",
"grafana_history_orders",
"grafana_trade_deals",
"grafana_cash_events",
"grafana_realized_pnl",
"grafana_symbol_pnl",
"grafana_trade_stats",
"grafana_account_snapshots",
"grafana_position_snapshots",
"grafana_order_snapshots",
"grafana_terminal_snapshots",
}
assert expected.issubset(views)
def test_stale_view_dropped_when_source_table_disappears(
self,
conn: sqlite3.Connection,
) -> None:
"""create_grafana_views drops a previously created view whose source is gone."""
_make_ticks_table(conn)
create_grafana_views(conn)
assert "grafana_ticks" in _get_names(conn, "view")
conn.execute("DROP TABLE ticks")
create_grafana_views(conn)
assert "grafana_ticks" not in _get_names(conn, "view")
def test_grafana_rates_skipped_when_table_absent(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_rates is skipped when rates table is missing."""
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_rates" not in _get_names(conn, "view")
def test_grafana_rates_skipped_when_required_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_rates is skipped when rates table lacks required columns."""
conn.execute("CREATE TABLE rates (open REAL)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_rates" not in _get_names(conn, "view")
assert "Skipping grafana_rates" in caplog.text
def test_grafana_ticks_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_ticks is skipped when ticks table lacks required columns."""
conn.execute("CREATE TABLE ticks (bid REAL)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_ticks" not in _get_names(conn, "view")
assert "Skipping grafana_ticks" in caplog.text
def test_grafana_history_deals_skipped_when_time_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_history_deals is skipped when history_deals.time is missing."""
conn.execute("CREATE TABLE history_deals (symbol TEXT)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_history_deals" not in _get_names(conn, "view")
assert "Skipping grafana_history_deals" in caplog.text
def test_grafana_history_orders_skipped_when_time_setup_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_history_orders is skipped when time_setup is absent."""
conn.execute("CREATE TABLE history_orders (symbol TEXT)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_history_orders" not in _get_names(conn, "view")
assert "Skipping grafana_history_orders" in caplog.text
def test_grafana_trade_deals_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_trade_deals is skipped when history_deals missing time/type."""
conn.execute("CREATE TABLE history_deals (symbol TEXT)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_trade_deals" not in _get_names(conn, "view")
def test_grafana_cash_events_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_cash_events is skipped when history_deals missing time/type."""
conn.execute("CREATE TABLE history_deals (symbol TEXT)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_cash_events" not in _get_names(conn, "view")
def test_grafana_realized_pnl_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_realized_pnl is skipped when history_deals missing required cols."""
conn.execute("CREATE TABLE history_deals (time TEXT, type INTEGER)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_realized_pnl" not in _get_names(conn, "view")
assert "Skipping grafana_realized_pnl" in caplog.text
def test_grafana_realized_pnl_skipped_when_entry_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_realized_pnl is skipped when entry column is absent."""
_make_history_deals_minimal(conn)
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_realized_pnl" not in _get_names(conn, "view")
assert "Skipping grafana_realized_pnl" in caplog.text
def test_grafana_symbol_pnl_skipped_when_required_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_symbol_pnl is skipped when required columns are absent."""
conn.execute("CREATE TABLE history_deals (time TEXT, type INTEGER)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_symbol_pnl" not in _get_names(conn, "view")
assert "Skipping grafana_symbol_pnl" in caplog.text
def test_grafana_symbol_pnl_without_volume_and_price(
self,
conn: sqlite3.Connection,
) -> None:
"""grafana_symbol_pnl is created with only required columns."""
conn.execute(
"CREATE TABLE history_deals"
" (time TEXT, symbol TEXT, profit REAL, type INTEGER, entry INTEGER)"
)
create_grafana_views(conn)
assert "grafana_symbol_pnl" in _get_names(conn, "view")
def test_grafana_symbol_pnl_with_volume_and_price(
self,
conn: sqlite3.Connection,
) -> None:
"""grafana_symbol_pnl includes volume and price columns when present."""
_make_history_deals_full(conn)
create_grafana_views(conn)
assert "grafana_symbol_pnl" in _get_names(conn, "view")
# View columns include volume and price
cols = {row[1] for row in conn.execute("PRAGMA table_info(grafana_symbol_pnl)")}
assert "volume" in cols
assert "price" in cols
def test_grafana_trade_stats_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""grafana_trade_stats is skipped when history_deals missing required cols."""
conn.execute("CREATE TABLE history_deals (time TEXT)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
assert "grafana_trade_stats" not in _get_names(conn, "view")
assert "Skipping grafana_trade_stats" in caplog.text
def test_grafana_trade_stats_without_entry_col(
self,
conn: sqlite3.Connection,
) -> None:
"""grafana_trade_stats is a static summary view with no time column."""
_make_history_deals_minimal(conn)
create_grafana_views(conn)
assert "grafana_trade_stats" in _get_names(conn, "view")
cols = {
row[1] for row in conn.execute("PRAGMA table_info(grafana_trade_stats)")
}
assert "time" not in cols
assert "symbol" in cols
def test_grafana_trade_stats_with_entry_col(
self,
conn: sqlite3.Connection,
) -> None:
"""grafana_trade_stats is a static summary view with no time column."""
_make_history_deals_full(conn)
create_grafana_views(conn)
assert "grafana_trade_stats" in _get_names(conn, "view")
cols = {
row[1] for row in conn.execute("PRAGMA table_info(grafana_trade_stats)")
}
assert "time" not in cols
assert "symbol" in cols
def test_snapshot_views_skipped_when_snapshot_tables_absent(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""Snapshot views are skipped when snapshot tables are not created."""
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
create_grafana_views(conn)
views = _get_names(conn, "view")
assert "grafana_account_snapshots" not in views
assert "grafana_position_snapshots" not in views
assert "grafana_order_snapshots" not in views
assert "grafana_terminal_snapshots" not in views
def test_build_snapshot_view_with_only_run_id_col(
self,
conn: sqlite3.Connection,
) -> None:
"""_build_snapshot_view exposes time and run_id when table has only run_id."""
create_snapshot_tables(conn)
conn.execute("CREATE TABLE only_run (run_id INTEGER NOT NULL)")
run_id = start_snapshot_run(conn, 1000)
record_snapshot_run(conn, run_id, "ok")
conn.execute("INSERT INTO only_run (run_id) VALUES (?)", (run_id,))
_build_snapshot_view(conn, "test_view", "only_run")
assert "test_view" in _get_names(conn, "view")
cols = {row[1] for row in conn.execute("PRAGMA table_info(test_view)")}
assert "time" in cols
assert "run_id" in cols
def test_build_snapshot_view_skips_when_snapshot_runs_missing(
self,
conn: sqlite3.Connection,
) -> None:
"""_build_snapshot_view skips view when snapshot_runs has wrong columns."""
conn.execute("CREATE TABLE only_run (run_id INTEGER NOT NULL)")
conn.execute("CREATE TABLE snapshot_runs (foo TEXT)")
_build_snapshot_view(conn, "test_view", "only_run")
views = _get_names(conn, "view")
assert "test_view" not in views
def test_build_snapshot_view_skips_when_run_id_col_missing(
self,
conn: sqlite3.Connection,
caplog: pytest.LogCaptureFixture,
) -> None:
"""_build_snapshot_view skips view when the table lacks run_id."""
create_snapshot_tables(conn)
conn.execute("CREATE TABLE no_run_id (symbol TEXT)")
with caplog.at_level(logging.WARNING, logger="mt5cli.grafana"):
_build_snapshot_view(conn, "test_view", "no_run_id")
assert "test_view" not in _get_names(conn, "view")
assert "missing run_id column" in caplog.text
def test_snapshot_view_excludes_failed_run_rows(
self,
conn: sqlite3.Connection,
) -> None:
"""Snapshot views hide rows from failed runs."""
create_snapshot_tables(conn)
run_id = start_snapshot_run(conn, 1000)
conn.execute(
"INSERT INTO account_snapshots"
" (run_id, login, balance, equity, margin, margin_free, profit)"
" VALUES (?, 12345, 10000.0, 9800.0, 200.0, 9600.0, -200.0)",
(run_id,),
)
record_snapshot_run(conn, run_id, "error", "terminal offline")
create_grafana_views(conn)
rows = conn.execute("SELECT * FROM grafana_account_snapshots").fetchall()
assert rows == []
def test_snapshot_view_includes_ok_run_rows(
self,
conn: sqlite3.Connection,
) -> None:
"""Snapshot views show rows from successful runs and expose run_id."""
create_snapshot_tables(conn)
run_id = start_snapshot_run(conn, 2000)
conn.execute(
"INSERT INTO account_snapshots"
" (run_id, login, balance, equity, margin, margin_free, profit)"
" VALUES (?, 12345, 10000.0, 9800.0, 200.0, 9600.0, -200.0)",
(run_id,),
)
record_snapshot_run(conn, run_id, "ok")
create_grafana_views(conn)
rows = conn.execute(
"SELECT time, run_id, login FROM grafana_account_snapshots"
).fetchall()
assert rows == [(2000, run_id, 12345)]
cols = {
row[1]
for row in conn.execute("PRAGMA table_info(grafana_account_snapshots)")
}
assert "run_id" in cols
def test_snapshot_view_same_second_ok_and_error_no_cross_contamination(
self,
conn: sqlite3.Connection,
) -> None:
"""An ok and error run sharing observed_at expose only the ok run's rows."""
create_snapshot_tables(conn)
run_err = start_snapshot_run(conn, 3000)
conn.execute(
"INSERT INTO account_snapshots (run_id, login) VALUES (?, 99)",
(run_err,),
)
record_snapshot_run(conn, run_err, "error")
run_ok = start_snapshot_run(conn, 3000)
conn.execute(
"INSERT INTO account_snapshots (run_id, login) VALUES (?, 12345)",
(run_ok,),
)
record_snapshot_run(conn, run_ok, "ok")
create_grafana_views(conn)
rows = conn.execute("SELECT login FROM grafana_account_snapshots").fetchall()
assert rows == [(12345,)]
def test_snapshot_view_two_ok_runs_same_second_no_duplication(
self,
conn: sqlite3.Connection,
) -> None:
"""Two ok runs sharing observed_at each produce exactly one row in the view."""
create_snapshot_tables(conn)
run1 = start_snapshot_run(conn, 4000)
conn.execute(
"INSERT INTO account_snapshots (run_id, login) VALUES (?, 1)",
(run1,),
)
record_snapshot_run(conn, run1, "ok")
run2 = start_snapshot_run(conn, 4000)
conn.execute(
"INSERT INTO account_snapshots (run_id, login) VALUES (?, 2)",
(run2,),
)
record_snapshot_run(conn, run2, "ok")
create_grafana_views(conn)
rows = conn.execute("SELECT login FROM grafana_account_snapshots").fetchall()
assert len(rows) == 2
# ---------------------------------------------------------------------------
# TestGrafanaIndexes
# ---------------------------------------------------------------------------
class TestGrafanaIndexes:
"""Tests for create_grafana_indexes."""
def test_all_indexes_created_with_full_schema(
self,
conn: sqlite3.Connection,
) -> None:
"""All 9 indexes are created when all source tables are present."""
_make_rates_table(conn)
_make_ticks_table(conn)
_make_history_deals_full(conn)
_make_history_orders_table(conn)
create_snapshot_tables(conn)
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_rates_time_symbol_timeframe" in indexes
assert "idx_ticks_time_symbol" in indexes
assert "idx_history_deals_time_symbol" in indexes
assert "idx_history_deals_symbol_time" in indexes
assert "idx_history_orders_time_setup_symbol" in indexes
assert "idx_account_snapshots_time_login" in indexes
assert "idx_position_snapshots_time_symbol" in indexes
assert "idx_order_snapshots_time_symbol" in indexes
assert "idx_snapshot_runs_time_status" in indexes
def test_no_indexes_created_when_tables_absent(
self,
conn: sqlite3.Connection,
) -> None:
"""No indexes are created when tables are absent."""
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert not any(name.startswith("idx_") for name in indexes)
def test_indexes_for_snapshot_tables_skipped_when_absent(
self,
conn: sqlite3.Connection,
) -> None:
"""Snapshot table indexes are skipped when snapshot tables don't exist."""
_make_history_deals_full(conn)
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_account_snapshots_time_login" not in indexes
assert "idx_position_snapshots_time_symbol" not in indexes
assert "idx_order_snapshots_time_symbol" not in indexes
assert "idx_snapshot_runs_time_status" not in indexes
def test_rates_index_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
) -> None:
"""Rates index is skipped when required columns are absent."""
conn.execute("CREATE TABLE rates (open REAL)")
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_rates_time_symbol_timeframe" not in indexes
def test_ticks_index_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
) -> None:
"""Ticks index is skipped when required columns are absent."""
conn.execute("CREATE TABLE ticks (bid REAL)")
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_ticks_time_symbol" not in indexes
def test_deals_indexes_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
) -> None:
"""history_deals indexes are skipped when required columns are absent."""
conn.execute("CREATE TABLE history_deals (ticket INTEGER)")
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_history_deals_time_symbol" not in indexes
def test_orders_index_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
) -> None:
"""history_orders index is skipped when required columns are absent."""
conn.execute("CREATE TABLE history_orders (ticket INTEGER)")
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_history_orders_time_setup_symbol" not in indexes
def test_snapshot_indexes_skipped_when_cols_missing(
self,
conn: sqlite3.Connection,
) -> None:
"""Snapshot table indexes are skipped when required columns are absent."""
conn.execute("CREATE TABLE account_snapshots (foo TEXT)")
conn.execute("CREATE TABLE position_snapshots (foo TEXT)")
conn.execute("CREATE TABLE order_snapshots (foo TEXT)")
conn.execute("CREATE TABLE snapshot_runs (foo TEXT)")
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_account_snapshots_time_login" not in indexes
assert "idx_position_snapshots_time_symbol" not in indexes
assert "idx_order_snapshots_time_symbol" not in indexes
assert "idx_snapshot_runs_time_status" not in indexes
def test_indexes_are_idempotent(self, conn: sqlite3.Connection) -> None:
"""Creating indexes twice does not raise (IF NOT EXISTS)."""
_make_rates_table(conn)
create_grafana_indexes(conn)
create_grafana_indexes(conn)
indexes = _get_names(conn, "index")
assert "idx_rates_time_symbol_timeframe" in indexes
# ---------------------------------------------------------------------------
# TestEnsureGrafanaSchema
# ---------------------------------------------------------------------------
class TestEnsureGrafanaSchema:
"""Tests for ensure_grafana_schema."""
def test_creates_all_tables_views_and_indexes(
self,
conn: sqlite3.Connection,
) -> None:
"""ensure_grafana_schema creates snapshot tables, views, and indexes."""
_make_rates_table(conn)
_make_history_deals_full(conn)
ensure_grafana_schema(conn)
tables = _get_names(conn, "table")
assert "snapshot_runs" in tables
assert "account_snapshots" in tables
views = _get_names(conn, "view")
assert "grafana_rates" in views
assert "grafana_account_snapshots" in views
indexes = _get_names(conn, "index")
assert "idx_rates_time_symbol_timeframe" in indexes
def test_is_idempotent(self, conn: sqlite3.Connection) -> None:
"""Calling ensure_grafana_schema twice does not raise."""
ensure_grafana_schema(conn)
ensure_grafana_schema(conn)
# ---------------------------------------------------------------------------
# TestSnapshotInserts
# ---------------------------------------------------------------------------
class TestSnapshotInserts:
"""Tests for snapshot insert helpers."""
@pytest.fixture(autouse=True)
def setup_tables(self, conn: sqlite3.Connection) -> None:
"""Create snapshot tables before each insert test."""
create_snapshot_tables(conn)
def test_insert_account_snapshot(self, conn: sqlite3.Connection) -> None:
"""insert_account_snapshot appends a row with correct values."""
run_id = start_snapshot_run(conn, 1700000000)
row: dict[str, object] = {
"login": 12345,
"currency": "USD",
"balance": 10000.0,
"equity": 9800.0,
"margin": 200.0,
"margin_free": 9800.0,
"margin_level": 4900.0,
"profit": -200.0,
"leverage": 100,
}
insert_account_snapshot(conn, run_id, row)
result = conn.execute(
"SELECT login, currency, balance FROM account_snapshots"
).fetchone()
assert result == (12345, "USD", 10000.0)
def test_insert_account_snapshot_partial_row(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_account_snapshot works when some fields are missing (uses None)."""
run_id = start_snapshot_run(conn, 1700000000)
insert_account_snapshot(conn, run_id, {"login": 1})
result = conn.execute(
"SELECT login, currency FROM account_snapshots"
).fetchone()
assert result == (1, None)
def test_insert_position_snapshots_with_rows(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_position_snapshots appends each position row."""
run_id = start_snapshot_run(conn, 1700000000)
rows: list[dict[str, object]] = [
{"ticket": 1, "symbol": "EURUSD", "volume": 0.1, "profit": 10.0},
{"ticket": 2, "symbol": "GBPUSD", "volume": 0.2, "profit": -5.0},
]
insert_position_snapshots(conn, run_id, 12345, rows)
count = conn.execute("SELECT COUNT(*) FROM position_snapshots").fetchone()[0]
assert count == 2
def test_insert_position_snapshots_noop_when_empty(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_position_snapshots is a no-op when rows is empty."""
run_id = start_snapshot_run(conn, 1700000000)
insert_position_snapshots(conn, run_id, 12345, [])
count = conn.execute("SELECT COUNT(*) FROM position_snapshots").fetchone()[0]
assert count == 0
def test_insert_order_snapshots_with_rows(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_order_snapshots appends each order row."""
run_id = start_snapshot_run(conn, 1700000000)
rows: list[dict[str, object]] = [
{"ticket": 10, "symbol": "EURUSD", "type": 2, "volume_current": 0.1},
]
insert_order_snapshots(conn, run_id, 12345, rows)
count = conn.execute("SELECT COUNT(*) FROM order_snapshots").fetchone()[0]
assert count == 1
def test_insert_order_snapshots_noop_when_empty(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_order_snapshots is a no-op when rows is empty."""
run_id = start_snapshot_run(conn, 1700000000)
insert_order_snapshots(conn, run_id, 12345, [])
count = conn.execute("SELECT COUNT(*) FROM order_snapshots").fetchone()[0]
assert count == 0
def test_insert_order_snapshots_normalizes_timestamp_time_setup(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_order_snapshots converts pd.Timestamp time_setup to epoch int."""
run_id = start_snapshot_run(conn, 1700000000)
ts = pd.Timestamp("2024-01-15 10:30:00", tz="UTC")
rows: list[dict[str, object]] = [{"ticket": 10, "time_setup": ts}]
insert_order_snapshots(conn, run_id, 12345, rows)
stored = conn.execute("SELECT time_setup FROM order_snapshots").fetchone()[0]
assert stored == int(ts.timestamp())
def test_insert_order_snapshots_stores_int_time_setup(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_order_snapshots stores an integer time_setup as-is."""
run_id = start_snapshot_run(conn, 1700000000)
rows: list[dict[str, object]] = [{"ticket": 10, "time_setup": 1705314600}]
insert_order_snapshots(conn, run_id, 12345, rows)
stored = conn.execute("SELECT time_setup FROM order_snapshots").fetchone()[0]
assert stored == 1705314600
def test_insert_order_snapshots_stores_null_for_unknown_time_setup_type(
self,
conn: sqlite3.Connection,
) -> None:
"""insert_order_snapshots stores NULL for an unrecognized time_setup type."""
run_id = start_snapshot_run(conn, 1700000000)
rows: list[dict[str, object]] = [{"ticket": 10, "time_setup": "not_a_time"}]
insert_order_snapshots(conn, run_id, 12345, rows)
stored = conn.execute("SELECT time_setup FROM order_snapshots").fetchone()[0]
assert stored is None
def test_insert_terminal_snapshot(self, conn: sqlite3.Connection) -> None:
"""insert_terminal_snapshot appends a terminal info row."""
run_id = start_snapshot_run(conn, 1700000000)
row: dict[str, object] = {
"name": "MetaTrader 5",
"connected": 1,
"community_account": 0,
"trade_allowed": 1,
"trade_expert": 1,
"path": "/mt5",
"company": "Broker",
"language": "en",
}
insert_terminal_snapshot(conn, run_id, row)
result = conn.execute(
"SELECT name, connected FROM terminal_snapshots"
).fetchone()
assert result == ("MetaTrader 5", 1)
def test_start_snapshot_run_returns_incrementing_ids(
self,
conn: sqlite3.Connection,
) -> None:
"""start_snapshot_run returns a unique run_id for each call."""
run1 = start_snapshot_run(conn, 1700000000)
run2 = start_snapshot_run(conn, 1700000000)
assert run1 != run2
def test_record_snapshot_run_with_detail(
self,
conn: sqlite3.Connection,
) -> None:
"""record_snapshot_run stores status and detail text."""
run_id = start_snapshot_run(conn, 1700000000)
record_snapshot_run(conn, run_id, "error", "RuntimeError: boom")
row = conn.execute("SELECT status, detail FROM snapshot_runs").fetchone()
assert row == ("error", "RuntimeError: boom")
def test_record_snapshot_run_without_detail(
self,
conn: sqlite3.Connection,
) -> None:
"""record_snapshot_run stores None for detail when omitted."""
run_id = start_snapshot_run(conn, 1700000000)
record_snapshot_run(conn, run_id, "ok")
row = conn.execute("SELECT status, detail FROM snapshot_runs").fetchone()
assert row == ("ok", None)
# ---------------------------------------------------------------------------
# TestPublishGrafanaCopy
# ---------------------------------------------------------------------------
def _make_source_db(path: Path) -> None:
"""Create a minimal source SQLite database with snapshot tables."""
with sqlite3.connect(path) as conn:
conn.execute("PRAGMA journal_mode=WAL")
create_snapshot_tables(conn)
conn.execute(
"INSERT INTO snapshot_runs (observed_at, status) VALUES (?, 'ok')",
(1700000000,),
)
class TestPublishGrafanaCopy:
"""Tests for publish_grafana_copy."""
def test_publish_to_fresh_target(self, tmp_path: Path) -> None:
"""publish_grafana_copy creates the target file."""
source = tmp_path / "src.db"
target = tmp_path / "out" / "grafana.db"
_make_source_db(source)
result = publish_grafana_copy(source, target)
assert target.exists()
assert result == target.resolve()
def test_overwrite_existing_target(self, tmp_path: Path) -> None:
"""publish_grafana_copy replaces an existing target without error."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
target.write_bytes(b"stale")
publish_grafana_copy(source, target)
# Target must now be a valid SQLite file from source
with sqlite3.connect(target) as conn:
tables = {
row[0]
for row in conn.execute(
"SELECT name FROM sqlite_master WHERE type='table'"
).fetchall()
}
assert "snapshot_runs" in tables
def test_target_contains_source_tables(self, tmp_path: Path) -> None:
"""Published target contains the same tables as the source."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
publish_grafana_copy(source, target)
with sqlite3.connect(target) as conn:
tables = {
row[0]
for row in conn.execute(
"SELECT name FROM sqlite_master WHERE type='table'"
).fetchall()
}
assert {"snapshot_runs", "account_snapshots"}.issubset(tables)
def test_target_can_be_opened_readonly(self, tmp_path: Path) -> None:
"""Published target can be opened with uri=True in read-only mode."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
publish_grafana_copy(source, target)
uri = f"file:{target}?mode=ro"
with sqlite3.connect(uri, uri=True) as conn:
row = conn.execute("SELECT status FROM snapshot_runs").fetchone()
assert row == ("ok",)
def test_same_path_raises(self, tmp_path: Path) -> None:
"""publish_grafana_copy raises ValueError when source equals target."""
db = tmp_path / "history.db"
_make_source_db(db)
with pytest.raises(ValueError, match="must differ from the source"):
publish_grafana_copy(db, db)
def test_source_not_found_raises(self, tmp_path: Path) -> None:
"""publish_grafana_copy raises FileNotFoundError when source is absent."""
with pytest.raises(FileNotFoundError):
publish_grafana_copy(tmp_path / "missing.db", tmp_path / "out.db")
def test_preserve_old_target_on_backup_failure(self, tmp_path: Path) -> None:
"""Old target is preserved when the backup fails."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
original_content = b"original_data"
target.write_bytes(original_content)
with patch("sqlite3.connect") as mock_connect:
mock_src = MagicMock()
mock_src.__enter__ = MagicMock(return_value=mock_src)
mock_src.__exit__ = MagicMock(return_value=False)
mock_src.backup.side_effect = sqlite3.OperationalError("backup failed")
mock_connect.return_value = mock_src
with pytest.raises(sqlite3.OperationalError, match="backup failed"):
publish_grafana_copy(source, target)
assert target.read_bytes() == original_content
def test_temp_file_cleaned_up_on_failure(self, tmp_path: Path) -> None:
"""Temporary file is removed when backup raises an exception."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
with patch("sqlite3.connect") as mock_connect:
mock_src = MagicMock()
mock_src.__enter__ = MagicMock(return_value=mock_src)
mock_src.__exit__ = MagicMock(return_value=False)
mock_src.backup.side_effect = sqlite3.OperationalError("fail")
mock_connect.return_value = mock_src
with pytest.raises(sqlite3.OperationalError):
publish_grafana_copy(source, target)
tmp_files = list(tmp_path.glob("grafana.db.*.tmp"))
assert not tmp_files, "Temp file should be cleaned up on failure"
def test_returns_path_object(self, tmp_path: Path) -> None:
"""publish_grafana_copy returns a Path instance."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
result = publish_grafana_copy(source, target)
assert isinstance(result, Path)
def test_fresh_target_has_readable_permissions(self, tmp_path: Path) -> None:
"""Published copy is readable by the owner."""
import stat as _stat # noqa: PLC0415
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
publish_grafana_copy(source, target)
mode = target.stat().st_mode & 0o777
assert bool(mode & _stat.S_IRUSR), "owner must be able to read"
@pytest.mark.skipif(
__import__("sys").platform == "win32",
reason="Windows does not support Unix-style group/other permission bits",
)
def test_overwrite_preserves_existing_target_mode(self, tmp_path: Path) -> None:
"""Overwriting an existing target preserves that target's file mode."""
source = tmp_path / "src.db"
target = tmp_path / "grafana.db"
_make_source_db(source)
target.write_bytes(b"old")
target.chmod(0o640)
publish_grafana_copy(source, target)
mode = target.stat().st_mode & 0o777
assert mode == 0o640
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"""Tests for mt5cli.telemetry module."""
from __future__ import annotations
from unittest.mock import MagicMock
import pytest
from opentelemetry.sdk.metrics.export import InMemoryMetricReader
from mt5cli.telemetry import (
_OTEL_AVAILABLE, # type: ignore[reportPrivateUsage]
_Mt5Metrics, # type: ignore[reportPrivateUsage]
_NoOp, # type: ignore[reportPrivateUsage]
configure_metrics,
enable_otel_metrics,
get_metrics,
)
class TestNoOp:
"""Tests for _NoOp no-op instrument."""
def test_add_is_noop(self) -> None:
"""_NoOp.add accepts amount and optional attributes without error."""
noop = _NoOp()
noop.add(1.0)
noop.add(1.0, {"key": "val"})
def test_set_is_noop(self) -> None:
"""_NoOp.set accepts amount and optional attributes without error."""
noop = _NoOp()
noop.set(2.0)
noop.set(2.0, {"key": "val"})
def test_record_is_noop(self) -> None:
"""_NoOp.record accepts amount and optional attributes without error."""
noop = _NoOp()
noop.record(3.0)
noop.record(3.0, {"key": "val"})
class TestMt5Metrics:
"""Tests for _Mt5Metrics."""
def test_default_instruments_are_noop(self) -> None:
"""Default _Mt5Metrics methods do not raise before configure is called."""
m = _Mt5Metrics()
m.record_account_state(
login="123",
server="demo",
balance=1000.0,
equity=1050.0,
margin=100.0,
margin_free=950.0,
margin_level=1050.0,
)
def test_configure_calls_meter(self) -> None:
"""configure() calls create_histogram, create_counter, create_gauge on meter."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
assert meter.create_histogram.called
assert meter.create_counter.called
assert meter.create_gauge.called
def test_record_history_update_success(self) -> None:
"""record_history_update records duration and timestamp on success."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
with m.record_history_update(dataset="rates"):
pass
m._history_duration.record.assert_called_once() # type: ignore[reportPrivateUsage]
m._last_successful_update.set.assert_called_once() # type: ignore[reportPrivateUsage]
m._history_failures.add.assert_not_called() # type: ignore[reportPrivateUsage]
def test_record_history_update_failure(self) -> None:
"""record_history_update increments failure counter and re-raises on error."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
exc = ValueError("boom")
with (
pytest.raises(ValueError, match="boom"),
m.record_history_update(dataset="rates"),
):
raise exc
m._history_failures.add.assert_called_once_with( # type: ignore[reportPrivateUsage]
1, {"dataset": "rates"}
)
m._history_duration.record.assert_not_called() # type: ignore[reportPrivateUsage]
def test_add_history_rows(self) -> None:
"""add_history_rows increments the rows-written counter."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
m.add_history_rows(42, dataset="rates")
m._history_rows.add.assert_called_once_with( # type: ignore[reportPrivateUsage]
42, {"dataset": "rates"}
)
def test_record_snapshot_update_success(self) -> None:
"""record_snapshot_update records duration on success."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
with m.record_snapshot_update():
pass
m._snapshot_duration.record.assert_called_once() # type: ignore[reportPrivateUsage]
m._snapshot_failures.add.assert_not_called() # type: ignore[reportPrivateUsage]
def test_record_snapshot_update_failure(self) -> None:
"""record_snapshot_update increments failure counter and re-raises on error."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
exc = RuntimeError("snap fail")
with (
pytest.raises(RuntimeError, match="snap fail"),
m.record_snapshot_update(),
):
raise exc
m._snapshot_failures.add.assert_called_once_with(1, {}) # type: ignore[reportPrivateUsage]
m._snapshot_duration.record.assert_not_called() # type: ignore[reportPrivateUsage]
def test_record_position_state(self) -> None:
"""record_position_state emits profit and volume gauges."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
m.record_position_state(
login="42",
server="demo",
symbol="EURUSD",
profit=12.5,
volume=0.01,
)
# Both profit and volume share the same gauge mock via create_gauge.
# Verify that set was called exactly twice (once each).
assert m._position_profit.set.call_count == 2 # type: ignore[reportPrivateUsage]
def test_record_terminal_state(self) -> None:
"""record_terminal_state emits connected, trade_allowed, trade_expert gauges."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
m.record_terminal_state(connected=1.0, trade_allowed=1.0, trade_expert=0.0)
# All three terminal gauges share the same mock; set is called 3 times.
assert m._terminal_connected.set.call_count == 3 # type: ignore[reportPrivateUsage]
def test_record_account_state_after_configure(self) -> None:
"""record_account_state emits all five account gauges."""
meter = MagicMock()
m = _Mt5Metrics()
m.configure(meter)
m.record_account_state(
login="99",
server="live",
balance=5000.0,
equity=5100.0,
margin=200.0,
margin_free=4800.0,
margin_level=2550.0,
)
# All five account gauges share the same gauge mock; set is called 5 times.
assert m._account_balance.set.call_count == 5 # type: ignore[reportPrivateUsage]
def test_record_history_update_noop_before_configure(self) -> None:
"""record_history_update works without configure (no-op instruments)."""
m = _Mt5Metrics()
with m.record_history_update(dataset="ticks"):
pass
def test_record_snapshot_update_noop_before_configure(self) -> None:
"""record_snapshot_update works without configure (no-op instruments)."""
m = _Mt5Metrics()
with m.record_snapshot_update():
pass
class TestConfigureMetrics:
"""Tests for configure_metrics and get_metrics."""
def test_configure_metrics_updates_global(self) -> None:
"""configure_metrics wires up the global singleton."""
meter = MagicMock()
configure_metrics(meter)
assert get_metrics() is get_metrics()
def test_get_metrics_returns_mt5metrics(self) -> None:
"""get_metrics returns the global _Mt5Metrics instance."""
assert isinstance(get_metrics(), _Mt5Metrics)
class TestEnableOtelMetrics:
"""Tests for enable_otel_metrics."""
def test_enable_raises_when_unavailable(
self,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""enable_otel_metrics raises ImportError when OTel is not installed."""
monkeypatch.setattr("mt5cli.telemetry._OTEL_AVAILABLE", False)
with pytest.raises(ImportError, match="opentelemetry-api"):
enable_otel_metrics()
def test_enable_configures_sdk_pipeline_with_readers(
self,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""enable_otel_metrics wires up an SDK MeterProvider with supplied readers."""
mock_mod = MagicMock()
monkeypatch.setattr("mt5cli.telemetry._OTEL_AVAILABLE", True)
monkeypatch.setattr("mt5cli.telemetry._otel_metrics_mod", mock_mod)
reader = InMemoryMetricReader()
enable_otel_metrics("my-service", readers=[reader])
mock_mod.set_meter_provider.assert_called_once()
provider = mock_mod.set_meter_provider.call_args[0][0]
assert provider.get_meter("my-service") is not None
def test_enable_default_readers_uses_otlp(
self,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""enable_otel_metrics with no readers creates an OTLP pipeline by default."""
mock_mod = MagicMock()
monkeypatch.setattr("mt5cli.telemetry._OTEL_AVAILABLE", True)
monkeypatch.setattr("mt5cli.telemetry._otel_metrics_mod", mock_mod)
monkeypatch.setattr("mt5cli.telemetry._OtelOTLPExporter", MagicMock())
enable_otel_metrics("my-service")
mock_mod.set_meter_provider.assert_called_once()
def test_enable_default_readers_raises_when_otlp_missing(
self,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""enable_otel_metrics raises ImportError when the OTLP exporter is missing."""
mock_mod = MagicMock()
monkeypatch.setattr("mt5cli.telemetry._OTEL_AVAILABLE", True)
monkeypatch.setattr("mt5cli.telemetry._otel_metrics_mod", mock_mod)
monkeypatch.setattr("mt5cli.telemetry._OtelOTLPExporter", None)
with pytest.raises(ImportError, match="opentelemetry-exporter-otlp-proto-http"):
enable_otel_metrics()
def test_otel_available_flag_is_bool(self) -> None:
"""_OTEL_AVAILABLE is a boolean."""
assert isinstance(_OTEL_AVAILABLE, bool)
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"""Tests for mt5cli.utils module."""
from __future__ import annotations
import json
import sqlite3
import sys
from datetime import UTC, datetime
from typing import TYPE_CHECKING
import pandas as pd
import pytest
import mt5cli.utils
if TYPE_CHECKING:
from pathlib import Path
from mt5cli.utils import (
DATETIME_TYPE,
REQUEST_TYPE,
TICK_FLAGS_TYPE,
TIMEFRAME_TYPE,
Dataset,
IfExists,
detect_format,
export_dataframe,
export_dataframe_to_sqlite,
parse_datetime,
parse_request,
parse_tick_flags,
parse_timeframe,
)
# ---------------------------------------------------------------------------
# detect_format
# ---------------------------------------------------------------------------
class TestDetectFormat:
"""Tests for detect_format."""
def test_explicit_format_returned(self, tmp_path: Path) -> None:
"""Test that explicit format overrides extension."""
result = detect_format(tmp_path / "data.txt", explicit_format="csv")
assert result == "csv"
@pytest.mark.parametrize(
("filename", "expected"),
[
("data.csv", "csv"),
("data.json", "json"),
("data.parquet", "parquet"),
("data.pq", "parquet"),
("data.db", "sqlite3"),
("data.sqlite", "sqlite3"),
("data.sqlite3", "sqlite3"),
("DATA.CSV", "csv"),
("DATA.JSON", "json"),
("DATA.PARQUET", "parquet"),
],
)
def test_auto_detect_from_extension(
self,
tmp_path: Path,
filename: str,
expected: str,
) -> None:
"""Test format auto-detection from file extension."""
result = detect_format(tmp_path / filename)
assert result == expected
def test_unknown_extension_raises(self, tmp_path: Path) -> None:
"""Test that unknown extension raises ValueError."""
with pytest.raises(ValueError, match="Cannot detect format"):
detect_format(tmp_path / "data.xyz")
# ---------------------------------------------------------------------------
# export_dataframe
# ---------------------------------------------------------------------------
class TestExportDataframe:
"""Tests for export_dataframe."""
@pytest.fixture
def sample_df(self) -> pd.DataFrame:
"""Create a sample DataFrame for testing."""
return pd.DataFrame({"a": [1, 2, 3], "b": ["x", "y", "z"]})
def test_export_csv(self, tmp_path: Path, sample_df: pd.DataFrame) -> None:
"""Test CSV export."""
output = tmp_path / "out.csv"
export_dataframe(sample_df, output, "csv")
result = pd.read_csv(output)
pd.testing.assert_frame_equal(result, sample_df)
def test_export_json(self, tmp_path: Path, sample_df: pd.DataFrame) -> None:
"""Test JSON export."""
output = tmp_path / "out.json"
export_dataframe(sample_df, output, "json")
with output.open() as f:
records = json.load(f)
assert len(records) == 3
assert records[0]["a"] == 1
def test_export_parquet(self, tmp_path: Path, sample_df: pd.DataFrame) -> None:
"""Test Parquet export."""
output = tmp_path / "out.parquet"
export_dataframe(sample_df, output, "parquet")
result = pd.read_parquet(output)
pd.testing.assert_frame_equal(result, sample_df)
def test_export_parquet_without_pyarrow(
self,
tmp_path: Path,
sample_df: pd.DataFrame,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Test that a clear error is raised when pyarrow is not installed."""
monkeypatch.setitem(sys.modules, "pyarrow", None)
with pytest.raises(ImportError, match="mt5cli\\[parquet\\]"):
export_dataframe(sample_df, tmp_path / "out.parquet", "parquet")
def test_export_sqlite3(self, tmp_path: Path, sample_df: pd.DataFrame) -> None:
"""Test SQLite3 export."""
output = tmp_path / "out.db"
export_dataframe(sample_df, output, "sqlite3", table_name="test_table")
with sqlite3.connect(output) as conn:
result = pd.read_sql( # type: ignore[reportUnknownMemberType]
"SELECT * FROM test_table",
conn,
)
pd.testing.assert_frame_equal(result, sample_df)
def test_unsupported_format_raises(
self,
tmp_path: Path,
sample_df: pd.DataFrame,
) -> None:
"""Test that unsupported format raises ValueError."""
with pytest.raises(ValueError, match="Unsupported output format"):
export_dataframe(sample_df, tmp_path / "out.txt", "xml")
class TestExportDataframeToSqlite:
"""Tests for export_dataframe_to_sqlite."""
def test_append_preserves_existing_rows(self, tmp_path: Path) -> None:
"""Test append mode keeps prior rows in the SQLite table."""
output = tmp_path / "append.db"
first = pd.DataFrame({"id": [1], "value": ["a"]})
second = pd.DataFrame({"id": [2], "value": ["b"]})
export_dataframe_to_sqlite(first, output, "items", if_exists=IfExists.REPLACE)
export_dataframe_to_sqlite(second, output, "items", if_exists=IfExists.APPEND)
with sqlite3.connect(output) as conn:
result = pd.read_sql( # type: ignore[reportUnknownMemberType]
"SELECT id, value FROM items ORDER BY id",
conn,
)
pd.testing.assert_frame_equal(
result,
pd.DataFrame({"id": [1, 2], "value": ["a", "b"]}),
)
def test_deduplicate_keeps_latest_row(self, tmp_path: Path) -> None:
"""Test deduplication keeps the latest ROWID for key columns."""
output = tmp_path / "dedup.db"
first = pd.DataFrame({
"symbol": ["EURUSD", "EURUSD"],
"time": ["2024-01-01", "2024-01-01"],
"bid": [1.0, 1.1],
})
second = pd.DataFrame({
"symbol": ["EURUSD"],
"time": ["2024-01-01"],
"bid": [1.2],
})
export_dataframe_to_sqlite(
first,
output,
"ticks",
if_exists=IfExists.REPLACE,
deduplicate_on=("symbol", "time"),
)
export_dataframe_to_sqlite(
second,
output,
"ticks",
if_exists=IfExists.APPEND,
deduplicate_on=("symbol", "time"),
)
with sqlite3.connect(output) as conn:
result = pd.read_sql( # type: ignore[reportUnknownMemberType]
"SELECT symbol, time, bid FROM ticks",
conn,
)
pd.testing.assert_frame_equal(
result.reset_index(drop=True),
pd.DataFrame({
"symbol": ["EURUSD"],
"time": ["2024-01-01"],
"bid": [1.2],
}),
)
def test_default_if_exists_appends_without_dropping_rows(
self,
tmp_path: Path,
) -> None:
"""Test the default append mode keeps prior rows."""
output = tmp_path / "default-append.db"
first = pd.DataFrame({"id": [1], "value": ["a"]})
second = pd.DataFrame({"id": [2], "value": ["b"]})
export_dataframe_to_sqlite(first, output, "items")
export_dataframe_to_sqlite(second, output, "items")
with sqlite3.connect(output) as conn:
result = pd.read_sql( # type: ignore[reportUnknownMemberType]
"SELECT id, value FROM items ORDER BY id",
conn,
)
pd.testing.assert_frame_equal(
result,
pd.DataFrame({"id": [1, 2], "value": ["a", "b"]}),
)
def test_writes_index_with_label(self, tmp_path: Path) -> None:
"""Test optional index export with a custom label."""
output = tmp_path / "index.db"
frame = pd.DataFrame(
{"value": [1.0]}, index=pd.Index(["EURUSD"], name="symbol")
)
export_dataframe_to_sqlite(
frame,
output,
"margins",
if_exists=IfExists.REPLACE,
index=True,
index_label="symbol",
)
with sqlite3.connect(output) as conn:
result = pd.read_sql( # type: ignore[reportUnknownMemberType]
"SELECT symbol, value FROM margins",
conn,
)
pd.testing.assert_frame_equal(
result,
pd.DataFrame({"symbol": ["EURUSD"], "value": [1.0]}),
)
# ---------------------------------------------------------------------------
# Parse helpers
# ---------------------------------------------------------------------------
class TestParseDatetime:
"""Tests for parse_datetime."""
def test_valid_date(self) -> None:
"""Test parsing a date string."""
result = parse_datetime("2024-01-15")
assert result == datetime(2024, 1, 15, tzinfo=UTC)
def test_valid_datetime_with_tz(self) -> None:
"""Test parsing a datetime with timezone."""
result = parse_datetime("2024-01-15T12:00:00+00:00")
assert result == datetime(2024, 1, 15, 12, 0, 0, tzinfo=UTC)
def test_invalid_format_raises(self) -> None:
"""Test that invalid format raises ValueError."""
with pytest.raises(ValueError, match="Invalid datetime"):
parse_datetime("not-a-date")
class TestParseTimeframe:
"""Tests for parse_timeframe."""
@pytest.mark.parametrize(
("value", "expected"),
[("M1", 1), ("h1", 16385), ("D1", 16408), ("MN1", 49153)],
)
def test_named_timeframe(self, value: str, expected: int) -> None:
"""Test parsing named timeframes."""
assert parse_timeframe(value) == expected
def test_integer_timeframe(self) -> None:
"""Test parsing supported integer timeframes."""
assert parse_timeframe("1") == 1
assert parse_timeframe(16385) == 16385
def test_unsupported_integer_timeframe_raises(self) -> None:
"""Test that unsupported integer timeframes raise ValueError."""
with pytest.raises(ValueError, match="Invalid timeframe"):
parse_timeframe("42")
def test_invalid_timeframe_raises(self) -> None:
"""Test that invalid timeframe raises ValueError."""
with pytest.raises(ValueError, match="Invalid timeframe"):
parse_timeframe("INVALID")
class TestParseTickFlags:
"""Tests for parse_tick_flags."""
@pytest.mark.parametrize(
("value", "expected"),
[("ALL", -1), ("info", 1), ("TRADE", 2), ("COPY_TICKS_ALL", -1)],
)
def test_named_flag(self, value: str, expected: int) -> None:
"""Test parsing named tick flags."""
assert parse_tick_flags(value) == expected
def test_integer_flag(self) -> None:
"""Test parsing supported integer tick flags."""
assert parse_tick_flags("-1") == -1
assert parse_tick_flags(2) == 2
def test_unsupported_integer_flag_raises(self) -> None:
"""Test that unsupported integer tick flags raise ValueError."""
with pytest.raises(ValueError, match="Invalid tick flags"):
parse_tick_flags("7")
def test_invalid_flag_raises(self) -> None:
"""Test that invalid flag raises ValueError."""
with pytest.raises(ValueError, match="Invalid tick flags"):
parse_tick_flags("INVALID")
# ---------------------------------------------------------------------------
# parse_request
# ---------------------------------------------------------------------------
class TestParseRequest:
"""Tests for parse_request."""
def test_inline_json(self) -> None:
"""Test parsing an inline JSON object string."""
result = parse_request('{"action": 1, "symbol": "EURUSD"}')
assert result == {"action": 1, "symbol": "EURUSD"}
def test_file_reference(self, tmp_path: Path) -> None:
"""Test parsing JSON from a file via the @path syntax."""
path = tmp_path / "req.json"
path.write_text('{"action": 2}', encoding="utf-8")
result = parse_request(f"@{path}")
assert result == {"action": 2}
def test_invalid_json_raises(self) -> None:
"""Test that invalid JSON raises ValueError."""
with pytest.raises(ValueError, match="Invalid JSON request"):
parse_request("not json")
def test_non_object_raises(self) -> None:
"""Test that a non-object JSON raises ValueError."""
with pytest.raises(ValueError, match="must be a JSON object"):
parse_request("[1, 2, 3]")
def test_missing_file_raises(self, tmp_path: Path) -> None:
"""Test that a missing request file raises ValueError."""
path = tmp_path / "missing.json"
with pytest.raises(ValueError, match="Failed to read JSON request file"):
parse_request(f"@{path}")
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
class TestConstants:
"""Tests for module constants."""
def test_timeframe_map_is_private_in_utils(self) -> None:
"""TIMEFRAME_MAP is a private implementation detail; not a public attribute."""
assert not hasattr(mt5cli.utils, "TIMEFRAME_MAP")
def test_tick_flag_map_absent_from_utils(self) -> None:
"""TICK_FLAG_MAP is not exposed by mt5cli.utils."""
assert not hasattr(mt5cli.utils, "TICK_FLAG_MAP")
@pytest.mark.parametrize(
("dataset", "expected"),
[
(Dataset.rates, "rates"),
(Dataset.ticks, "ticks"),
(Dataset.history_orders, "history_orders"),
(Dataset.history_deals, "history_deals"),
],
)
def test_dataset_table_name(self, dataset: Dataset, expected: str) -> None:
"""Test dataset SQLite table names."""
assert dataset.table_name == expected
# ---------------------------------------------------------------------------
# Click ParamTypes
# ---------------------------------------------------------------------------
class TestDateTimeType:
"""Tests for _DateTimeType."""
def test_convert_string(self) -> None:
"""Test converting a string to datetime."""
result = DATETIME_TYPE.convert("2024-06-15", None, None)
assert result == datetime(2024, 6, 15, tzinfo=UTC)
def test_convert_datetime_passthrough(self) -> None:
"""Test that datetime values pass through unchanged."""
dt = datetime(2024, 1, 1, tzinfo=UTC)
assert DATETIME_TYPE.convert(dt, None, None) is dt
def test_convert_invalid(self) -> None:
"""Test that invalid values raise BadParameter."""
with pytest.raises(Exception, match="Invalid datetime"):
DATETIME_TYPE.convert("bad", None, None)
class TestTimeframeType:
"""Tests for _TimeframeType."""
def test_convert_string(self) -> None:
"""Test converting a string to timeframe integer."""
assert TIMEFRAME_TYPE.convert("H1", None, None) == 16385
def test_convert_int(self) -> None:
"""Test converting supported integer timeframe values."""
assert TIMEFRAME_TYPE.convert(16385, None, None) == 16385
def test_convert_unsupported_int(self) -> None:
"""Test that unsupported integer values raise BadParameter."""
with pytest.raises(Exception, match="Invalid timeframe"):
TIMEFRAME_TYPE.convert(42, None, None)
def test_convert_invalid(self) -> None:
"""Test that invalid values raise BadParameter."""
with pytest.raises(Exception, match="Invalid timeframe"):
TIMEFRAME_TYPE.convert("bad", None, None)
@pytest.mark.parametrize("value", [True, False, None, 1.5])
def test_convert_invalid_types(self, value: object) -> None:
"""Test that bool, float, and None values raise BadParameter."""
with pytest.raises(Exception, match="Invalid timeframe"):
TIMEFRAME_TYPE.convert(value, None, None)
class TestTickFlagsType:
"""Tests for _TickFlagsType."""
def test_convert_string(self) -> None:
"""Test converting a string to tick flags integer."""
assert TICK_FLAGS_TYPE.convert("ALL", None, None) == -1
def test_convert_int(self) -> None:
"""Test converting supported integer tick flag values."""
assert TICK_FLAGS_TYPE.convert(2, None, None) == 2
def test_convert_unsupported_int(self) -> None:
"""Test that unsupported integer values raise BadParameter."""
with pytest.raises(Exception, match="Invalid tick flags"):
TICK_FLAGS_TYPE.convert(7, None, None)
@pytest.mark.parametrize("value", [True, False, None, 1.5])
def test_convert_invalid_types(self, value: object) -> None:
"""Test that bool, float, and None values raise BadParameter."""
with pytest.raises(Exception, match="Invalid tick flags"):
TICK_FLAGS_TYPE.convert(value, None, None)
def test_convert_invalid(self) -> None:
"""Test that invalid values raise BadParameter."""
with pytest.raises(Exception, match="Invalid tick flags"):
TICK_FLAGS_TYPE.convert("bad", None, None)
class TestRequestType:
"""Tests for _RequestType."""
def test_convert_string(self) -> None:
"""Test converting a JSON string to a request dictionary."""
assert REQUEST_TYPE.convert('{"action": 1}', None, None) == {"action": 1}
def test_convert_invalid(self) -> None:
"""Test that invalid values raise BadParameter."""
with pytest.raises(Exception, match="Invalid JSON request"):
REQUEST_TYPE.convert("bad", None, None)
Generated
+146 -19
View File
@@ -223,6 +223,18 @@ wheels = [
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{ name = "protobuf" },
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]
[[package]]
name = "griffelib"
version = "2.0.2"
@@ -234,11 +246,11 @@ wheels = [
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name = "idna"
version = "3.13"
version = "3.15"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/ce/cc/762dfb036166873f0059f3b7de4565e1b5bc3d6f28a414c13da27e442f99/idna-3.13.tar.gz", hash = "sha256:585ea8fe5d69b9181ec1afba340451fba6ba764af97026f92a91d4eef164a242", size = 194210, upload-time = "2026-04-22T16:42:42.314Z" }
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[[package]]
@@ -487,21 +499,33 @@ wheels = [
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name = "mt5cli"
version = "0.2.0"
version = "1.1.0"
source = { editable = "." }
dependencies = [
{ name = "click" },
{ name = "pdmt5" },
{ name = "pyarrow" },
{ name = "typer" },
]
[package.optional-dependencies]
otel = [
{ name = "opentelemetry-api" },
{ name = "opentelemetry-exporter-otlp-proto-http" },
{ name = "opentelemetry-sdk" },
]
parquet = [
{ name = "pyarrow" },
]
[package.dev-dependencies]
dev = [
{ name = "mkdocs" },
{ name = "mkdocs-material" },
{ name = "mkdocstrings", extra = ["python"] },
{ name = "opentelemetry-api" },
{ name = "opentelemetry-sdk" },
{ name = "pandas-stubs" },
{ name = "pyarrow" },
{ name = "pymdown-extensions" },
{ name = "pyright" },
{ name = "pytest" },
@@ -513,17 +537,24 @@ dev = [
[package.metadata]
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{ name = "pdmt5", specifier = ">=0.2.3" },
{ name = "pyarrow", specifier = ">=19.0.0" },
{ name = "opentelemetry-api", marker = "extra == 'otel'" },
{ name = "opentelemetry-exporter-otlp-proto-http", marker = "extra == 'otel'" },
{ name = "opentelemetry-sdk", marker = "extra == 'otel'" },
{ name = "pdmt5", specifier = ">=1.0.0" },
{ name = "pyarrow", marker = "extra == 'parquet'", specifier = ">=19.0.0" },
{ name = "typer", specifier = ">=0.15.0" },
]
provides-extras = ["parquet", "otel"]
[package.metadata.requires-dev]
dev = [
{ name = "mkdocs", specifier = ">=1.6.1" },
{ name = "mkdocs-material", specifier = ">=9.7.6" },
{ name = "mkdocstrings", extras = ["python"], specifier = ">=1.0.4" },
{ name = "opentelemetry-api" },
{ name = "opentelemetry-sdk" },
{ name = "pandas-stubs", specifier = ">=2.2.3.250527" },
{ name = "pyarrow", specifier = ">=19.0.0" },
{ name = "pymdown-extensions", specifier = ">=10.21.2" },
{ name = "pyright", specifier = ">=1.1.407" },
{ name = "pytest", specifier = ">=9.0.3" },
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