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Author SHA1 Message Date
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
19 changed files with 10149 additions and 1306 deletions
+3 -1
View File
@@ -29,9 +29,11 @@ uv sync
- `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
- `utils.py`: Constants, enums, parameter types, parsers, and export utilities
- `__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
- `test_cli.py`: Tests for CLI commands and collect-history behavior
- `test_utils.py`: Tests for utility constants, parameter types, parsers, and export functions
- `docs/`: MkDocs documentation with API reference
- `docs/index.md`: Main documentation
- `docs/api/`: Auto-generated API documentation for all modules
+92 -23
View File
@@ -13,6 +13,7 @@ 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
@@ -50,28 +51,33 @@ 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) |
| `collect-history` | Bundle rates, ticks, history-orders, and history-deals for one or more symbols into a single SQLite database |
| 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 trade request to the trade server (`--yes` required) |
| `collect-history` | Bundle rates, ticks, history-orders, and history-deals for one or more symbols into a single SQLite database |
Use `order-check` to validate a request payload before running `order-send --yes`.
@@ -87,7 +93,70 @@ mt5cli -o history.db collect-history \
--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 deals, and uses volume-weighted open/close prices; reversal deals (`DEAL_ENTRY_INOUT`) are reported via `volume_reversal` / `reversal_count` columns and do not contribute to the weighted prices.
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.
### 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 Dataset, update_history, update_history_with_config
# 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 tools such as mteor optimize.
- **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 `pdmt5.Mt5TradingError` / `pdmt5.Mt5RuntimeError` 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.
- **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` and let the caller decide logging.
- **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 `Mt5CliClient` 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
+229
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@@ -0,0 +1,229 @@
# 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
Use `load_rate_data()` to load a table or view from a SQLite path, or
`load_rate_data_from_connection()` when you already have a connection:
```python
from pathlib import Path
from mt5cli import load_rate_data
from mt5cli.history import 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)
```
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)
```
+63 -6
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@@ -10,12 +10,26 @@ The mt5cli package consists of the following modules:
Command-line interface module providing typer-based commands for exporting MetaTrader 5 data to CSV, JSON, Parquet, and SQLite3 formats.
### [Utils](utils.md)
Utility module providing constants, enums, Click parameter types, and helper functions for parsing and exporting data.
### [SDK](sdk.md)
Programmatic SDK for read-only MetaTrader 5 data collection. Returns pandas DataFrames and provides `collect_history` for SQLite bulk collection.
### [History Collection (SQLite)](history.md)
SQLite storage helpers for the `collect-history` command schema, incremental updates, deduplication, indexes, and optional views.
## 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.
1. **CLI Layer** (`cli.py`): Typer application with subcommands that delegate to the SDK and export results.
2. **SDK Layer** (`sdk.py`): Read-only data access functions, `Mt5CliClient`, and `collect_history` orchestration.
3. **Utils Layer** (`utils.py`): Constants, enums, custom Click parameter types, parsing helpers, and format detection/export utilities.
4. **Data Layer** (via `pdmt5`): Uses `Mt5DataClient` and `Mt5Config` from the pdmt5 package for all MetaTrader 5 data access.
## Usage Guidelines
@@ -47,15 +61,58 @@ mt5cli -o data.db --table symbols symbols --group "*USD*"
## Python API
```python
from mt5cli import detect_format, export_dataframe
import pandas as pd
from datetime import UTC, datetime
from pathlib import Path
from mt5cli import (
Dataset,
IfExists,
Mt5CliClient,
collect_history,
copy_rates_range,
detect_format,
export_dataframe,
export_dataframe_to_sqlite,
minimum_margins,
recent_ticks,
)
from mt5cli.history import resolve_rate_view_name
# Fetch rates programmatically
rates = copy_rates_range(
"EURUSD",
timeframe="H1",
date_from="2024-01-01",
date_to="2024-02-01",
)
# 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")
export_dataframe(rates, Path("output.csv"), "csv")
# Append to SQLite with deduplication
export_dataframe_to_sqlite(
rates,
Path("history.db"),
"rates",
if_exists=IfExists.APPEND,
deduplicate_on=("symbol", "timeframe", "time"),
)
# Resolve rate compatibility views and fetch recent ticks
view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1")
ticks = recent_ticks("EURUSD", seconds=300)
margins = minimum_margins("EURUSD")
# Collect history into SQLite
collect_history(
Path("history.db"),
symbols=["EURUSD"],
date_from=datetime(2024, 1, 1, tzinfo=UTC),
date_to=datetime(2024, 2, 1, tzinfo=UTC),
)
```
## Examples
+103
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@@ -0,0 +1,103 @@
# 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. `collect_latest_closed_rates_for_accounts()` fetches `count + 1` bars,
drops that row with `drop_forming_rate_bar()`, and validates each series is
non-empty. Use `collect_latest_closed_rates_by_granularity()` when callers
prefer keys such as `("EURUSD", "M1")` instead of integer timeframes.
```python
from mt5cli import AccountSpec, collect_latest_closed_rates_by_granularity
rates = collect_latest_closed_rates_by_granularity(
[AccountSpec(symbols=["EURUSD"], login=12345)],
["M1", "H1"],
count=500,
retry_count=3,
)
closed_m1 = rates["EURUSD", "M1"]
```
### 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"
```
### 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 Dataset, ThrottledHistoryUpdater
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()
```
By default `Mt5TradingError`, `Mt5RuntimeError`, and `sqlite3.Error` propagate so
the caller controls logging; pass `suppress_errors=True` to swallow them and
return `False` without advancing the throttle.
+3
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@@ -0,0 +1,3 @@
# Utils Module
::: mt5cli.utils
+84 -13
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@@ -13,6 +13,7 @@ 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 +21,67 @@ mt5cli is a CLI application that exports MetaTrader 5 trading data to multiple f
pip install mt5cli
```
## Programmatic usage / SDK usage
mt5cli can be used as a small Python SDK for read-only MetaTrader 5 data collection. SDK functions return pandas DataFrames without writing files. Use `export_dataframe` or `export_dataframe_to_sqlite` when you need to persist results.
```python
from datetime import UTC, datetime
from pathlib import Path
from mt5cli import (
Mt5CliClient,
collect_history,
copy_rates_range,
export_dataframe,
export_dataframe_to_sqlite,
load_rate_data,
minimum_margins,
recent_ticks,
)
from mt5cli.history import resolve_rate_view_name
# One-off fetch with module-level helpers
rates = copy_rates_range(
"EURUSD",
timeframe="H1",
date_from="2024-01-01",
date_to="2024-02-01",
)
export_dataframe(rates, Path("rates.csv"), "csv")
# Resolve SQLite rate compatibility views for downstream tools
view = resolve_rate_view_name(Path("history.db"), "EURUSD", "M1", require_existing=True)
offline_rates = load_rate_data(Path("history.db"), view, count=1000)
# Recent tick window and minimum margin summary
ticks = recent_ticks("EURUSD", seconds=300)
margins = minimum_margins("EURUSD")
# Reuse one MT5 connection for multiple calls
with Mt5CliClient(login=12345, password="secret", server="Broker-Demo") as client:
account = client.account_info()
positions = client.positions()
latest = client.latest_rates("EURUSD", "M1", count=100)
summary = client.mt5_summary()
summary_table = client.mt5_summary_as_df()
# Bulk SQLite collection (same behavior as the collect-history CLI command)
collect_history(
Path("history.db"),
symbols=["EURUSD", "GBPUSD"],
date_from=datetime(2024, 1, 1, tzinfo=UTC),
date_to=datetime(2024, 2, 1, tzinfo=UTC),
timeframe="M1",
flags="ALL",
with_views=True,
)
```
Timeframes, tick flags, and ISO 8601 date strings are accepted wherever noted in the SDK API.
`Mt5CliClient.mt5_summary()` returns the SDK structured form as plain nested Python values. Use `Mt5CliClient.mt5_summary_as_df()` when you need a one-row DataFrame for export. The `mt5-summary` CLI command uses this tabular form, so nested terminal/account fields are JSON-encoded strings that are safe for CSV, JSON, Parquet, and SQLite output.
## Quick Start
```bash
@@ -50,14 +112,16 @@ 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
@@ -70,18 +134,21 @@ 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
| 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 |
| `order-send` | Send a trade request to the trade server (`--yes` required) |
Use `order-check` to validate a request payload before running `order-send --yes`.
@@ -114,6 +181,8 @@ mt5cli -o history.db collect-history \
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
| Option | Description |
@@ -138,7 +207,9 @@ History orders and deals are fetched per symbol and concatenated, so the symbol
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 export 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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@@ -24,6 +24,7 @@ theme:
features:
- content.code.annotate
- content.code.copy
- content.code.mermaid
- navigation.indexes
- navigation.sections
- navigation.tabs
@@ -56,6 +57,9 @@ nav:
- API Reference:
- Overview: api/index.md
- CLI: api/cli.md
- SDK: api/sdk.md
- History Collection (SQLite): api/history.md
- Utils: api/utils.md
markdown_extensions:
- admonition
+133 -2
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@@ -1,12 +1,143 @@
"""mt5cli: Command-line tool for MetaTrader 5."""
"""mt5cli: Command-line tool and SDK for MetaTrader 5."""
from importlib.metadata import version
from .cli import detect_format, export_dataframe
from .history import (
RateTarget,
build_rate_targets,
build_rate_view_name,
drop_forming_rate_bar,
load_rate_data,
load_rate_data_from_connection,
load_rate_series_by_granularity,
load_rate_series_from_sqlite,
resolve_history_datasets,
resolve_history_tick_flags,
resolve_history_timeframes,
resolve_rate_tables,
resolve_rate_view_name,
resolve_rate_view_names,
)
from .sdk import (
AccountSpec,
Mt5CliClient,
ThrottledHistoryUpdater,
account_info,
build_config,
collect_history,
collect_latest_closed_rates_by_granularity,
collect_latest_closed_rates_for_accounts,
collect_latest_rates,
collect_latest_rates_for_accounts,
collect_latest_rates_for_accounts_with_retries,
copy_rates_from,
copy_rates_from_pos,
copy_rates_range,
copy_ticks_from,
copy_ticks_range,
history_deals,
history_orders,
last_error,
latest_rates,
market_book,
minimum_margins,
mt5_session,
mt5_summary,
mt5_summary_as_df,
orders,
positions,
recent_history_deals,
recent_ticks,
resolve_account_spec,
resolve_account_specs,
substitute_env_placeholders,
symbol_info,
symbol_info_tick,
symbols,
terminal_info,
update_history,
update_history_with_config,
)
from .sdk import (
version as mt5_version,
)
from .utils import (
TICK_FLAG_MAP,
TIMEFRAME_MAP,
Dataset,
IfExists,
detect_format,
export_dataframe,
export_dataframe_to_sqlite,
parse_datetime,
parse_tick_flags,
parse_timeframe,
)
__version__ = version(__package__) if __package__ else None
__all__ = [
"TICK_FLAG_MAP",
"TIMEFRAME_MAP",
"AccountSpec",
"Dataset",
"IfExists",
"Mt5CliClient",
"RateTarget",
"ThrottledHistoryUpdater",
"account_info",
"build_config",
"build_rate_targets",
"build_rate_view_name",
"collect_history",
"collect_latest_closed_rates_by_granularity",
"collect_latest_closed_rates_for_accounts",
"collect_latest_rates",
"collect_latest_rates_for_accounts",
"collect_latest_rates_for_accounts_with_retries",
"copy_rates_from",
"copy_rates_from_pos",
"copy_rates_range",
"copy_ticks_from",
"copy_ticks_range",
"detect_format",
"drop_forming_rate_bar",
"export_dataframe",
"export_dataframe_to_sqlite",
"history_deals",
"history_orders",
"last_error",
"latest_rates",
"load_rate_data",
"load_rate_data_from_connection",
"load_rate_series_by_granularity",
"load_rate_series_from_sqlite",
"market_book",
"minimum_margins",
"mt5_session",
"mt5_summary",
"mt5_summary_as_df",
"mt5_version",
"orders",
"parse_datetime",
"parse_tick_flags",
"parse_timeframe",
"positions",
"recent_history_deals",
"recent_ticks",
"resolve_account_spec",
"resolve_account_specs",
"resolve_history_datasets",
"resolve_history_tick_flags",
"resolve_history_timeframes",
"resolve_rate_tables",
"resolve_rate_view_name",
"resolve_rate_view_names",
"substitute_env_placeholders",
"symbol_info",
"symbol_info_tick",
"symbols",
"terminal_info",
"update_history",
"update_history_with_config",
]
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@@ -0,0 +1,453 @@
"""Utility constants, types, and functions for the mt5cli package."""
from __future__ import annotations
import json
import sqlite3
from datetime import UTC, datetime
from enum import StrEnum
from pathlib import Path
from typing import TYPE_CHECKING, Any, TypeGuard
import click
if TYPE_CHECKING:
from collections.abc import Sequence
import pandas as pd
# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
TIMEFRAME_MAP: dict[str, int] = {
"M1": 1,
"M2": 2,
"M3": 3,
"M4": 4,
"M5": 5,
"M6": 6,
"M10": 10,
"M12": 12,
"M15": 15,
"M20": 20,
"M30": 30,
"H1": 16385,
"H2": 16386,
"H3": 16387,
"H4": 16388,
"H6": 16390,
"H8": 16392,
"H12": 16396,
"D1": 16408,
"W1": 32769,
"MN1": 49153,
}
TICK_FLAG_MAP: dict[str, int] = {
"ALL": 1,
"INFO": 2,
"TRADE": 4,
}
_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.
"""
if isinstance(value, int):
return value
try:
return parse_timeframe(str(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.
"""
if isinstance(value, int):
return value
try:
return parse_tick_flags(str(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 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 sqlite3.connect(output_path) as 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:
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":
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: str) -> 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.
"""
upper = value.upper()
if upper in TIMEFRAME_MAP:
return TIMEFRAME_MAP[upper]
try:
return int(value)
except ValueError:
valid = ", ".join(TIMEFRAME_MAP)
msg = f"Invalid timeframe: '{value}'. Use one of: {valid}, or an integer."
raise ValueError(msg) from None
def parse_tick_flags(value: str) -> int:
"""Parse tick flags string or integer value.
Args:
value: Tick flag name (ALL, INFO, TRADE) or integer value.
Returns:
Integer tick flag value.
Raises:
ValueError: If the flag is invalid.
"""
upper = value.upper()
if upper in TICK_FLAG_MAP:
return TICK_FLAG_MAP[upper]
try:
return int(value)
except ValueError:
valid = ", ".join(TICK_FLAG_MAP)
msg = f"Invalid tick flags: '{value}'. Use one of: {valid}, or an 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
+2 -5
View File
@@ -1,6 +1,6 @@
[project]
name = "mt5cli"
version = "0.3.0"
version = "0.6.0"
description = "Command-line tool for MetaTrader 5"
authors = [{name = "dceoy", email = "dceoy@users.noreply.github.com"}]
maintainers = [{name = "dceoy", email = "dceoy@users.noreply.github.com"}]
@@ -48,10 +48,6 @@ dev = [
"pymdown-extensions >= 10.21.2",
]
[tool.uv.build-backend]
source-include = ["mt5cli/**", "LICENSE"]
source-exclude = ["tests/**"]
[tool.ruff]
line-length = 88
exclude = ["build", ".venv"]
@@ -128,6 +124,7 @@ ignore = [
]
[tool.ruff.lint.per-file-ignores]
"mt5cli/history.py" = ["TC003"]
"tests/**/*.py" = [
"DOC201", # Missing return documentation
"DOC501", # Raised exception missing from docstring
+188 -320
View File
@@ -6,7 +6,7 @@ import json
import logging
import re
import sqlite3
from datetime import UTC, datetime
from datetime import UTC, datetime, timedelta
from typing import TYPE_CHECKING
from unittest.mock import MagicMock
@@ -19,22 +19,11 @@ if TYPE_CHECKING:
from pathlib import Path
from mt5cli.cli import (
DATETIME_TYPE,
REQUEST_TYPE,
TICK_FLAG_MAP,
TICK_FLAGS_TYPE,
TIMEFRAME_MAP,
TIMEFRAME_TYPE,
_execute_export, # type: ignore[reportPrivateUsage]
_ExportContext, # type: ignore[reportPrivateUsage]
_sdk_client, # type: ignore[reportPrivateUsage]
app,
detect_format,
export_dataframe,
main,
parse_datetime,
parse_request,
parse_tick_flags,
parse_timeframe,
)
runner = CliRunner()
@@ -46,299 +35,6 @@ def normalize_cli_output(output: str) -> str:
return " ".join(_ANSI_ESCAPE_RE.sub("", output).split())
# ---------------------------------------------------------------------------
# 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_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")
# ---------------------------------------------------------------------------
# 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 integer timeframe."""
assert parse_timeframe("42") == 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", 2), ("TRADE", 4)],
)
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 integer tick flag."""
assert parse_tick_flags("7") == 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_has_expected_keys(self) -> None:
"""Test that TIMEFRAME_MAP contains standard timeframes."""
for key in ("M1", "M5", "M15", "M30", "H1", "H4", "D1", "W1", "MN1"):
assert key in TIMEFRAME_MAP
def test_tick_flag_map_has_expected_keys(self) -> None:
"""Test that TICK_FLAG_MAP contains standard flags."""
assert set(TICK_FLAG_MAP) == {"ALL", "INFO", "TRADE"}
# ---------------------------------------------------------------------------
# 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_passthrough(self) -> None:
"""Test that integer values pass through unchanged."""
assert TIMEFRAME_TYPE.convert(42, None, None) == 42
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)
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_passthrough(self) -> None:
"""Test that integer values pass through unchanged."""
assert TICK_FLAGS_TYPE.convert(7, None, None) == 7
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)
# ---------------------------------------------------------------------------
# _execute_export
# ---------------------------------------------------------------------------
@@ -355,7 +51,7 @@ class TestExecuteExport:
"""Test that shutdown is called even when fetch raises."""
mock_client = MagicMock()
mock_client.account_info_as_df.side_effect = RuntimeError("boom")
mocker.patch("mt5cli.cli.Mt5DataClient", return_value=mock_client)
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=mock_client)
ctx = MagicMock()
ctx.obj = _ExportContext(
output=tmp_path / "out.csv",
@@ -364,7 +60,7 @@ class TestExecuteExport:
config=MagicMock(),
)
with pytest.raises(RuntimeError, match="boom"):
_execute_export(ctx, lambda c: c.account_info_as_df())
_execute_export(ctx, _sdk_client(ctx).account_info)
mock_client.shutdown.assert_called_once()
@@ -397,7 +93,11 @@ def mock_client(mocker: MockerFixture) -> MagicMock:
client.market_book_get_as_df.return_value = sample_df
client.order_check_as_df.return_value = sample_df
client.order_send_as_df.return_value = sample_df
mocker.patch("mt5cli.cli.Mt5DataClient", return_value=client)
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
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
return client
@@ -527,6 +227,37 @@ class TestCommands:
count=50,
)
def test_latest_rates(
self,
tmp_path: Path,
mock_client: MagicMock,
) -> None:
"""Test latest-rates command."""
output = tmp_path / "out.csv"
result = runner.invoke(
app,
[
"-o",
str(output),
"latest-rates",
"--symbol",
"GBPUSD",
"--timeframe",
"H1",
"--count",
"50",
"--start-pos",
"2",
],
)
assert result.exit_code == 0, result.output
mock_client.copy_rates_from_pos_as_df.assert_called_once_with(
symbol="GBPUSD",
timeframe=16385,
start_pos=2,
count=50,
)
def test_rates_range(
self,
tmp_path: Path,
@@ -620,6 +351,65 @@ class TestCommands:
flags=2,
)
def test_ticks_recent(
self,
tmp_path: Path,
mock_client: MagicMock,
) -> None:
"""Test ticks-recent command."""
output = tmp_path / "out.csv"
result = runner.invoke(
app,
[
"-o",
str(output),
"ticks-recent",
"--symbol",
"EURUSD",
"--seconds",
"120",
"--date-to",
"2024-01-02",
"--count",
"500",
"--flags",
"ALL",
],
)
assert result.exit_code == 0, result.output
mock_client.copy_ticks_from_as_df.assert_called_once_with(
symbol="EURUSD",
date_from=datetime(2024, 1, 2, tzinfo=UTC) - timedelta(seconds=120),
count=500,
flags=1,
)
mock_client.copy_ticks_range_as_df.assert_not_called()
def test_minimum_margins(
self,
tmp_path: Path,
mock_client: MagicMock,
) -> None:
"""Test minimum-margins command."""
sym = MagicMock(volume_min=0.01)
account = MagicMock(currency="USD")
tick = MagicMock(ask=1.1010, bid=1.1000)
mock_client.symbol_info.return_value = sym
mock_client.account_info.return_value = account
mock_client.symbol_info_tick.return_value = tick
mock_client.order_calc_margin.side_effect = [12.5, 12.4]
mock_client.mt5.ORDER_TYPE_BUY = 0
mock_client.mt5.ORDER_TYPE_SELL = 1
output = tmp_path / "out.csv"
result = runner.invoke(
app,
["-o", str(output), "minimum-margins", "--symbol", "EURUSD"],
)
assert result.exit_code == 0, result.output
mock_client.symbol_info.assert_called_once_with("EURUSD")
mock_client.order_calc_margin.assert_any_call(0, "EURUSD", 0.01, 1.1010)
mock_client.order_calc_margin.assert_any_call(1, "EURUSD", 0.01, 1.1000)
def test_orders(
self,
tmp_path: Path,
@@ -696,6 +486,84 @@ class TestCommands:
assert result.exit_code == 0, result.output
mock_client.history_deals_get_as_df.assert_called_once()
def test_recent_history_deals(
self,
tmp_path: Path,
mock_client: MagicMock,
) -> None:
"""Test recent-history-deals command."""
output = tmp_path / "out.csv"
result = runner.invoke(
app,
[
"-o",
str(output),
"recent-history-deals",
"--hours",
"6",
"--date-to",
"2024-01-02",
"--symbol",
"EURUSD",
],
)
assert result.exit_code == 0, result.output
mock_client.history_deals_get_as_df.assert_called_once_with(
date_from=datetime(2024, 1, 1, 18, tzinfo=UTC),
date_to=datetime(2024, 1, 2, tzinfo=UTC),
group=None,
symbol="EURUSD",
ticket=None,
position=None,
)
@pytest.mark.parametrize(
("filename", "reader"),
[
("summary.csv", "csv"),
("summary.json", "json"),
("summary.db", "sqlite3"),
("summary.parquet", "parquet"),
],
)
def test_mt5_summary_export_formats(
self,
tmp_path: Path,
mock_client: MagicMock,
filename: str,
reader: str,
) -> None:
"""Test mt5-summary writes export-safe files for supported formats."""
output = tmp_path / filename
result = runner.invoke(app, ["-o", str(output), "mt5-summary"])
assert result.exit_code == 0, result.output
assert output.exists()
mock_client.version.assert_called_once()
mock_client.terminal_info.assert_called_once()
mock_client.account_info.assert_called_once()
mock_client.symbols_total.assert_called_once()
if reader == "csv":
frame = pd.read_csv(output)
elif reader == "json":
with output.open() as f:
records = json.load(f)
frame = pd.DataFrame(records)
elif reader == "sqlite3":
with sqlite3.connect(output) as conn:
frame = pd.read_sql( # type: ignore[reportUnknownMemberType]
"SELECT * FROM data",
conn,
)
else:
frame = pd.read_parquet(output)
assert len(frame) == 1
assert frame.iloc[0].to_dict() == {
"version": "[5,0,1]",
"terminal_info": '{"connected":true,"paths":["terminal.exe"]}',
"account_info": '{"limits":{"modes":["demo"]},"login":123}',
"symbols_total": 42,
}
def test_version(
self,
tmp_path: Path,
@@ -931,7 +799,7 @@ class TestCallback:
mock_client = MagicMock()
mock_client.account_info_as_df.return_value = pd.DataFrame({"a": [1]})
mocker.patch(
"mt5cli.cli.Mt5DataClient",
"mt5cli.sdk.Mt5DataClient",
return_value=mock_client,
)
mock_config = mocker.patch("mt5cli.cli.Mt5Config")
@@ -984,7 +852,7 @@ class TestCallback:
{"s": ["EURUSD"]},
)
mocker.patch(
"mt5cli.cli.Mt5DataClient",
"mt5cli.sdk.Mt5DataClient",
return_value=mock_client,
)
output = tmp_path / "out.db"
@@ -1090,7 +958,7 @@ def _build_history_client(mocker: MockerFixture) -> MagicMock:
client.history_orders_get_as_df.side_effect = _orders
client.history_deals_get_as_df.side_effect = _deals
mocker.patch("mt5cli.cli.Mt5DataClient", return_value=client)
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
return client
@@ -1393,7 +1261,7 @@ class TestCollectHistory:
assert all(row[0] not in {0, 1} for row in cash)
# Position 100 (BUY 1@1.10 + BUY 3@1.20 then SELL 4@1.50) is closed.
# Position 200 (BUY 2@2.00 then SELL 2@2.20) is closed.
# Position 300 (open-only) and 400 (reversal-only) are excluded.
# Position 400 (reversal-only with non-trade deal type) stays excluded.
assert set(positions) == {100, 200, 500, 600}
pos_100 = positions[100]
tol = 1e-9
@@ -1410,10 +1278,10 @@ class TestCollectHistory:
assert abs(pos_500[5] - 1.05) < tol
pos_600 = positions[600]
assert abs(pos_600[1] - 3.0) < tol
assert abs(pos_600[2] - 3.0) < tol
assert abs(pos_600[2] - 4.0) < tol # reversal + close volumes
assert abs(pos_600[3] - 1.0) < tol
assert abs(pos_600[4] - 1.10) < tol
assert abs(pos_600[5] - 1.40) < tol
assert abs(pos_600[5] - 3.5475) < tol
assert pos_600[6] == 1
def test_collect_history_filters_history_symbols_exactly(
@@ -1431,7 +1299,7 @@ class TestCollectHistory:
"ticket": [3, 4],
"symbol": ["EURUSD", "EURUSDm"],
})
mocker.patch("mt5cli.cli.Mt5DataClient", return_value=client)
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
output = tmp_path / "history.db"
result = runner.invoke(
app,
@@ -1519,9 +1387,9 @@ class TestCollectHistory:
client.copy_ticks_range_as_df.return_value = pd.DataFrame({"x": [1]})
client.history_orders_get_as_df.return_value = pd.DataFrame({"x": [1]})
client.history_deals_get_as_df.return_value = pd.DataFrame({"x": [1]})
mocker.patch("mt5cli.cli.Mt5DataClient", return_value=client)
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
output = tmp_path / "history.db"
with caplog.at_level(logging.WARNING, logger="mt5cli.cli"):
with caplog.at_level(logging.WARNING, logger="mt5cli.sdk"):
result = runner.invoke(
app,
[
@@ -1559,7 +1427,7 @@ class TestCollectHistory:
client = MagicMock()
client.copy_rates_range_as_df.return_value = pd.DataFrame({"time": [1]})
client.history_deals_get_as_df.return_value = pd.DataFrame()
mocker.patch("mt5cli.cli.Mt5DataClient", return_value=client)
mocker.patch("mt5cli.sdk.Mt5DataClient", return_value=client)
output = tmp_path / "history.db"
result = runner.invoke(
app,
@@ -1598,7 +1466,7 @@ class TestCollectHistory:
) -> None:
"""Test that --with-views warns when history_deals is not written."""
output = tmp_path / "history.db"
with caplog.at_level(logging.WARNING, logger="mt5cli.cli"):
with caplog.at_level(logging.WARNING, logger="mt5cli.sdk"):
result = runner.invoke(
app,
[
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+1934
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File diff suppressed because it is too large Load Diff
+443
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@@ -0,0 +1,443 @@
"""Tests for mt5cli.utils module."""
from __future__ import annotations
import json
import sqlite3
from datetime import UTC, datetime
from typing import TYPE_CHECKING
import pandas as pd
import pytest
if TYPE_CHECKING:
from pathlib import Path
from mt5cli.utils import (
DATETIME_TYPE,
REQUEST_TYPE,
TICK_FLAG_MAP,
TICK_FLAGS_TYPE,
TIMEFRAME_MAP,
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_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 integer timeframe."""
assert parse_timeframe("42") == 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", 2), ("TRADE", 4)],
)
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 integer tick flag."""
assert parse_tick_flags("7") == 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_has_expected_keys(self) -> None:
"""Test that TIMEFRAME_MAP contains standard timeframes."""
for key in ("M1", "M5", "M15", "M30", "H1", "H4", "D1", "W1", "MN1"):
assert key in TIMEFRAME_MAP
def test_tick_flag_map_has_expected_keys(self) -> None:
"""Test that TICK_FLAG_MAP contains standard flags."""
assert set(TICK_FLAG_MAP) == {"ALL", "INFO", "TRADE"}
@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_passthrough(self) -> None:
"""Test that integer values pass through unchanged."""
assert TIMEFRAME_TYPE.convert(42, None, None) == 42
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)
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_passthrough(self) -> None:
"""Test that integer values pass through unchanged."""
assert TICK_FLAGS_TYPE.convert(7, None, None) == 7
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
+4 -4
View File
@@ -487,7 +487,7 @@ wheels = [
[[package]]
name = "mt5cli"
version = "0.3.0"
version = "0.6.0"
source = { editable = "." }
dependencies = [
{ name = "click" },
@@ -836,11 +836,11 @@ wheels = [
[[package]]
name = "pygments"
version = "2.19.2"
version = "2.20.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" }
sdist = { url = "https://files.pythonhosted.org/packages/c3/b2/bc9c9196916376152d655522fdcebac55e66de6603a76a02bca1b6414f6c/pygments-2.20.0.tar.gz", hash = "sha256:6757cd03768053ff99f3039c1a36d6c0aa0b263438fcab17520b30a303a82b5f", size = 4955991, upload-time = "2026-03-29T13:29:33.898Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" },
{ url = "https://files.pythonhosted.org/packages/f4/7e/a72dd26f3b0f4f2bf1dd8923c85f7ceb43172af56d63c7383eb62b332364/pygments-2.20.0-py3-none-any.whl", hash = "sha256:81a9e26dd42fd28a23a2d169d86d7ac03b46e2f8b59ed4698fb4785f946d0176", size = 1231151, upload-time = "2026-03-29T13:29:30.038Z" },
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[[package]]