Files
mt5cli/README.md
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Daichi Narushima efc0de230a fix: stabilize history timestamps and telemetry docs (#100)
* fix: stabilize history timestamps and telemetry docs

* fix: preserve numeric epoch cursors in history SQLite queries

Normalize mixed ISO and unixepoch time values for incremental resume and scoped dedup so legacy numeric rows are not dropped by julianday filters.

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

* Bump version to v1.1.2

* fix: aggregate incremental start timestamps in SQLite

Use MAX on the normalized time expression with GROUP BY so incremental
resume loaders stay O(groups) instead of materializing every history row.

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

* test: parametrize duplicated incremental-start cases in TestIncrementalStart

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

---------

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-07-04 01:03:40 +09:00

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Markdown

# mt5cli
[![CI/CD](https://github.com/dceoy/mt5cli/actions/workflows/ci.yml/badge.svg)](https://github.com/dceoy/mt5cli/actions/workflows/ci.yml)
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
- **Auto-detection**: Format detection from file extensions
- **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
```bash
pip install -U mt5cli MetaTrader5
```
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
mt5cli -o account.csv account-info
# Export EURUSD M1 rates to Parquet
mt5cli -o rates.parquet rates-from --symbol EURUSD --timeframe M1 \
--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 symbols to SQLite3 with custom table name
mt5cli -o data.db --table symbols symbols --group "*USD*"
# Export with connection credentials
mt5cli --login 12345 --password mypass --server MyBroker-Demo \
-o positions.csv positions
```
Run as a Python module:
```bash
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 |
| `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;
```
#### Grafana and telemetry API docs
The shipped Grafana helpers are documented in [`docs/api/grafana.md`](docs/api/grafana.md), including `publish_grafana_copy()` for creating a WAL-safe published SQLite copy for Grafana.
OpenTelemetry metrics are documented in [`docs/api/telemetry.md`](docs/api/telemetry.md), including `enable_otel_metrics()`, `configure_metrics()`, the `mt5cli[otel]` extra, and `OTEL_EXPORTER_OTLP_ENDPOINT`.
### 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
- Python 3.11+
- 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
git clone https://github.com/dceoy/mt5cli.git
cd mt5cli
uv sync
```
## License
[MIT](LICENSE)