* Add trading session helpers and extend ThrottledHistoryUpdater Introduce mt5cli.trading with mt5_trading_session() for Mt5TradingClient lifecycle management and reusable operational helpers for position-side detection, margin/volume sizing, and protective order price derivation. Extend ThrottledHistoryUpdater to validate inputs before updates and to optionally suppress ValueError, OSError, and missing-method errors without advancing the throttle timestamp. Export the new helpers from mt5cli.__init__, add unit tests with mocked clients, and document migration guidance for downstream projects such as mteor. Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com> * Narrow ThrottledHistoryUpdater suppress_errors handling (#27) * Narrow ThrottledHistoryUpdater suppress_errors for MT5 capability only Remove broad AttributeError/TypeError handling from recoverable errors. Add _is_mt5_client_capability_error() to detect missing history API methods or non-callable client attributes by message and attribute name. Generic AttributeError/TypeError values always propagate even when suppress_errors=True. Update docs and tests accordingly. Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com> * Detect non-callable history client methods in suppress_errors Address review feedback: when a history API attribute exists but is not callable, Python raises a generic TypeError. Inspect the traceback for mt5cli.history client call sites so these capability mismatches are still suppressed without matching all TypeError values. Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com> * Address PR review feedback on trading helpers - Resolve history module path once at import time - Only treat non-callable TypeErrors as capability errors at the raise site - Validate SL/TP ratios in determine_order_limits - Add tests for margin_free edge cases, body-raise shutdown, and internal TypeError propagation - Clarify ThrottledHistoryUpdater suppress_errors docs - Split README migration example into trading vs read-only history sessions Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com> * Tighten protective ratio validation and clamp negative margin_free Add _require_protective_ratio enforcing 0 <= ratio < 1 for SL/TP limits so a ratio of 1.0 cannot produce zero protective prices. Clamp negative margin_free to 0.0 in calculate_margin_and_volume before sizing. Add boundary and negative-margin tests; document constraints in trading API docs. Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com> --------- Co-authored-by: Cursor Agent <cursoragent@cursor.com> Co-authored-by: Daichi Narushima <dceoy@users.noreply.github.com>
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API Reference
This section contains the complete API documentation for mt5cli.
Modules
The mt5cli package consists of the following modules:
CLI
Command-line interface module providing typer-based commands for exporting MetaTrader 5 data to CSV, JSON, Parquet, and SQLite3 formats.
Utils
Utility module providing constants, enums, Click parameter types, and helper functions for parsing and exporting data.
SDK
Programmatic SDK for read-only MetaTrader 5 data collection. Returns pandas DataFrames and provides collect_history for SQLite bulk collection.
Trading
Trading-capable session management and operational helpers built on pdmt5.Mt5TradingClient. Complements the read-only SDK without changing existing Mt5CliClient behavior.
History Collection (SQLite)
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:
- CLI Layer (
cli.py): Typer application with subcommands that delegate to the SDK and export results. - SDK Layer (
sdk.py): Read-only data access functions,Mt5CliClient, andcollect_historyorchestration. - Trading Layer (
trading.py): Trading-capable sessions and operational helpers onMt5TradingClient. - Utils Layer (
utils.py): Constants, enums, custom Click parameter types, parsing helpers, and format detection/export utilities. - Data Layer (via
pdmt5): UsesMt5DataClient,Mt5TradingClient, andMt5Configfrom the pdmt5 package for MetaTrader 5 access.
Usage Guidelines
All modules follow these conventions:
- Type Safety: All functions include comprehensive type hints
- Error Handling: User-friendly error messages via typer
- Documentation: Google-style docstrings with examples
- Validation: Custom Click parameter types for input validation
Quick Start
# Export account information to CSV
mt5cli -o account.csv account-info
# Export EURUSD H1 rates to Parquet
mt5cli -o rates.parquet rates-from --symbol EURUSD --timeframe H1 \
--date-from 2024-01-01 --count 1000
# Export ticks to JSON
mt5cli -o ticks.json ticks-from --symbol EURUSD \
--date-from 2024-01-01 --count 500 --flags ALL
# Export to SQLite3 with custom table name
mt5cli -o data.db --table symbols symbols --group "*USD*"
Python API
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
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
See individual module pages for detailed usage examples and code samples.