mt5cli/docs/api/index.md

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.

Architecture Overview

The package follows a simple architecture built on top of pdmt5:

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

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 (
    Mt5CliClient,
    collect_history,
    copy_rates_range,
    detect_format,
    export_dataframe,
)

# 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")

# 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.