🚀 Welcome to forex_data Documentation

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forex_data is a powerful, professional-grade Python library for aggregating and managing Forex market data in standardized OHLC (Open, High, Low, Close) format. It provides a unified, elegant interface for both historical and real-time data sources, making it effortless to work with multiple data providers and timeframes.

Important

🎯 The Perfect Combination: This package uniquely bridges historical data (20+ years of market history) with real-time updates, giving you comprehensive market coverage through a single, intuitive API.

Tip

New to forex_data? Start with our Quick Start guide to be up and running in minutes!

Key Features

  • 📊 Unified OHLC Format: All data sources return consistent timestamp, open, high, low, close format

  • 🕐 Multiple Timeframes: Easily aggregate data into any timeframe (1m, 5m, 1h, 1D, 1W, etc.)

  • 📈 Historical Data: Access 20+ years of historical data from sources like histdata.com

  • Real-time Data: Get up-to-date market data from Alpha Vantage and Polygon.io

  • 🔍 Conditional Filtering: Filter data directly during retrieval with SQL-like conditions

  • 🚀 High Performance: Built on Polars, PyArrow, or Pandas for lightning-fast data processing

  • 💾 Smart Caching: Intelligent data caching for optimal performance

  • 📉 Built-in Plotting: Visualize candlestick charts with ease

Quick Example

from forex_data import HistoricalManagerDB

# Create a historical data manager
manager = HistoricalManagerDB(
    config='data_config.yaml'
)

# Get hourly data for a date range
data = manager.get_data(
    ticker='NZDUSD',
    timeframe='1h',
    start='2020-01-01',
    end='2020-12-31'
)

# Plot the data
manager.plot(
    ticker='NZDUSD',
    timeframe='1D',
    start_date='2020-01-01',
    end_date='2020-12-31'
)

⚡ Quick Navigation

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📥 Getting Started
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  • Examples - 15+ comprehensive code examples

  • forex_data - Complete API reference documentation

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Additional Information

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