Python Financial Data Toolkit

A collection of Python scripts designed for fetching, cleaning, and analyzing financial data from various sources, with an initial focus on cryptocurrency and stock market APIs.

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🎯 Project Goals

• Data Acquisition: Provide robust and easy-to-use scripts for fetching historical and real-time financial data (OHLCV, trades, etc.).
• Modularity: Create reusable functions and classes for common data processing tasks.
• Extensibility: Allow easy integration with different data sources (exchanges, financial APIs) and analysis libraries.
• Reliability: Implement proper error handling, rate limiting considerations, and data validation.

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✨ Features (Current)

• Historical OHLCV Fetcher (fetch_data.py):
  • Fetches historical Open, High, Low, Close, Volume (OHLCV) data for cryptocurrencies.
  • Uses the powerful ccxt library to support hundreds of exchanges (defaults to Binance).
  • Handles fetching in batches for large historical data requests.
  • Includes basic rate limit awareness (enableRateLimit).
  • Supports various timeframes (e.g., 1m, 5m, 1h, 1d).
  • Allows fetching data from a specific start date or just the most recent candles.
  • Command-line interface for easy execution.
  • Option to save fetched data to a CSV file.

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🛠️ Setup

1. Clone the Repository:

   git clone [https://github.com/learnonlye/python-financial-data-toolkit.git](https://github.com/learnonlye/python-financial-data-toolkit.git)
   cd python-financial-data-toolkit

2. Create a Virtual Environment (Recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install Dependencies:

   pip install -r requirements.txt

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▶️ Usage Example (fetch_data.py)

The fetch_data.py script can be run from your terminal.

Command Structure:

python fetch_data.py <SYMBOL> [options]