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Welcome to FinFetcher

FinFetcher is a robust Python library designed for quantitative analysts and developers who need clean, market-aware historical financial data. It acts as a smart wrapper around yfinance, solving common issues with incomplete daily candles and timezone mismatches.

PyPI version License

🚀 Key Features

  • Market-Aware Cleaning: Automatically identifies if a market is currently open and removes the "unfinished" daily candle to prevent look-ahead bias.
  • Timezone Intelligence: Handles exchange-specific closing times for US Equities, European Markets, Asian Markets, and Crypto (UTC).
  • Target Date Calculation: Automatically computes the next valid trading day (or calendar day for 24/7 assets) for predictive modeling.
  • Robust Error Handling: Custom exceptions for missing tickers, empty data, or connection issues.
  • Multi-Asset Support: Native support for Equities, ETFs, Crypto, Forex, Futures, and Indices.

📦 Installation

Install via pip:

pip install finfetcher

⚡ Quick Start

from finfetcher import DataFetcher

# 1. Initialize
fetcher = DataFetcher("AAPL")

# 2. Fetch clean data
df = fetcher.get_data(period="1y")

# 3. Access results
print(df.tail())
print(f"Prediction Target Date: {fetcher.target_date}")

❓ Why FinFetcher?

Standard data fetching tools often return the current day's data even if the market hasn't closed. For a model trained on "Close" prices, treating a 10:00 AM price as the final "Close" for the day introduces significant noise and bias.

FinFetcher checks the asset's specific exchange hours against the current server time and strictly enforces a "closed-only" policy for the current day's row.