y-not-finance 1.0.0

Financial data library for prices and index constituents

Y-Not-Finance

A comprehensive Python library for fetching financial data, combining Yahoo Finance price data with stock index constituents from multiple sources.

Features

📈 Prices Module

• Multi-ticker concurrent fetching - Fetch data for multiple stocks simultaneously
• Automatic retry with exponential backoff - Resilient to API rate limits
• Flexible intervals - Support for intraday (1m, 5m, 15m, 30m, 1h) and daily+ (1d, 1wk, 1mo) data
• Multiple fields - Open, High, Low, Close, Volume, Adjusted Close
• Date range filtering - Easy-to-use range strings like "1mo", "3mo", "1y"

🏢 Constituents Module

• Multiple indexes - S&P 500, NASDAQ, Dow Jones, TSX, and market cap tiers
• Unified API - Single function to access all data sources
• Company names included - Get both ticker symbols and full company names
• Automatic pagination - Handles large datasets seamlessly

Installation

pip install -e .

Or install from requirements:

pip install -r requirements.txt

Quick Start

Fetch Price Data

from y_not_finance import YahooFinanceClient

# Initialize the client
client = YahooFinanceClient()

# Single ticker
df = client.get_prices("AAPL", range_str="1mo")

# Multiple tickers
df = client.get_prices(["AAPL", "MSFT", "GOOGL"], range_str="3mo", fields="close")

# Multiple fields
df = client.get_prices(
    ["AAPL", "MSFT"],
    range_str="1y",
    interval="1d",
    fields=["open", "high", "low", "close", "volume"]
)

Fetch Index Constituents

from y_not_finance import get_constituents

# Get S&P 500 constituents
tickers, description = get_constituents("^SPX", info=True)

# Get TSX constituents
tickers, description = get_constituents("^GSPTSE", include_benchmark=True)

# Get mega cap stocks
tickers, description = get_constituents("megacaps")

Combined Usage

from y_not_finance import YahooFinanceClient, get_constituents

# Get index constituents
sp500_tickers, _ = get_constituents("^SPX")

# Fetch prices for all constituents
client = YahooFinanceClient()
df = client.get_prices(
    list(sp500_tickers.keys()),
    range_str="1mo",
    fields="adjclose"
)

Package Structure

y_not_finance/
├── __init__.py                 # Main package API
│
├── prices/                     # Price data module
│   ├── __init__.py
│   ├── client.py              # YahooFinanceClient class
│   ├── fetcher.py             # HTTP request handling
│   ├── parser.py              # JSON parsing logic
│   ├── processor.py           # DataFrame processing
│   ├── utils.py               # Utility functions
│   └── constants.py           # Configuration constants
│
└── constituents/              # Index constituents module
    ├── __init__.py
    ├── client.py              # get_constituents() function
    ├── config.py              # Index configurations
    ├── utils.py               # Validation utilities
    └── scrapers/              # Data source scrapers
        ├── __init__.py
        ├── stock_analysis.py  # StockAnalysis.com scraper
        └── tsx.py             # Globe and Mail TSX scraper

See PACKAGE_STRUCTURE.md for detailed structure documentation.

Documentation

• QUICK_REFERENCE.md - Common tasks and examples
• ARCHITECTURE.md - System architecture overview
• PACKAGE_STRUCTURE.md - Package layout details

Supported Indexes

Key	Index Name	Source
^SPX	S&P 500 Index	StockAnalysis.com
^DJI	Dow Jones Industrial Average	StockAnalysis.com
^IXIC	NASDAQ Composite	StockAnalysis.com
^GSPTSE	S&P/TSX Composite (Canada)	Globe and Mail
megacaps	Mega Cap Stocks	StockAnalysis.com
largecaps	Large Cap Stocks	StockAnalysis.com
midcaps	Mid Cap Stocks	StockAnalysis.com
smallcaps	Small Cap Stocks	StockAnalysis.com
microcaps	Micro Cap Stocks	StockAnalysis.com
nanocaps	Nano Cap Stocks	StockAnalysis.com

Examples

See the examples/ directory for comprehensive usage examples:

• combined_usage.py - Complete demonstration of all features
• basic_usage.py - Simple price fetching
• financial_analysis.py - Analysis workflows
• data_export.py - Export to CSV/Excel

Run an example:

python examples/combined_usage.py

Requirements

• Python 3.8+
• numpy
• pandas
• requests

Optional:

• pyarrow (for Parquet export in examples)

See requirements.txt for complete dependencies.

License

See LICENSE file for details.

Changelog

Version 1.0.0

• Complete restructure into modular package
• Separated prices and constituents into submodules
• Improved code organization following best practices
• Added comprehensive documentation
• Enhanced error handling and logging