y-not-finance 1.8.2

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 (Yahoo Finance)

• 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"

📅 Events (Yahoo Finance)

• Dividends and splits
• Multi-ticker support - Retrieve events across multiple tickers
• Consistent output - Returns DataFrame with date index and ticker columns

🏢 Constituents (Web Scrapers)

• 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

🗂️ Constituents (Historical Data)

• Daily S&P 500 constituents - 1980-01-01 to 2025-12-31
• Intraday OHLC - Precomputed 2024 dataset
• Fast access - Downloads once and reads from cached Parquet

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 Events Data

from y_not_finance import YahooFinanceClient

client = YahooFinanceClient()

# Get dividends
dividends_df = client.get_events("AAPL", range_str="5y", event_type="dividends")

# Get splits
splits_df = client.get_events("AAPL", range_str="5y", event_type="splits")

Fetch Index Constituents

from y_not_finance import get_constituents

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

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

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

Fetch Historical Constituents

from y_not_finance.constituents.historical import (
    get_historical_constituents,
    get_intraday_ohlc,
)

# Daily S&P 500 constituents (full history)
df = get_historical_constituents()

# Constituents on a specific date
df_date = get_historical_constituents(date="2024-01-15")

# Intraday OHLC data for 2024
ohlc_df = get_intraday_ohlc()

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
│
├── yahoo_finance/              # Yahoo Finance provider
│   ├── client.py               # YahooFinanceClient (prices + events)
│   ├── core/                   # Shared infrastructure
│   │   ├── http_client.py
│   │   └── exceptions.py
│   ├── prices/                 # Price parsing and constants
│   └── events/                 # Events parsing helpers
│
└── constituents/               # Index constituents provider
    ├── historical/             # Historical constituents + intraday data
    │   ├── client.py            # get_historical_constituents(), get_intraday_ohlc()
    │   └── README.md            # Module documentation
    └── scrapers/               # Web scrapers

See ARCHITECTURE.md for full structure and design rationale.

Documentation

• API_REFERENCE.md - Complete API documentation
• ARCHITECTURE.md - System architecture overview
• CONTRIBUTING.md - Development guidelines
• CHANGELOG.md - Version history

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