congressional-trades 0.1.0

Scrape and analyze stock trades by members of US Congress

congressional-trades

Scrape and analyze stock trades by members of the US Congress.

Features

• Scrapes directly from official sources (efdsearch.senate.gov)
• Clean, typed Python API
• Local caching for fast repeated queries
• Export to CSV/DataFrame
• Daily updates via GitHub Actions

Installation

pip install congressional-trades

Quick Start

from congressional_trades import get_trades, get_politicians

# Get all recent trades
trades = get_trades()

# Filter by various criteria
trades = get_trades(
    chamber="senate",
    ticker="NVDA",
    start_date="2024-01-01",
    transaction_type="purchase",
)

# Get as pandas DataFrame
df = get_trades(as_dataframe=True)

# List all politicians
politicians = get_politicians(chamber="senate")

CLI Usage

# List recent trades
congressional-trades list --ticker NVDA --since 2024-01-01

# Export to CSV
congressional-trades export trades.csv

# Force refresh from source
congressional-trades refresh

Data Sources

• Senate: efdsearch.senate.gov - Electronic Financial Disclosure
• House: Coming in v2 (PDF parsing required)

Data Model

Each trade includes:

Field	Type	Description
politician	str	Full name
chamber	str	"senate" or "house"
party	str	"D", "R", or "I"
state	str	Two-letter state code
ticker	str	Stock ticker (if resolved)
asset_name	str	Full asset description
transaction_type	str	"purchase", "sale", etc.
transaction_date	date	When trade occurred
disclosure_date	date	When disclosed
amount_min	int	Minimum transaction amount
amount_max	int	Maximum transaction amount

Contributing

Contributions welcome! The biggest need is help with House PDF parsing.

# Development setup
git clone https://github.com/guttu44/congressional-trades
cd congressional-trades
pip install -e ".[dev]"
pytest

License

MIT