Read and analyze SEC EDGAR filings in Python. 10-K, 8-K, XBRL financials, Form 3/4/5, 13F, ADV — clean API, well-typed, MIT-licensed.
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Jun 12, 2026 - Python
Read and analyze SEC EDGAR filings in Python. 10-K, 8-K, XBRL financials, Form 3/4/5, 13F, ADV — clean API, well-typed, MIT-licensed.
Python SDK for SEC & EDGAR data — API access and bulk dataset downloads for 20M+ filings, insider trades, 13F holdings, financial statements, exec comp, enforcement actions, material contracts, registration statements & prospectuses, bond & credit agreements, investment advisers, proxy voting, XBRL-to-JSON, real-time streaming, full-text search...
Node.js SDK for SEC & EDGAR data — API access and bulk dataset downloads for 20M+ filings, insider trades, 13F holdings, financial statements, exec comp, enforcement actions, material contracts, registration statements & prospectuses, bond & credit agreements, investment advisers, proxy voting, XBRL-to-JSON, real-time streaming, full-text search...
Parse SEC EDGAR HTML documents into a tree of elements that correspond to the visual (semantic) structure of the document.
Korean DART + SEC EDGAR filings as structured Python data for company analysis
edgarParser helps you parse and analyze SEC filings from the EDGAR database
EDGAR Analytics – Python Library for Extracting, Analyzing, and Forecasting SEC EDGAR Filings. Streamline your financial analysis with comprehensive metrics, growth rates, and automated reporting capabilities.
all 10-K MD&A (management discussion and analysis) 1993-2021
A Python script to automatically download the latest 10-K financials and Management Reports from the SEC.
Unofficial wrapper for the sec-api.io API. Search & filter SEC filings.
A Telegram bot that monitors SEC filings (10-K, 10-Q, 8-K) and insider trading (Form 4) for a configurable list of tickers. Command-triggered via natural language. Powered by OpenRouter free LLMs. Runs on Android (Termux) or any Linux machine.
A Python tool for extracting stock repurchase program data from SEC 10-Q and 10-K filings
From-scratch replication of Loughran & McDonald (2011) — SEC 10-K sentiment analysis with the LM Master Dictionary, Fama-MacBeth regressions on filing-period excess returns.
A metric explorer for SaaS companies
MCP server for SEC EDGAR: filings search, 10-K/8-K reading, XBRL facts, insider trades. Hosted on Cloudflare Workers.
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