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EdgarTools

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by dgunning

EdgarTools 是无需 API 密钥即可解析 SEC EDGAR 财报的开源 Python 库。

这个工具解决了金融数据获取的痛点——直接让 AI 读取结构化财报，比如让 Claude 分析苹果的 10-K 文件。适合量化分析师或金融开发者快速构建数据管道。但注意，它依赖 SEC 网站稳定性，高峰期可能延迟。

1.9kGitHub

什么是 EdgarTools？

EdgarTools 是无需 API 密钥即可解析 SEC EDGAR 财报的开源 Python 库。

README

<p align="center"> <a href="https://github.com/dgunning/edgartools"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/edgartools-logo.png" alt="EdgarTools Python SEC EDGAR library logo" height="80"> </a> </p> <h1 align="center">EdgarTools - Python Library for SEC EDGAR Filings</h1> <h3 align="center">The simplest, most complete Python library for SEC EDGAR data</h3> <p align="center"> <a href="https://pypi.org/project/edgartools"><img src="https://img.shields.io/pypi/v/edgartools.svg" alt="PyPI - Version"></a> <a href="https://github.com/dgunning/edgartools/actions"><img src="https://img.shields.io/github/actions/workflow/status/dgunning/edgartools/python-hatch-workflow.yml" alt="GitHub Workflow Status"></a> <a href="https://www.codefactor.io/repository/github/dgunning/edgartools"><img src="https://www.codefactor.io/repository/github/dgunning/edgartools/badge" alt="CodeFactor"></a> <a href="https://github.com/pypa/hatch"><img src="https://img.shields.io/badge/%F0%9F%A5%9A-Hatch-4051b5.svg" alt="Hatch project"></a> <a href="https://github.com/dgunning/edgartools/blob/main/LICENSE"><img src="https://img.shields.io/github/license/dgunning/edgartools" alt="GitHub"></a> <a href="https://pypi.org/project/edgartools"><img src="https://img.shields.io/pypi/dm/edgartools" alt="PyPI - Downloads"></a> </p> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-ai-native.svg" alt="AI Native"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-10x-faster.svg" alt="10x Faster"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-zero-cost.svg" alt="Zero Cost"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-production-ready.svg" alt="Production Ready"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-open-source.svg" alt="Open Source"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/badges/badge-financial-data.svg" alt="Financial Data"> </p> <p align="center"> <b>Get financial statements, insider trades, fund holdings, and 20+ other filing types as structured Python objects — in a few lines of code. Free and open source.</b> </p>

EdgarTools is a Python library for accessing SEC EDGAR filings as structured data. Parse financial statements, insider trades, fund holdings, proxy statements, and dozens of other filing types with a consistent Python API.

EdgarTools SEC filing data extraction demo

<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p>

Why EdgarTools?

EdgarTools turns SEC filings into Python objects. Every supported form type gives you structured data — not raw HTML, not XML, not JSON dumps. Actual Python objects with properties, methods, and DataFrames.

<table align="center"> <tr> <td align="center" width="33%"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-speed.svg" width="80" alt="Fast"><br> <b>Fast</b><br> Optimized with lxml & PyArrow<br> Smart caching, rate-limit aware </td> <td align="center" width="33%"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-ai.svg" width="80" alt="AI Ready"><br> <b>AI Ready</b><br> Built-in MCP server for Claude<br> LLM-optimized text extraction </td> <td align="center" width="33%"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-quality.svg" width="80" alt="Well Tested"><br> <b>Well Tested</b><br> 1000+ verification tests<br> Type hints throughout </td> </tr> <tr> <td align="center" width="33%"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-xbrl.svg" width="80" alt="XBRL Support"><br> <b>XBRL Native</b><br> Full XBRL standardization<br> Cross-company comparisons </td> <td align="center" width="33%"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-data.svg" width="80" alt="20+ Filing Types"><br> <b>20+ Filing Types</b><br> Typed objects for every form<br> Pandas-ready DataFrames </td> <td align="center" width="33%"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/icon-community.svg" width="80" alt="Open Source"><br> <b>Open Source</b><br> MIT license, free forever<br> No API keys, no rate limits </td> </tr> </table> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p>

How It Works

<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/how-it-works.svg" alt="How EdgarTools Python library extracts SEC EDGAR filing data"> </p> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/sections/section-quick-start.svg" alt="Quick Start"> </p>
python
pip install edgartools

from edgar import *
set_identity("your.name@example.com")

# Get a company's balance sheet
balance_sheet = Company("AAPL").get_financials().balance_sheet()

# Browse a company's filings
company = Company("MSFT")

# Parse insider transactions
filings = company.get_filings(form="4")
form4 = filings[0].obj()

Apple SEC Form 4 insider transaction data extraction with Python

<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p>

Use Cases

Analyze 13F Institutional Holdings & Hedge Fund Portfolios

Track what hedge funds and institutional investors own by parsing SEC 13F filings. EdgarTools extracts complete portfolio holdings with position sizes, values, and quarter-over-quarter changes.

python
from edgar import get_filings
thirteenf = get_filings(form="13F-HR")[0].obj()
thirteenf.holdings  # DataFrame of all portfolio positions

Institutional Holdings guide →

Track Insider Trading with SEC Form 4

Monitor insider buying and selling activity from SEC Form 4 filings. See which executives are purchasing or selling shares, option exercises, and net position changes.

python
company = Company("TSLA")
form4 = company.get_filings(form="4")[0].obj()
form4.transactions  # Insider buy/sell transactions

Insider Trades guide →

Extract Financial Statements from 10-K and 10-Q Filings

Get income statements, balance sheets, and cash flow statements from SEC annual and quarterly reports. Data is parsed from XBRL with standardized labels for cross-company comparison.

python
financials = Company("MSFT").get_financials()
financials.balance_sheet()   # Balance sheet with all line items
financials.income_statement()  # Revenue, net income, EPS

Financial Statements guide →

Parse 8-K Current Reports for Corporate Events

Access material corporate events as they happen -- earnings releases, acquisitions, executive changes, and more. EdgarTools parses 8-K filings into structured items with full text extraction.

python
eightk = get_filings(form="8-K")[0].obj()
eightk.items  # List of reported event items

Current Events guide →

Query XBRL Financial Data Across Companies

Access structured XBRL financial facts for any SEC filer. Query specific line items like revenue or total assets over time, and compare across companies using standardized concepts.

python
facts = Company("AAPL").get_facts()
facts.to_pandas("us-gaap:Revenues")  # Revenue history as DataFrame

XBRL Deep Dive →

<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/sections/section-features.svg" alt="Key Features"> </p>

Comprehensive SEC Data Access

<table> <tr> <td width="50%" valign="top">

Financial Statements (XBRL)

  • Balance Sheets, Income Statements, Cash Flows
  • Individual line items via XBRL tags
  • Multi-period comparisons with comparative periods
  • Standardized cross-company data
  • Automatic unit conversion
  • Metadata columns (dimensions, members, units)
  • Complete dimensional data support

Fund & Investment Data

  • 13F institutional holdings & portfolio analysis
  • N-PORT fund portfolio data
  • N-MFP money market fund holdings
  • N-CSR/N-CEN fund reports
  • Position tracking over time

Company Dataset & Reference Data

  • Industry and state filtering
  • Company subsets with metadata
  • Standardized industry classifications
  • SEC ticker/CIK lookups
  • Exchange information

Insider Transactions

  • Form 3, 4, 5 structured data
  • Transaction history by insider
  • Ownership changes
  • Grant and exercise details
  • Automatic parsing
</td> <td width="50%" valign="top">

Filing Intelligence

  • Any form type (10-K, 10-Q, 8-K, S-1, etc.)
  • Complete history since 1994
  • Typed data objects for 20+ form types
  • HTML to clean text extraction
  • Section extraction (Risk Factors, MD&A)
  • Subsidiaries (EX-21) and auditor extraction

Performance & Reliability

  • Configurable rate limiting (enterprise mirrors supported)
  • Custom SEC data sources (corporate/academic mirrors)
  • Smart caching (30-second fresh filing cache)
  • Robust error handling
  • SSL verification with fail-fast retry
  • Type hints throughout
  • Enterprise configuration →

Developer Experience

  • Intuitive, consistent API
  • Pandas DataFrame integration
  • Rich terminal output
  • 1000+ tests
</td> </tr> </table>

EdgarTools supports all SEC form types including 10-K annual reports, 10-Q quarterly filings, 8-K current reports, 13F institutional holdings, Form 4 insider transactions, proxy statements (DEF 14A), S-1 registration statements, N-CSR fund reports, N-MFP money market data, N-PORT fund portfolios, Schedule 13D/G ownership, Form D offerings, Form C crowdfunding, and Form 144 restricted stock. Parse XBRL financial data, extract text sections, and convert filings to pandas DataFrames.

<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p>

Comparison with Alternatives

EdgarTools is a Python library that talks directly to SEC EDGAR. sec-api is a hosted API service that returns JSON. Both parse SEC filings — the difference is how you work with the data.

EdgarToolssec-apiRaw EDGAR
What it isPython libraryREST API serviceDIY
CostFree (MIT)$49+/moFree
Data formatTyped Python objectsJSONRaw XML/HTML
Parsed filing types24 (10-K, 8-K, 13F, N-PORT, proxy, etc.)15+ structured APIs—
Financials<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-check.svg" width="20"> Parsed + standardized<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-check.svg" width="20"> Parsed (XBRL-to-JSON)<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-cross.svg" width="20">
Full-text search<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-check.svg" width="20"> via EFTS<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-check.svg" width="20"><img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-cross.svg" width="20">
AI/MCP integration<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-check.svg" width="20"><img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-cross.svg" width="20"><img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-cross.svg" width="20">
LanguagePythonAnyAny
Open source<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-check.svg" width="20"><img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/compare-cross.svg" width="20"> ProprietaryN/A
<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/sections/section-ai-integration.svg" alt="AI Integration"> </p>

Use EdgarTools with Claude Code & Claude Desktop

EdgarTools includes an MCP server and AI skills for Claude Desktop and Claude Code. Ask questions in natural language and get answers backed by real SEC data.

  • "Compare Apple and Microsoft's revenue growth rates over the past 3 years"
  • "Which Tesla executives sold more than $1 million in stock in the past 6 months?"
<details> <summary><b>Setup Instructions</b></summary>

Option 1: AI Skills (Recommended)

Install the EdgarTools skill for Claude Code or Claude Desktop:

bash
pip install "edgartools[ai]"
python -c "from edgar.ai import install_skill; install_skill()"

This adds SEC analysis capabilities to Claude, including 3,450+ lines of API documentation, code examples, and form type reference.

Option 2: MCP Server

Run EdgarTools as an MCP server for any AI client -- Claude Desktop, Cline, or your own containerized deployment.

Add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

json
{
  "mcpServers": {
    "edgartools": {
      "command": "uvx",
      "args": ["--from", "edgartools[ai]", "edgartools-mcp"],
      "env": {
        "EDGAR_IDENTITY": "Your Name your.email@example.com"
      }
    }
  }
}

Requires uv. Alternatively, pip install "edgartools[ai]" and use python -m edgar.ai.

See AI Integration Guide for complete documentation.

</details> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p>

<img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/icons/emoji-heart.svg" width="24" height="24"> Support This Project

EdgarTools replaces hundreds of hours of SEC parsing work — and it costs nothing to use. No API keys, no subscriptions, no rate limits. Free infrastructure for anyone working with SEC data.

But it doesn't maintain itself. The SEC updates filing formats every year. XBRL taxonomies change. New form types appear. One maintainer keeps all of it working, and your support makes that sustainable.

Sponsors aren't just giving back — you're investing in a shared resource and helping shape what gets built next.

<p align="center"> <a href="https://github.com/sponsors/dgunning" target="_blank"> <img src="https://img.shields.io/badge/sponsor-30363D?style=for-the-badge&logo=GitHub-Sponsors&logoColor=#EA4AAA" alt="GitHub Sponsors" height="40"> </a> &nbsp;&nbsp; <a href="https://www.buymeacoffee.com/edgartools" target="_blank"> <img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" height="40"> </a> </p>

What your support enables:

  • Continued maintenance as SEC formats evolve
  • New filing types and data objects
  • Fast bug fixes and community support
  • Free access for everyone, forever

Corporate sponsors: If your team depends on EdgarTools for compliance, financial analysis, or data pipelines, GitHub Sponsors offers tiers designed for organizations with mission-critical dependencies.

<p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/dividers/divider-hexagons.svg" alt=""> </p> <p align="center"> <img src="https://raw.githubusercontent.com/dgunning/edgartools/main/docs/images/sections/section-community.svg" alt="Community & Support"> </p>

Documentation & Resources

Get Help & Connect

Contributing

Contributions welcome:

  • Code: Fix bugs, add features, improve documentation
  • Examples: Share interesting use cases and examples
  • Feedback: Report issues or suggest improvements
  • Spread the Word: Star the repo, share with colleagues

See our Contributing Guide for details.

Professional Services

Need help building production SEC data infrastructure? The creator of EdgarTools offers consulting for teams building financial AI products:

  • SEC Data Sprint (1–3 days) — Working prototype on your data
  • Architecture Review (1–2 weeks) — Pipeline audit with prioritized fixes
  • Pipeline Build (2–4 weeks) — Production-ready code, tests, and handoff

Learn more →

<p align="center"> EdgarTools is distributed under the <a href="LICENSE">MIT License</a> </p>

Star History

Star History Chart

<!-- mcp-name: io.github.dgunning/edgartools -->

常见问题

EdgarTools 是什么？

Open-source SEC EDGAR toolkit — 11 tools, 7 prompts, every filing type. No API key required.

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