EdgarTools

Powerful Python library for SEC data analysis and financial research

EdgarTools makes it simple to access, analyze, and extract insights from SEC filings. Whether you're analyzing company financials, tracking insider trading, or researching investment funds, edgartools provides the tools you need.

What You Can Do

Analyze Company Financials

Extract financial statements, calculate ratios, and track performance over time.

company = Company("AAPL")
financials = company.get_financials()
income_statement = financials.income_statement()

Track Insider Trading

Monitor insider transactions from Forms 3, 4, and 5 with structured data objects.

filings = company.get_filings(form="4").head(10)
transactions = pd.concat([f.obj()
                         .to_dataframe()
                         .fillna('')
                for f in filings])

Research Investment Funds

Analyze 13F holdings, track portfolio changes, and compare fund strategies.

fund = Company("BRK-A")
holdings = fund.get_filings(form="13F-HR").latest().obj()

Extract Filing Data

Access any SEC filing since 1994 with clean, structured data extraction.

filing = company.get_filings(form="10-K").latest()
text = filing.text()  # Clean, readable text

Key Features

🚀 Easy to Use

Simple, intuitive API designed for both beginners and experts
Comprehensive documentation with real-world examples
Smart defaults that handle edge cases automatically

📊 Complete SEC Data Access

All filing types: 10-K, 10-Q, 8-K, 13F, Form 4, S-1, and more
Historical data: Access filings back to 1994
Real-time data: Get the latest filings as they're published

🔍 Advanced XBRL Support

Extract structured financial data from XBRL filings
Query individual financial line items with standardized concepts
Handle complex financial statement hierarchies automatically

⚡ Performance Optimized

Efficient data handling for large datasets
Local caching to minimize API calls
Batch processing capabilities for bulk analysis

🛠 Developer Friendly

Type hints and comprehensive error handling
Jupyter notebook integration with rich display
Pandas DataFrames for seamless data analysis

Installation

Install edgartools with pip:

pip install edgartools

Or use uv for faster installation:

uv pip install edgartools

Get Started in 2 Minutes

Install and set your identity (required by SEC):

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

Find a company and get their latest financial data:

company = Company("TSLA")
latest_10k = company.get_filings(form="10-K").latest()
financials = latest_10k.obj().financials()

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Popular Use Cases

Financial Analysis

Compare companies across industries
Track financial performance over time
Calculate and analyze financial ratios
Build custom financial dashboards

Investment Research

Analyze fund holdings and strategy changes
Track insider buying and selling activity
Monitor material events through 8-K filings
Research IPOs and new offerings

Academic Research

Large-scale financial data analysis
Corporate governance studies
Market efficiency research
Regulatory compliance analysis

AI/ML Applications

Extract clean text for natural language processing
Build predictive models with financial data
Automate document analysis workflows
Create training datasets for financial AI

Why Choose EdgarTools?

Feature	EdgarTools	Alternative Solutions
Ease of Use	✅ Simple, Pythonic API	❌ Complex setup required
Data Quality	✅ Clean, standardized data	⚠️ Raw data needs processing
Performance	✅ Optimized for large datasets	❌ Slow for bulk operations
Documentation	✅ Comprehensive with examples	⚠️ Limited examples
Active Development	✅ Regular updates and features	❌ Infrequent updates
Community	✅ Growing user base	⚠️ Limited community