/edgartools

name: edgartools
description: Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings.
license: MIT
metadata:
    skill-author: K-Dense Inc.

edgartools — SEC EDGAR Data

Python library for accessing all SEC filings since 1994 with structured data extraction.

Authentication (Required)

The SEC requires identification for API access. Always set identity before any operations:

from edgar import set_identity
set_identity("Your Name your.email@example.com")

Set via environment variable to avoid hardcoding: `EDGAR_IDENTITY="Your Name your@email.com"`.

Installation

uv pip install edgartools
# For AI/MCP features:
uv pip install "edgartools[ai]"

Core Workflow

Find a Company

from edgar import Company, find

company = Company("AAPL")        # by ticker
company = Company(320193)         # by CIK (fastest)
results = find("Apple")           # by name search

Get Filings

# Company filings
filings = company.get_filings(form="10-K")
filing = filings.latest()

# Global search across all filings
from edgar import get_filings
filings = get_filings(2024, 1, form="10-K")

# By accession number
from edgar import get_by_accession_number
filing = get_by_accession_number("0000320193-23-000106")

Extract Structured Data

# Form-specific object (most common approach)
tenk = filing.obj()              # Returns TenK, EightK, Form4, ThirteenF, etc.

# Financial statements (10-K/10-Q)
financials = company.get_financials()     # annual
financials = company.get_quarterly_financials()  # quarterly
income = financials.income_statement()
balance = financials.balance_sheet()
cashflow = financials.cashflow_statement()

# XBRL data
xbrl = filing.xbrl()
income = xbrl.statements.income_statement()

Access Filing Content

text = filing.text()             # plain text
html = filing.html()             # HTML
md = filing.markdown()           # markdown (good for LLM processing)
filing.open()                    # open in browser

Key Company Properties

company.name                     # "Apple Inc."
company.cik                      # 320193
company.ticker                   # "AAPL"
company.industry                 # "ELECTRONIC COMPUTERS"
company.sic                      # "3571"
company.shares_outstanding       # 15115785000.0
company.public_float             # 2899948348000.0
company.fiscal_year_end          # "0930"
company.exchange                 # "Nasdaq"

Form → Object Mapping

| Form | Object | Key Properties | |------|--------|----------------| | 10-K | TenK | `financials`, `income_statement`, `balance_sheet` | | 10-Q | TenQ | `financials`, `income_statement`, `balance_sheet` | | 8-K | EightK | `items`, `press_releases` | | Form 4 | Form4 | `reporting_owner`, `transactions` | | 13F-HR | ThirteenF | `infotable`, `total_value` | | DEF 14A | ProxyStatement | `executive_compensation`, `proposals` | | SC 13D/G | Schedule13 | `total_shares`, `items` | | Form D | FormD | `offering`, `recipients` |

**Important:** `filing.financials` does NOT exist. Use `filing.obj().financials`.

Common Pitfalls

• `filing.financials` → AttributeError; use `filing.obj().financials`
• `get_filings()` has no `limit` param; use `.head(n)` or `.latest(n)`
• Prefer `amendments=False` for multi-period analysis (amended filings may be incomplete)
• Always check for `None` before accessing optional data

Reference Files

Load these when you need detailed information:

• **[companies.md](references/companies.md)** — Finding companies, screening, batch lookups, Company API
• **[filings.md](references/filings.md)** — Working with filings, attachments, exhibits, Filings collection API
• **[financial-data.md](references/financial-data.md)** — Financial statements, convenience methods, DataFrame export, multi-period analysis
• **[xbrl.md](references/xbrl.md)** — XBRL parsing, fact querying, multi-period stitching, standardization
• **[data-objects.md](references/data-objects.md)** — All supported form types and their structured objects
• **[entity-facts.md](references/entity-facts.md)** — EntityFacts API, FactQuery, FinancialStatement, FinancialFact
• **[ai-integration.md](references/ai-integration.md)** — MCP server setup, Skills installation, `.docs` and `.to_context()` properties