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Structured financial data from SEC EDGAR filings — 10-Q, 10-K, and 8-K

Project description

edgar-parser

Structured financial data from SEC EDGAR filings.

Give your Python application access to income statements, balance sheets, cash flows, and qualitative sections from 10-Q, 10-K, and 8-K filings — parsed directly from SEC EDGAR with no third-party data vendor required.

This isn't a raw EDGAR scraper. The library handles XBRL namespace resolution, fiscal period matching, current vs. prior period alignment, sign normalization, and fuzzy metric lookup — so you get clean, analysis-ready data.

What it does

Core Extraction (parse_filing)

  • Parses iXBRL facts from 10-Q and 10-K filings on SEC EDGAR
  • Resolves XBRL namespaces, units, scales, and dimensional qualifiers
  • Enriches facts with presentation roles and negated-label sign flipping

Period Matching (match_filing)

  • Aligns current and prior period values for each financial line item
  • Handles quarterly, full-year, and 4Q (derived annual) modes
  • Zip-matching with adaptive fallback to fuzzy matching for edge cases

8-K Earnings Extraction (earnings_8k) — optional, requires anthropic

  • Extracts financial data from 8-K earnings press releases using Claude
  • Automatic fallback when 10-Q/10-K is not yet available for a period
  • Same output schema as core extraction for seamless integration

Filing Sections (section_parser)

  • Parses qualitative sections from 10-K/10-Q filings (Risk Factors, MD&A, Business, etc.)
  • Summary and full-text modes with configurable word limits

High-Level Tools (tools)

  • get_financials(ticker, year, quarter) — all facts for a filing period
  • get_filings(ticker, year, quarter) — list available filings (10-Q, 10-K, 8-K)
  • get_metric(ticker, year, quarter, metric_name) — single metric lookup with fuzzy matching
  • get_filing_sections(ticker, year, quarter) — qualitative section text

Install

pip install edgar-parser

For 8-K earnings extraction (uses Claude API):

pip install "edgar-parser[llm]"

Quick start

from edgar_parser.tools import get_financials, get_metric

# Get all financial facts from Apple's Q1 2025 10-Q
result = get_financials("AAPL", 2025, 1)
for fact in result["facts"][:5]:
    print(f"{fact['metric']}: {fact['current_value']}")

# Look up a single metric
revenue = get_metric("AAPL", 2025, 1, "Revenue")
print(f"Revenue: {revenue['value']} {revenue['unit']}")

Or use the lower-level API for more control:

from edgar_parser import parse_filing, match_filing

# Parse raw XBRL facts
parsed = parse_filing("AAPL", 2025, 1, full_year_mode=False)

# Match current vs. prior periods
matched = match_filing(parsed)
print(matched.head())

Key functions

Function Module Description
get_financials tools All facts for a ticker/period, with caching
get_filings tools List SEC filings (10-Q, 10-K, 8-K) for a period
get_metric tools Single metric lookup with fuzzy matching
get_filing_sections tools Qualitative section text (Risk Factors, MD&A, etc.)
parse_filing pipeline Low-level XBRL fact extraction
enrich_filing pipeline Fiscal period categorization and enrichment
match_filing matching Current vs. prior period alignment
find_8k_for_period earnings_8k Find 8-K earnings release for a fiscal period

Requirements

  • Python 3.10+
  • No API key needed — data comes directly from SEC EDGAR (public)
  • Optional: ANTHROPIC_API_KEY environment variable for 8-K extraction

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