SEC EDGAR — filings, financials, full-text search

SEC EDGAR is the free, authoritative source for US corporate disclosure: 10-K/10-Q/8-K filings, standardized XBRL financial facts (cross-company comparable), insider trades (Form 4), institutional holdings (13F), proxy statements, and full-text search across everything. No API key — just a User-Agent header. It is the corporate-finance backbone the ZeroPaper pipeline uses for governance, disclosure, and fundamentals work. This page is the distilled access recipe.

• Cost: free, no paywall, no key.
• Auth: none — but a descriptive User-Agent header is mandatory.
• Coverage: all US public-company filings; XBRL facts from ~2009.
• Home: https://www.sec.gov/edgar · API: https://data.sec.gov · Full-text: https://efts.sec.gov

Access

Option 1 — edgartools (preferred — structured data)

# pip install edgartools
from edgar import Company, set_identity

# Identity = your User-Agent. Required by the SEC. Keep it in .env, not here.
set_identity("Your Name your@email.edu")

company = Company("AAPL")                 # ticker → CIK resolved for you
tenks = company.get_filings(form="10-K")
filing = tenks[0]
print(filing.filing_date, filing.accession_no)

facts = company.get_facts()               # XBRL, cross-company comparable
revenue = facts.to_pandas("us-gaap:Revenues")

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

Option 2 — Direct REST API (no package)

import requests
headers = {"User-Agent": "Your Name your@email.edu"}  # mandatory

# All filings + metadata for a company (note 10-digit zero-padded CIK):
requests.get("https://data.sec.gov/submissions/CIK0000320193.json",
             headers=headers).json()

# One XBRL concept across time:
requests.get("https://data.sec.gov/api/xbrl/companyconcept/"
             "CIK0000320193/us-gaap/Revenues.json", headers=headers).json()

# Full-text search:
requests.get("https://efts.sec.gov/LATEST/search-index?"
             "q=%22climate+risk%22&forms=10-K", headers=headers).json()

Store the name/email in .env (e.g. SEC_EDGAR_NAME, SEC_EDGAR_EMAIL); never hard-code them.

Gotchas (the ones that bite pipelines)

The reason to read this page rather than the SEC docs. Verified against live endpoints on the date above.

• No User-Agent → HTTP 403. This is the #1 EDGAR failure. A request with no (or a default python-requests) User-Agent is rejected outright — confirmed 403 live. Always send a descriptive Name email string.
• Rate limit: 10 requests/second, hard. edgartools throttles for you; for the direct API add time.sleep(0.1) between calls and never parallelize blindly — sustained bursts get the host IP blocked, not just throttled.
• CIK must be 10-digit zero-padded in data.sec.gov URLs (CIK0000320193, not CIK320193 or 320193). edgartools’ Company("TICKER") hides this; the raw API does not.
• Use XBRL for cross-company work, not filing text. Narrative text and table formatting vary by filer and year; us-gaap:* XBRL facts are standardized and comparable. Only parse text when the datum isn’t tagged.
• XBRL coverage starts ~2009 and tag usage drifts: revenue may be us-gaap:Revenues or us-gaap:RevenueFromContractWithCustomerExcludingAssessedTax. Check both.
• Cache aggressively. Save XBRL facts to data/*.parquet and check before re-downloading — re-pulling companyfacts for a panel will blow the rate limit fast.
• Amendments & restatements. 10-K/A supersedes 10-K; a company can restate prior XBRL facts. Pin the accession number when reproducibility matters.

Key filing types

Form	Contents	Use for
10-K	Annual report	Financials, risk factors, business description
10-Q	Quarterly report	Interim financials
8-K	Current report	Material events (M&A, earnings, mgmt changes)
DEF 14A	Proxy statement	Executive comp, board, governance
4	Insider trades	Director/officer buy/sell transactions
13F-HR	Institutional holdings	Quarterly positions of large investors
S-1	IPO registration	Pre-IPO financials, risk factors
SC 13D/G	Beneficial ownership	>5% shareholder positions

Common XBRL facts

Concept	Tag
Revenue	us-gaap:Revenues / us-gaap:RevenueFromContractWithCustomerExcludingAssessedTax
Net income	us-gaap:NetIncomeLoss
Total assets	us-gaap:Assets
Total equity	us-gaap:StockholdersEquity
EPS (basic)	us-gaap:EarningsPerShareBasic
Shares outstanding	us-gaap:CommonStockSharesOutstanding
Cash	us-gaap:CashAndCashEquivalentsAtCarryingValue
Long-term debt	us-gaap:LongTermDebt
R&D expense	us-gaap:ResearchAndDevelopmentExpense

Standard recipes

Panel of fundamentals across firms — loop tickers, pull get_facts(), take the XBRL concept you need, cache each to parquet, then assemble:

from edgar import Company
import pandas as pd

rows = []
for t in ["AAPL", "MSFT", "GOOGL", "AMZN", "META"]:
    rev = Company(t).get_facts().to_pandas("us-gaap:Revenues")
    rows.append({"ticker": t, "rev_latest": rev.iloc[-1] if len(rev) else None})
df = pd.DataFrame(rows)

Full-text search for a research topic — efts.sec.gov/LATEST/search-index returns hit counts and snippets; use it to scope a sample before downloading filings (data["hits"]["total"]["value"]).

Insider-trading study — iterate a company’s Form 4 filings and read .obj().transactions (a DataFrame of trades) per filing.

Citation

Cite the filing and source, e.g.: Apple Inc., Form 10-K, fiscal year 2024, filed [date], accession [no.], U.S. Securities and Exchange Commission EDGAR; https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193, accessed YYYY-MM-DD. For XBRL facts, state the concept tag and the filing the value came from.