Pulling SEC EDGAR Data with Python: A Beginner's Guide

13F Chat — Wed, 14 Oct 2026 14:46:44 +0000

Every quarter the SEC publishes thousands of filings on EDGAR, and all of it is free. If you're a developer curious about finance data, here's what I learned getting started.

1. Identify yourself

EDGAR asks every automated client to send a descriptive User-Agent with a contact email, and to stay under about 10 requests per second. If you skip this you'll get 403s.

import requests
HEADERS = {"User-Agent": "my-research-script you@example.com"}

2. Use the JSON APIs, not HTML scraping

data.sec.gov serves clean JSON:

https://data.sec.gov/submissions/CIK##########.json lists a company's recent filings
https://data.sec.gov/api/xbrl/companyfacts/CIK##########.json returns every XBRL fact (revenue, assets...) the company has reported

CIKs must be zero-padded to 10 digits.

cik = "320193"  # Apple
url = f"https://data.sec.gov/submissions/CIK{cik.zfill(10)}.json"
data = requests.get(url, headers=HEADERS).json()
recent = data["filings"]["recent"]
for form, date in list(zip(recent["form"], recent["filingDate"]))[:10]:
    print(form, date)

3. Know the form types

10-K / 10-Q: annual and quarterly reports
8-K: material events
4: insider transactions
13F-HR: quarterly holdings of large investment managers
SC 13D / 13G: 5%+ ownership stakes

4. Cache everything

Filings never change after they're accepted, so cache responses on disk. You'll stay well within rate limits and iterate faster.

5. Watch the units

XBRL facts come with units (USD, shares, USD/share) and periods (instant vs duration). Mixing a quarterly duration with an annual one is the most common bug I hit.