Examples

Everything lives in the repo's examples/ directory: 12 runnable scripts, a live filing tape, and 17 Jupyter notebooks committed with their executed outputs, so GitHub renders every table and chart without you running anything.

All of it works on a free API key (signup); the notebooks additionally need pandas and matplotlib.

Notebooks

In rough order of complexity:

Notebook	What it shows
getting_started	One schema for every filer, client basics, pagination, error handling
insider_analysis	A year of insider trades in pandas, top sellers, monthly volume
institutional_13f	Berkshire's portfolio, largest holders of a stock, manager similarity heatmap
fund_overlap	Portfolio overlap between two 13F managers
activist_radar	Every new 13D stake across the whole market
company_360	One issuer across every dataset
insider_vs_institutions	Insider net buying vs institutional quarter-over-quarter change
form4_price_chart	A price chart reconstructed purely from insider filing prices
form_d_heatmap	Private raises by industry and month
whale_quarter_diff	Berkshire's position changes between quarters
insider_dossier	One insider's full cross-issuer footprint
form144_follow_through	Announced sales (Form 144) vs executed sales (Form 4)
conviction_clone	Concentration-ranked managers and their aggregated best ideas
nport_xray	Fund composition by asset class, country, and fair-value level
mmf_stress	Every money market fund vs the 50% weekly liquidity floor
tenb5_tracker	Insider trades under 10b5-1 plans since the 2023 rule
rate_cycle	The Fed cycle from money market yields, with pass-through regressions

Scripts

Terminal-friendly versions of the common tasks: quickstart, insider activity, 13F holdings, fund portfolios, beneficial ownership, private offerings, financials (statements, metrics, ratios, factors), money market funds, coverage checks, error handling, CSV export, a sqlite changefeed sync, and sec_tape.py, a live tape of filings as they are ingested. See the examples README for the full index.