insidertracker 0.1.0

Python wrapper for OpenInsider.com

openinsider

A Python wrapper for OpenInsider.com that scrapes SEC Form 4 insider trading data and caches it locally in DuckDB.

Installation

pip install openinsider

Quick Start

from openinsider import OpenInsider

insider = OpenInsider()

# Insider trades for one or more tickers
df = insider.ticker.get_insider_trades("AAPL")
df = insider.ticker.get_insider_trades(["AAPL", "TSLA", "NVDA"])

# Latest cluster buys (multiple insiders buying the same stock)
df = insider.cluster_buys.get_cluster_buys()

# CEO/CFO purchases over $25k (high-signal)
df = insider.ceo_cfo_purchases_25k.get_ceo_cfo_purchases_25k()

Endpoints

Attribute	Method	Source Page
ticker	get_insider_trades(ticker)	Screener filtered by ticker
ticker	get_insider_sales(ticker)	Same, filtered to sales only
cluster_buys	get_cluster_buys()	/latest-cluster-buys
insider_purchases	get_insider_purchases()	/insider-purchases
insider_sales	get_insider_sales()	/insider-sales
insider_purchases_25k	get_insider_purchases_25k()	/latest-insider-purchases-25k
ceo_cfo_purchases_25k	get_ceo_cfo_purchases_25k()	/latest-ceo-cfo-purchases-25k
ceo_cfo_sales_100k	get_ceo_cfo_sales_100k()	/latest-ceo-cfo-sales-100k
top_officer_purchases_week	get_top_officer_purchases_week()	/top-officer-purchases-of-the-week
screener	get(**kwargs)	/screener with full filter support

All methods return a Polars DataFrame.

Common Parameters

All endpoint methods accept these optional parameters:

Parameter	Type	Description
stale_threshold	timedelta	How old cached data can be before re-fetching
force_update	bool	Bypass cache and always re-fetch
min_date	datetime	Only return rows with filing_date after this date
max_date	datetime	Only return rows with filing_date before this date

import datetime as dt

df = insider.cluster_buys.get_cluster_buys(
    stale_threshold=dt.timedelta(days=1),
    force_update=False,
    min_date=dt.datetime(2025, 1, 1, tzinfo=dt.timezone.utc),
    max_date=dt.datetime(2025, 12, 31, tzinfo=dt.timezone.utc),
)

Screener

The screener module exposes the full OpenInsider screener with 30+ filter parameters:

df = insider.screener.get(
    ticker="AAPL",
    transaction_value_min_usd_thousands=100,
    filing_date_within_days=30,
    page_size=200,
)

Data Schema

Ticker / Latest Purchase & Sale endpoints

Column	Type	Description
filing_date	TIMESTAMPTZ	SEC filing timestamp
trade_date	DATE	Date the trade occurred
ticker	VARCHAR	Stock symbol
company_name	VARCHAR	Company name
insider_name	VARCHAR	Name of the insider
title	VARCHAR	Insider's role (CEO, CFO, Dir, etc.)
trade_type	VARCHAR	e.g. S - Sale, P - Purchase
price	DOUBLE	Trade price per share
quantity	DOUBLE	Number of shares traded
owned	DOUBLE	Shares owned after trade
ownership_change	DOUBLE	Fractional change in ownership (e.g. -0.20)
value	DOUBLE	Total value of trade in USD

Cluster Buys

Same as above, with insider_name and title replaced by:

Column	Type	Description
industry	VARCHAR	Industry classification
num_insiders	VARCHAR	Number of insiders who bought

Database

Data is cached in a local DuckDB database. The path is resolved in this order:

1. OPENINSIDER_DB environment variable
2. database key in the config file
3. Default: ~/.config/openinsider/openinsider.db (Linux), ~/Library/Application Support/openinsider/openinsider.db (macOS), %APPDATA%\openinsider\openinsider.db (Windows)

To use a custom path:

export OPENINSIDER_DB=/path/to/my.db

Or create a config file at the platform default config path:

{
  "database": "/path/to/my.db"
}

Individual Classes

You can import and use each module independently without going through OpenInsider:

from openinsider import CeoCfoPurchases25k

ceo = CeoCfoPurchases25k()
df = ceo.get_ceo_cfo_purchases_25k(force_update=True)