Business Intelligence

One Python interface in front of many financial data sources.

A Python research workbench for machine-learning experiments on market data.

It draws a JSON, YAML, XML or CSV file as a diagram that can be zoomed around and searched.

A faster replacement for pandas when the file is large.

Self-installed website analytics with no cookies, running on an existing PostgreSQL database.

One page that links to every service you run and shows live figures from each of them.

A library that assigns each input feature a contribution to each individual model prediction.

Downloads market data from Yahoo Finance into Python tables.

TradingView's own charting library — the chart a forex trader already knows how to read.

Website and product analytics you run yourself, with funnels, retention and session replay, and no cookies.

More than 150 standard chart indicators for Python, computed by the long-established TA-Lib engine.

A browser component for exploring and charting very large or continuously updating tables.

A Python library that extracts hundreds of statistical descriptions from time-ordered data and keeps only the ones related to your target.

It runs thousands of variations of a trading rule over past prices at once.

Tests a trading rule against years of past prices and reports what it would have returned.

A Python library that groups documents by meaning and labels each group with its distinguishing words.

The long-established free library for pricing and risk-managing financial instruments.

Portfolio tearsheets from a returns series — the monthly-returns heatmap that tests the 2%-a-month claim, under a licence he can ship.

Self-hosted web and product analytics with funnels, cohorts and session replay included.

A reporting tool where every page is a Markdown file containing SQL queries and chart components.

Visitor counting that keeps no personal data.

A short way to write a chart, from the makers of D3.

It adds 43 standard technical-analysis indicators as new columns on a table of prices.

Apple's interactive embedding map with automatic cluster labelling — worth studying as a design reference for an overview screen rather than adding as a dependency.

Fast classical forecasting models (ARIMA, ETS, Theta, naive) that give a strategy a floor it has to clear.

A trading test that models the place in the order queue and the delay before an order arrives.

A private server for coding-time statistics, using the editor add-ons that already exist.

Computes the matrix profile of a time series, finding repeated shapes and unusual moments without being told what to look for.

It draws a picture of why one database query is slow.

Charts and reports over a plain-text money ledger you already keep.

A Python library that prices financial derivatives and measures their risk.

Self-hosted visitor counting that works from the server's own records, with no cookies.

Visitor counting you host yourself, with no cookies and no cookie banner.

Display tables in Python with titles, spanners, footnotes and real number formatting — from a pandas or Polars frame.

An admin interface over SQLAlchemy tables, mounted inside a FastAPI or Starlette application.

GroupStats: hand it a DataFrame of many equity curves and get one table of performance statistics for all of them.

A Python library for portfolio allocation, built to the same shape as scikit-learn, with time-aware testing built in.

A small web analytics service that runs on Cloudflare Workers and its Analytics Engine.

It runs SQL queries straight against CSV, JSON and YAML files.

Simple, privacy-first usage figures for phone, desktop and web apps, run on hardware you control.

The standard Python library for measuring market volatility and for testing whether the best of many strategies is real.

A Python wrapper that turns a table of price bars into one where trading indicators are columns.

Time-series forecasting with scikit-learn models, with time-respecting testing built into the core.

A Python library that draws readable, labelled maps of text collections.

A check on whether a trading signal actually predicts returns, before anything is built on it.

Python financial indicators that update as each new price arrives, instead of recalculating the whole series.

Five families of topic model behind one scikit-learn-style API — the head-to-head against BERTopic in one afternoon.

A library that writes readable names for groups of text, at every level of a tree.