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Ai Analytics Python Packages

Python packages with the GitHub topic ai-analytics. Sorted by monthly downloads, with stars and forks.
PostHog
hogql-parser

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.

1.6M 40K 4K
PostHog
deltalite

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.

1.5M 40K 4K
PostHog
hogql-parser-rs

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.

1.5M 40K 4K
duckcode-ai
datalex-cli

Git-native data modeling for dbt users — versioned, reviewable YAML with contracts, lineage, ERDs, and clean round-trip back to dbt.

1K 1 0
PostHog
owners-yaml

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.

884 40K 4K
PostHog
hogli

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.

376 40K 4K
chigwell
yearly-insights-parser

A new package that analyzes user-provided text summaries of yearly breakdowns (e.g., financial reports, project post-mortems, or performance reviews) and extracts structured insights. It uses an LLM t

46 1 0
    • Original data from PyPI, GitHub, and OSV; downloads served through ClickHouse
    • Sources & methodology