# GeneralMills/pytrends

Pseudo API for Google Trends

Repository: https://github.com/GeneralMills/pytrends
Canonical: https://ross.abutalabs.com/products/pytrends
Language: Python
License: NOASSERTION
License Family: other
Archived: true
Last push: 2024-08-10T16:13:40+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4347, "days_push": 753, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3730, forks 889 (observed 2026-08-28T04:08:15.721065+00:00)

## What it is
Pytrends is an unofficial Python library providing a pseudo API for Google Trends, enabling automated downloading of trend reports. It wraps Google's internal endpoints and returns data as pandas DataFrames.

## Use cases
- download google trends interest over time data
- get interest by region for a keyword
- fetch related topics and related queries
- track trending searches and realtime trends
- analyze keyword popularity over the last 5 years
- export google trends data to pandas for analysis

## When to choose
- you need programmatic access to Google Trends data in Python
- you want trend data as pandas DataFrames for analysis
- you need historical hourly or multirange interest data

## When to avoid
- you need a guaranteed, officially supported API
- you cannot tolerate breakage when Google changes its backend
- you need high-volume scraping without hitting rate limits

## Facets
- artifact type: library
- maturity: maintenance
- function: http-client, web-scraping, data-science, analytics
- domain: analytics, data-science, apis
- platform: python, cross-platform
- tags: google-trends, unofficial-api, trend-analysis, pandas, search

## Member repositories
- GeneralMills/pytrends (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:15.721065+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:29:13.552618+00:00, confidence not recorded.
  - readme: https://github.com/GeneralMills/pytrends (fetched 2026-08-28T04:08:15.721065+00:00, sha 6766bcaf1eec)
- Data as of 2026-08-30T08:39:29.467469+00:00.