---
id: scholarly
version: "1.7.11"
license: Unlicense
license_treatment: permissive
maintenance: active
---

# scholarly — Simple access to Google Scholar authors and citations

License: permissive · Maintenance: active · Downloads: 364.0K/mo

## What it is and what it does

scholarly is a Python scraper that queries Google Scholar to retrieve author profiles, publication records, and citation metadata in a programmatic, dictionary-based format. It handles the mechanics of web requests, HTML parsing, and result iteration so you can focus on the academic data rather than HTTP details.

The package wraps requests, httpx, beautifulsoup4, and bibtexparser to extract structured fields like author names, publication titles, citation counts, and venue information. It includes proxy support via free-proxy and fake-useragent to work around Google Scholar's rate-limiting and IP blocking, though the documentation warns that certain query types (like citedby and search_pubs) will trigger blocking without proxies. Tor support exists but is deprecated and unsupported.

Use it for:

- Build a researcher profile aggregator that collects publication lists and citation metrics from Google Scholar for a list of author names.
- Extract bibliographic data from Scholar search results to populate a local academic database or bibliography tool.
- Track citation counts and related papers for a specific publication to monitor its academic impact over time.
- Automate literature review workflows by scraping Scholar results for papers matching a research topic.
- Generate citation networks by querying who has cited a particular paper and extracting their metadata.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

scholarly retrieves author profiles, publication metadata, and citation information from Google Scholar without requiring CAPTCHA solving, using web scraping with proxy support.

Yes, if you need programmatic access to Google Scholar data and can manage proxy configuration. The package is actively developed, has no known vulnerabilities, and carries a permissive license. However, expect to invest time in proxy setup (required for heavy queries) and be aware that the last PyPI release is from early 2023, so test compatibility with your use case before relying on it in production.

## Install

pip install scholarly
uv add scholarly
poetry add scholarly

## Installing scholarly

Before you install: Low friction installation with a pure-Python wheel and 12 runtime dependencies. The package is actively maintained with a recent commit on 2026-03-24, though the latest release on PyPI dates to 2023-01-16, creating a gap between development activity and published versions.

License in practice: Released under the Unlicense, a permissive public-domain-equivalent license that places no restrictions on use, modification, or redistribution—suitable for any project type.

Quickstart:

pip install scholarly

from scholarly import scholarly
search_query = scholarly.search_author('Steven A Cholewiak')
first_author = next(search_query)
author = scholarly.fill(first_author)
print(author['publications'])

Google Scholar actively blocks scrapers; queries like citedby() and search_pubs() will trigger IP blocking unless you configure a proxy via ProxyGenerator before making requests.

Verify before relying:

- Whether the 1306-day gap since the 2023-01-16 release indicates maintenance slowdown or stable API compatibility.
- Current reliability of free-proxy and fake-useragent dependencies for evading Google Scholar's anti-bot measures.
- Whether Tor support (deprecated since v1.5) is still functional or should be avoided.

## Package facts

- License: Unlicense (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: active
- Downloads: 364.0K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

google scholar scraping python, academic author metadata extraction, citation data retrieval, scholar profile lookup, publication information api, academic database scraper, scholar.google.com automation, web-scraping, academic-data, google-scholar

[View on SkillFed](https://skillfed.io/packages/scholarly) · [View on PyPI](https://pypi.org/project/scholarly/)