Gitlab Projects Scraper

GitLab Projects Scraper helps you gather repository data, open group details, and project search results. Simply pick your mode, set your item limit, and export clean structured datasets in JSON, CSV, or Excel formats.

Use cases

• Project discovery: Search projects for specific libraries, programming languages, or topics, and export structured lists.
• Shortlisting repositories: Pull star counts, fork metrics, topics, and web URLs for specific project IDs or paths.
• Group lookups: Search groups by name and export their IDs, paths, and web URLs.
• CSV export: Export structured datasets directly to spreadsheets without needing custom tools.
• Scheduled monitoring: Run recurring jobs to keep star counts, fork statistics, and last activity dates up to date.
• Lead & research lists: Collect project names and namespace details for research queues.

Modes

• Projects (search): Search open projects sorted by star counts or recent activity.
• Details (project): Fetch detailed repository metadata for specific project IDs or namespace paths.
• Groups (groups): Search groups by keywords.

Input

Parameter	Type	Default	Description
mode	string	search	Choose between Projects, Details, or Groups mode.
query	string	python	Search text for Projects mode.
orderBy	string	star_count	Sort criteria (star_count or last_activity_at).
projects	array	["278964"]	Project IDs or namespace paths for Details mode.
groups	array	["gnome"]	Keyword list for Groups mode search.
maxItems	integer	100	Target number of successful records to output (Max 1000).
requestDelaySecs	number	1	Delay between consecutive requests. Minimum threshold is 0.12s.
timeoutSecs	integer	300	Maximum runtime before stopping new requests.
requestTimeoutSecs	integer	30	Per-request timeout limit.
userAgent	string	BigiByteActorResearch/1.0	Custom contact identifier string sent with requests.
proxyConfiguration	object	{"useApifyProxy": false}	Optional proxy settings.

Example input

{
  "mode": "search",
  "query": "python",
  "orderBy": "star_count",
  "maxItems": 100,
  "requestDelaySecs": 1,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "userAgent": "BigiByteActorResearch/1.0 (contact: research@bigibyte.com)",
  "proxyConfiguration": { "useApifyProxy": false }
}

What data does this actor extract?

Each successful item represents a project or group record. Descriptions are organized under projectDescription to keep dataset schemas uniform and clean across runs.

{
  "id": 470007,
  "path_with_namespace": "ase/ase",
  "name": "ase",
  "projectDescription": "[Atomic Simulation Environment](https://ase-lib.org): A Python library for working with atoms",
  "web_url": "[https://gitlab.com/ase/ase](https://gitlab.com/ase/ase)",
  "star_count": 516,
  "forks_count": 979,
  "topics": ["Atomistic simulations", "chemistry"],
  "created_at": "2015-09-17T12:32:33.814Z",
  "last_activity_at": "2026-10-10T16:34:42.444Z",
  "namespace_name": "ase",
  "scraped_at": "2026-10-12T00:00:00+00:00"
}

Field	Type	Description
id	integer	Unique identifier. Duplicates in a single run are automatically deduplicated.
path_with_namespace	string	Complete project path or namespace group path.
name	string	Display name.
projectDescription	string	Formatted project description.
web_url	string	Direct web page URL.
star_count	integer	Total star count (when available).
forks_count	integer	Total forks count (when available).
topics	array	Assigned topic labels.
created_at	string	Creation timestamp.
last_activity_at	string	Timestamp of the most recent activity.
namespace_name	string	Full namespace path.
scraped_at	string	UTC timestamp recorded when data was extracted.

If an item encounters an HTTP error (such as a missing repository or invalid ID), it records a clear error row with status details without crashing the entire run.

Pricing & usage limits

The actor software is completely free to use. You only pay for standard Apify platform compute consumption during execution.

maxItems defaults to 100 records and can be configured up to a maximum cap of 1000 items. Execution stops when maxItems is reached or when timeoutSecs expires (default 300 seconds).

How it works

1. Reads your configuration inputs and validates selected modes, keywords, or ID lists.
2. Sends requests sequentially using your specified User-Agent header.
3. Automatically pages through dataset results while removing internal duplicate records.
4. Outputs results smoothly into datasets in structured batches.
5. Logs helpful summary logs detailing items processed, page counts, and warnings upon completion.

FAQ

How many projects can I extract per run? The default cap is set to 100 items and can be adjusted up to 1000 records per run depending on your requirements.

What happens if a project ID is missing or invalid? The actor logs a descriptive status row for that individual record and seamlessly moves on to process the remaining items in your list.

Can I export data as CSV or Excel? Yes, Apify natively supports downloading datasets as CSV, Excel, JSON, XML, or HTML directly from the dataset view after run completion.

Does running a job multiple times create duplicate rows? Within a single execution, duplicate IDs are automatically deduplicated. Successive runs write to new datasets unless merged manually.

Related tools

If you plan to map or join these rows, a data cleanup or CSV formatting pass are the usual next steps. BigiByte builds scrapers and automated tools for developer portals, code platforms, and open data hubs.

Need a scheduled monitor, custom dataset, or tailored extraction pipeline? BigiByte builds custom scrapers and APIs: https://bigibyte.com

Trademark Notice

GitLab Projects and related names, logos, and trademarks belong to their respective owners. Their use in this documentation is solely to identify the target software platform and does not imply affiliation, sponsorship, endorsement, or partnership.

Disclaimer

This Actor is an independent tool developed by BigiByte and is not affiliated with, endorsed by, sponsored by, or otherwise officially associated with GitLab or its parent entities. Users are responsible for adhering to applicable terms, rate guidelines, and licensing standards.

Is web scraping legal?

This Actor only collects web data without bypassing access controls. Scraping publicly available data is generally legal, but how you handle and process the extracted data matters:

• Personal data: If your output data includes personal details (such as names, public handles, or email addresses), data protection laws such as the GDPR or CCPA may apply. Ensure you handle personal data responsibly and lawfully.
• Copyright: Content like project documentation, code, or technical descriptions may be protected under specific licenses or copyright laws. Avoid redistributing full copyrighted content without proper attribution or permission.
• Terms of use: Ensure your request frequencies and usage comply with fair usage standards and platform policies.
• Legal advice: This summary provides general information, not legal advice. Consult legal counsel for specific legal guidance.

For further reading, explore Apify's legal guide: Is web scraping legal?