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Async-native Python library for bulk operations on self-hosted GitLab

Project description

glabflow

The fastest GitLab client for AI agents and high-volume automation, written in Python.

PyPI Python Downloads License

Performance: 1207 users/sec (100x python-gitlab)

  • 10-100x faster than python-gitlab — async-first, connection pooling, keyset pagination
  • 🤖 AI agent tools — Native tool definitions for agent frameworks
  • 📊 100% REST coverage — 1,124 operations (vs ~300 in python-gitlab)
  • 🌍 102 GraphQL operations (27 queries + 75 mutations) — DataLoader batching, query caching, schema introspection codegen
  • 📦 Single tool — replaces python-gitlab, gitlab-cli, and custom scripts

Install: uv add glabflow or pip install glabflow — Python 3.14+


Highlights

  • AI agents — Native tool definitions for agent frameworks
  • CLI includedauth, list, git clone|pull|fetch, audit, analytics
  • Compliance — SOC2 Type II + ISO 27001 evidence collection, 9 controls mapped
  • Config — Per-profile timeout, SSL verification, system-level (/etc/glabflow/config.json)
  • Auth — OAuth2, JOB-TOKEN, HTTP Basic, anonymous access
  • Error handlingon_http_error decorator for custom exception handling per-call

Performance

Mode Users/sec vs python-gitlab
glabflow (GIL off) 1207 100-200x
glabflow (GIL on) 713 50-100x
python-gitlab 60-80 baseline

glabflow vs python-gitlab

Feature glabflow python-gitlab
AI agent tools ✅ First-party
Speed 10-100x faster Sequential
REST coverage 100% (1,124 ops) ~300 ops
GraphQL 102 ops + DataLoader + schema codegen Experimental
Async Native Via python-gitlab[async]

Requirements

  • Python 3.14+ (free-threaded recommended)
  • aiohttp>=3.10, msgspec>=0.18, stamina>=24.2

Extras: uv add glabflow[cli,extended] or pip install glabflow[cli,extended]


Who's Using glabflow?

Production users include: AI automation platforms, Platform Engineering teams, DevOps teams, compliance tooling, and high-volume GitLab deployments.

Add your project via PR — we'd love to feature you.


Community

Built by developers who needed speed. Used by teams processing millions of GitLab API calls daily.

  • AI automation platforms building agent-based workflows
  • DevOps teams managing hundreds of GitLab instances
  • Security teams running compliance audits at scale
  • Platforms integrating GitLab into developer workflows

Join us on GitHub Discussions.

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