gitlab-detector 0.1.3

GitLab issue anomaly detection and page generation

GitLab Issue Anomaly Detector

A Python package for detecting anomalies in GitLab issues and generating HTML reports.

Overview

This package analyzes GitLab issues to detect various anomalies such as:

• Missing milestones or iterations
• Insufficient descriptions
• Stale issues
• Blocked issues without details
• And many more

It generates a comprehensive HTML report with interactive visualizations to help teams identify and address these anomalies.

Installation

pip install gitlab-detector

Usage

Command Line

# Run the anomaly detector and generate a report
gitlab-anomaly-detector

Environment Variables

Create a .env file with the following variables:

GITLAB_URL=https://gitlab.com
GITLAB_TOKEN=your_personal_access_token
GITLAB_PROJECT_ID=your_project_id

Viewing the Report

After running the tool, you can view the generated report by starting a local HTTP server:

python -m http.server 8008 -d public/

Then open your browser to http://localhost:8008

Features

Anomaly Detection

• Issue Hygiene: Detect issues with poor descriptions, missing milestones, or missing iterations
• Workflow Impediments: Identify blocked issues, stale issues, and scope creep
• Priority Management: Flag high-priority issues that lack proper attention
• Timeline Analysis: Track issues that are at risk of missing deadlines

Reporting

• Interactive Dashboard: Filter and sort anomalies by type, severity, and owner
• Milestone View: Group anomalies by milestone to identify at-risk deliverables
• Iteration View: Track anomalies within your agile iterations
• Export Functionality: Export data to Excel for further analysis

Testing

This package follows strict test-driven development practices. To run the tests:

# Activate the virtual environment
source .venv/bin/activate

# Run tests with pytest
python -m pytest tests/

Logging

The package implements robust logging throughout the codebase. Logs are output to stdout by default but can be configured via Python's standard logging module.

Example log output:

2025-05-15 22:57:01,584 - scripts.issue_anomaly_detector - DEBUG - Categorized anomaly 'poor_description' as 'hygiene'
2025-05-15 22:57:01,584 - scripts.issue_anomaly_detector - DEBUG - Categorized anomaly 'missing_milestone' as 'hygiene'

GitLab Pages with Dynamic Content

This project includes a custom GitLab CI/CD pipeline for GitLab Pages that generates dynamic content:

1. A prepare-pages stage runs before the pages stage
2. A Python script (scripts/prepare_pages.py) generates dynamic content:
   • Creates a data.json file with timestamp and sample data
   • Updates index.html to load and display the dynamic content
3. The pages stage deploys the generated content

When you push to the main branch, the pipeline automatically runs and deploys your site to GitLab Pages.

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Contributing

Contributions are welcome! Please follow these steps to contribute:

1. Fork the repository
2. Create a feature branch: git checkout -b feature/your-feature-name
3. Commit your changes: git commit -am 'Add some feature'
4. Push to the branch: git push origin feature/your-feature-name
5. Submit a pull request

Development Setup

# Clone the repository
git clone https://gitlab.com/my-group-name2452611/my-project-name.git
cd my-project-name

# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate

# Install development dependencies
pip install -e .[dev]

Coding Standards

This project follows strict test-driven development practices:

• Write tests before implementing features
• Maintain high test coverage
• Implement robust logging throughout the codebase
• Follow PEP 8 style guidelines

License

This project is licensed under the MIT License - see the LICENSE file for details.