Jira Analyzer

A powerful analytics tool for visualizing and understanding Jira workflow metrics.

Overview

Jira Analyzer is a web application that provides insightful metrics and visualizations for Jira projects. It helps teams analyze their workflow efficiency by calculating and displaying key performance indicators derived from Jira issue data.

Features

• JQL-Based Analysis: Filter issues using Jira Query Language (JQL) to focus on specific projects, teams, or time periods
• Saved Configurations: Create and save configurations for quick access to frequently used queries
• Comprehensive Metrics:
  • Lead Time: Visualize how long issues take from creation to completion
  • Throughput: Track completion rates over time
  • WIP (Work in Progress): Monitor the number of issues in progress at any given time
  • CFD (Cumulative Flow Diagram): Visualize workflow distribution and identify bottlenecks
  • Cycle Time: Measure the time issues spend in specific workflow states

Architecture

The application consists of:

• Frontend: Built with SolidJS and TailwindCSS, providing a responsive and intuitive user interface
• Backend: Python/FastAPI backend that interfaces with Jira's API and processes metrics
• Dockerized Deployment: Containerized setup with Docker Compose for easy deployment and development
• CI/CD: GitHub Actions workflows for continuous integration and deployment

Development Tools

This repository uses several tools to maintain code quality:

• yamlfmt: YAML formatting tool used to ensure consistent formatting of YAML files
• pre-commit: Hooks for code quality checks before committing
• ESLint/Ruff: Code linting for JavaScript/TypeScript and Python
• Playwright: End-to-end testing framework

Getting Started

Prerequisites

• Docker and Docker Compose
• Jira instance with API access

Installation & Running

1. Clone this repository

2. Create a .env file based on .env.example with your configuration settings

3. Run the application:

   # Production mode
   docker-compose up -d
   
   # Development mode
   docker-compose -f docker-compose.dev.yml up -d

4. Access the application at http://localhost (or the port specified in your .env file)

Development Setup

For development, the application provides:

• Hot-reloading for both frontend and backend
• Debugging ports for Python (5678) and Node.js (9229)
• Mock Jira API option for testing without a real Jira instance

# Start in development mode
docker-compose -f docker-compose.dev.yml up -d

# Run tests
make test

# Run E2E tests
make e2e-tests

License

This project is licensed under the terms in the LICENSE file.

Repository Structure

• frontend/: SolidJS frontend application
• backend/: Python/FastAPI backend application
• e2e-tests/: End-to-end tests using Playwright
  • Contains Test Performance Guidelines for optimizing test execution
• .github/: GitHub Actions workflows and configuration
  • Contains detailed GitHub Actions documentation

E2E Testing

The project includes comprehensive end-to-end tests using Playwright. These tests verify theapplication's functionality from a user's perspective.

Test Performance Optimizations

We've implemented several optimizations to improve E2E test performance:

• Page Object Pattern: Using an optimized page object model that reduces timeouts and improves reliability
• Test Categorization: Tests are tagged as @slow or @fast to allow selective execution
• Reduced Wait Times: Consolidated wait operations and optimized verification steps
• Selective Screenshots: Taking screenshots only at critical points to reduce overhead

For more details, see the Test Performance Guidelines.

Running E2E Tests

# Run all tests
make e2e-tests

# Run only fast tests
cd e2e-tests && npx playwright test --grep-invert "@slow"

# Run only slow tests
cd e2e-tests && npx playwright test --grep "@slow"

# Run tests with visual feedback
cd e2e-tests && npx playwright test --headed