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Integration Architecture Overview

repoindex features a powerful plugin-based integration architecture that allows for extensible functionality through modular components. This document provides an overview of the integration system and available integrations.

Architecture Philosophy

The integration system follows these core principles:

  1. Modularity: Each integration is self-contained with minimal dependencies
  2. Composability: Integrations can work together through standard interfaces
  3. Extensibility: Easy to add new integrations without modifying core code
  4. Performance: Lazy loading and optional features for optimal performance
  5. Standards-based: Uses JSONL for data exchange between components

Integration Types

Core Integrations

Built into repoindex and always available:

  • Git Operations: Repository management, status tracking, synchronization
  • GitHub API: Issues, pull requests, releases, GitHub Pages
  • GitLab API: Projects, merge requests, CI/CD pipelines
  • PyPI: Package detection, version tracking, publishing status
  • Documentation: MkDocs, Sphinx, Jekyll, Hugo support

Advanced Integrations

Powerful analysis and automation features:

Platform Integrations

External service connections:

  • Social Media: Twitter, LinkedIn, Mastodon posting
  • CI/CD: GitHub Actions, GitLab CI, Jenkins
  • Package Registries: PyPI, npm, Maven Central
  • Documentation Hosting: GitHub Pages, Read the Docs, GitLab Pages

Integration Architecture

graph TB
    subgraph "Core System"
        CLI[CLI Commands]
        Core[Core Functions]
        Meta[Metadata Store]
    end

    subgraph "Integration Layer"
        API[Integration API]
        Load[Plugin Loader]
        Reg[Integration Registry]
    end

    subgraph "Integrations"
        Cluster[Clustering]
        Work[Workflow]
        Net[Network Analysis]
        Social[Social Media]
    end

    CLI --> Core
    Core --> Meta
    Core --> API
    API --> Load
    Load --> Reg
    Reg --> Cluster
    Reg --> Work
    Reg --> Net
    Reg --> Social

Standard Integration Interface

All integrations follow a standard interface for consistency:

class Integration:
    """Base class for all repoindex integrations."""

    def __init__(self, config: dict):
        """Initialize with configuration."""
        self.config = config

    def validate(self) -> bool:
        """Validate integration requirements."""
        pass

    def execute(self, data: Generator) -> Generator:
        """Process data stream and return results."""
        pass

    def get_commands(self) -> List[click.Command]:
        """Return CLI commands for this integration."""
        pass

Data Flow

Integrations work with repoindex' streaming architecture:

  1. Input Stream: Receive JSONL data from repoindex commands
  2. Processing: Transform, analyze, or enrich the data
  3. Output Stream: Return JSONL results for further processing
  4. Composition: Chain multiple integrations via Unix pipes

Example pipeline:

# List repos → Filter Python → Cluster → Export
repoindex list | \
  jq 'select(.language == "Python")' | \
  repoindex cluster analyze --stdin | \
  repoindex export markdown --stdin

Configuration

Integrations are configured in ~/.repoindex/config.json:

{
  "integrations": {
    "clustering": {
      "enabled": true,
      "default_algorithm": "kmeans",
      "default_features": ["tech-stack", "size"]
    },
    "workflow": {
      "enabled": true,
      "workflows_dir": "~/.repoindex/workflows",
      "max_parallel": 4
    },
    "network_analysis": {
      "enabled": true,
      "layout": "force-directed",
      "max_nodes": 500
    }
  }
}

Available Integrations

Repository Clustering

Advanced machine learning algorithms for grouping similar repositories:

  • Algorithms: K-means, hierarchical, DBSCAN, spectral clustering
  • Features: Technology stack, code complexity, size, activity
  • Applications: Duplicate detection, portfolio organization, tech debt analysis

Full Documentation →

Workflow Orchestration

YAML-based workflow automation with DAG execution:

  • YAML Workflows: Human-readable workflow definitions
  • DAG Execution: Dependency management and parallel execution
  • Built-in Actions: Rich library of pre-built actions
  • Conditional Logic: If/else conditions and dynamic branching

Full Documentation →

Network Analysis

Visualize and analyze repository relationships:

  • Dependency Graphs: Visualize project dependencies
  • Collaboration Networks: Understand team interactions
  • Technology Landscapes: Map technology usage across projects
  • Interactive Visualizations: D3.js-powered web visualizations

Full Documentation →

Creating Custom Integrations

To create your own integration:

1. Create Integration Module

# repoindex/integrations/myintegration.py
from repoindex.integrations.base import Integration
import click

class MyIntegration(Integration):
    """Custom integration for repoindex."""

    def validate(self):
        """Check if requirements are met."""
        # Check for required tools, configs, etc.
        return True

    def execute(self, repos):
        """Process repository data."""
        for repo in repos:
            # Process each repository
            repo['my_field'] = self.analyze(repo)
            yield repo

    def get_commands(self):
        """Define CLI commands."""
        @click.command()
        @click.option('--option', help='My option')
        def mycommand(option):
            """My integration command."""
            # Implementation
            pass

        return [mycommand]

2. Register Integration

# repoindex/integrations/__init__.py
from .myintegration import MyIntegration

INTEGRATIONS = {
    'myintegration': MyIntegration,
    # ... other integrations
}

3. Add Configuration

{
  "integrations": {
    "myintegration": {
      "enabled": true,
      "option": "value"
    }
  }
}

Integration Best Practices

Performance

  • Lazy Loading: Only load integration when needed
  • Streaming: Process data incrementally, don't load everything into memory
  • Caching: Cache expensive computations when appropriate
  • Parallel Processing: Use multiprocessing for CPU-intensive tasks

Error Handling

  • Graceful Degradation: Continue processing even if some items fail
  • Error Reporting: Output errors as JSONL error objects
  • Validation: Check requirements before execution
  • Recovery: Provide recovery mechanisms for failures

Testing

  • Unit Tests: Test integration logic in isolation
  • Integration Tests: Test interaction with repoindex core
  • Mock External Services: Don't depend on external APIs in tests
  • Performance Tests: Ensure integration scales well

Documentation

  • API Documentation: Document all public methods
  • Usage Examples: Provide clear, runnable examples
  • Configuration Guide: Explain all configuration options
  • Troubleshooting: Common issues and solutions

Integration Lifecycle

  1. Discovery: repoindex discovers available integrations at startup
  2. Registration: Integrations register their commands and capabilities
  3. Configuration: User configuration is loaded and validated
  4. Execution: Integrations are invoked as needed by commands
  5. Cleanup: Resources are properly released after execution

Future Integrations

Planned integrations for future releases:

  • Container Analysis: Docker, Kubernetes configuration analysis
  • Security Scanning: Vulnerability detection and remediation
  • Code Quality: Static analysis and metrics collection
  • Cloud Providers: AWS, Azure, GCP integration
  • Issue Tracking: Jira, Linear, Asana synchronization
  • Time Tracking: Development time and cost analysis
  • AI Assistants: Code review and documentation generation

Getting Help