Orchestration-Go

This project includes a local Go installation, so you don't need to install Go system-wide.

Using the Local Go Installation

You can use the provided shell script to run Go commands:

# Run the hello world example
./go.sh run src/main.go

# Build a binary
./go.sh build -o bin/app src/main.go

# Get dependencies
./go.sh mod tidy

# Run any other Go command
./go.sh <command> [arguments]

Project Structure

• goroot/ - Contains the local Go installation
• src/ - Source code
• pkg/ - Package objects
• bin/ - Compiled binaries

CSV Processor API

A high-performance Go web service that processes CSV files, validates royalty percentages and date formats, and converts the data to JSON.

Features

• Fast Parallel Processing: Configurable number of worker goroutines
• Web Interface: Easy-to-use upload form
• REST API: Simple endpoint for programmatic access
• Validation: Checks royalty percentages and date formats
• Containerized: Ready to deploy with Docker

Quick Start with Docker

The easiest way to run the application is with Docker and Docker Compose:

# Build and start the service
make deploy

# Or manually:
docker-compose up -d

This will start the service on port 8080. Access the web interface at http://localhost:8080

Manual Docker Build

# Build the Docker image
docker build -t csv-processor-api .

# Run the container
docker run -p 8080:8080 --name csv-api csv-processor-api

Using the Makefile

The project includes a Makefile with helpful commands:

# Show available commands
make help

# Build Docker image
make build

# Run Docker container
make run-docker

# Stop Docker container
make stop

# Clean up Docker resources
make clean

API Usage

Web Interface

Open http://localhost:8080 in your browser and use the upload form.

API Endpoint

Use the /upload endpoint to programmatically process CSV files:

# Using curl
curl -X POST \
  -F "csvFile=@/path/to/your/file.csv" \
  -F "workers=4" \
  http://localhost:8080/upload > results.json

Expected CSV Format

The CSV file should have the following headers:

Release ID, Release Title, Track ID, Track Title, ISRC, Artist Name, Genre,
Release Date, Label Name, UPC, Language, Explicit, Territories, Rights Holder,
File URL, Royalty Artist %, Royalty Label %, Royalty Distributor %, Royalty Publisher %

Response Format

The API returns a JSON object with two main sections:

1. validation: Validation results for each row, keyed by Track ID
2. conversion: The converted CSV data as an array of objects

Example:

{
  "validation": {
    "TRK001": {
      "release_id": "RLS001",
      "track_id": "TRK001",
      "royalties_sum": true,
      "date_format": true
    },
    ...
  },
  "conversion": [
    {
      "Release ID": "RLS001",
      "Release Title": "Midnight Drive",
      ...
    },
    ...
  ]
}

Building Without Docker

If you have Go installed locally (version 1.22 or later), you can build and run without Docker:

# Using the local go.sh script (if available)
./go.sh run src/main.go

# Or using the standard Go command
go run src/main.go

# Build a binary
go build -o bin/csvapi src/main.go
./bin/csvapi

Deployment

The Docker image is ready for deployment to various cloud platforms:

• AWS ECS/Fargate: Use the provided Dockerfile
• Google Cloud Run: Deploy directly from the Docker image
• Kubernetes: Use the provided Docker image with your K8s configuration
• Digital Ocean App Platform: Deploy directly from the Docker image

Environment Variables

• PORT: The port on which the server will listen (default: 8080)

Testing with Sample Data

The repository includes sample CSV files for testing:

• src/sample-data/sample.csv: A clean sample with valid data
• src/sample-data/sample-with-errors.csv: A sample with validation errors to test error handling

You can use these files to test the application:

# Upload via web interface
# Navigate to http://localhost:8080 and select one of the sample files

# Or using curl
curl -X POST \
  -F "csvFile=@src/sample-data/sample.csv" \
  -F "workers=4" \
  http://localhost:8080/upload > results.json

# Test with invalid data
curl -X POST \
  -F "csvFile=@src/sample-data/sample-with-errors.csv" \
  -F "workers=4" \
  http://localhost:8080/upload > error_results.json

License

MIT License