Adding New Sources

Guide for integrating new data sources into the Integrate Pasifika search system. Learn about supported formats, integration process, and best practices.

Extensible

Support for multiple data source types including APIs, HTML scraping, databases, and file-based sources.

Flexible

Modular architecture with specialized handlers for different data formats and integration patterns.

Reliable

Comprehensive testing strategies and error handling for production-ready integrations.

Supported Source Types

Different types of data sources that can be integrated into the system

API Sources

RESTful API integrations

Medium

Features

JSON/XML response formats
Authentication support
Rate limiting handling
Error response parsing

Examples: Pacific Data Hub, Microdata Library

HTML Scraping

Web scraping from HTML pages

High

Features

CSS selector parsing
Dynamic content handling
Anti-bot protection bypass
Content extraction

Examples: Stats Pacific Data, Pacific Map

Database Sources

Direct database connections

Low

Features

SQL query support
Connection pooling
Data transformation
Schema mapping

Examples: PostgreSQL, MySQL

File-based Sources

Local file system data

Low

Features

CSV/JSON file parsing
Batch processing
File monitoring
Data validation

Examples: CSV files, JSON datasets

Integration Process

Step-by-step guide for adding new data sources

Source Analysis

1-2 hours

Analyze the data source structure and requirements

1Identify data format and structure
2Determine authentication requirements
3Assess rate limiting and quotas
4Document API endpoints or URLs

Handler Development

2-4 hours

Create specialized handler for the data source

1Implement source-specific logic
2Add error handling and retries
3Configure circuit breakers
4Set up data transformation

Configuration Setup

30-60 minutes

Configure the source in the system

1Add source to configuration
2Set up authentication credentials
3Configure rate limits
4Define data mapping

Testing & Validation

1-2 hours

Test the integration thoroughly

1Test data retrieval
2Validate response formats
3Check error handling
4Performance testing

Deployment

30-60 minutes

Deploy the new source to production

1Deploy handler code
2Update configuration
3Monitor initial performance
4Document the integration

Supported Data Formats

Data formats that can be processed and integrated

JSON

JavaScript Object Notation

Features

Human readable
Nested structure support
Wide compatibility

Examples: API responses, Configuration files, Data exports

CSV

Comma-Separated Values

Features

Tabular data
Excel compatibility
Simple structure

Examples: Spreadsheet data, Database exports, Statistical data

XML

Extensible Markup Language

Features

Structured data
Schema validation
Hierarchical format

Examples: RSS feeds, Configuration files, Data interchange

GeoJSON

Geographic data format

Features

Spatial data support
Geometry types
Property attributes

Examples: Map data, Location services, Spatial analysis

Best Practices

Guidelines for successful source integration

Data Quality

Validate data before processing
Handle missing or null values
Ensure data consistency
Implement data versioning

Performance

Implement caching strategies
Use pagination for large datasets
Optimize query performance
Monitor response times

Error Handling

Implement comprehensive error handling
Log errors for debugging
Provide meaningful error messages
Use circuit breakers for external APIs

Security

Validate all inputs
Use secure authentication
Implement rate limiting
Protect sensitive data

Testing Strategies

Comprehensive testing approaches for source integration

Unit Testing

Test individual components in isolation

Test Types

Handler function tests
Data transformation tests
Error handling tests
Configuration validation

Tools: Jest, Mocha, Chai, Sinon

Integration Testing

Test source integration end-to-end

Test Types

API endpoint testing
Data flow validation
Error scenario testing
Performance testing

Tools: Supertest, Postman, Newman, RestAssured

Load Testing

Test system performance under load

Test Types

Concurrent request testing
Response time measurement
Resource usage monitoring
Scalability validation

Tools: Artillery, JMeter, K6, Gatling

Monitoring

Continuous monitoring in production

Test Types

Health check monitoring
Error rate tracking
Performance metrics
Alert configuration

Tools: Prometheus, Grafana, Datadog, New Relic