Data Pipeline

Build ETL pipelines with Ifa-Lang's functional data processing.

Pipeline Stages

1. Extract - Fetch data from APIs or files
2. Transform - Filter, map, aggregate
3. Load - Write to database or file

Domains Used

• Otura / Net - API data fetching
• Ogunda / List - Data transformations
• Storage / Db - Persistence
• Osa / Async - Parallel processing

Code Example

// ETL Data Pipeline
ese extract() {
    // Fetch from API
    ayanmo response = Otura.gba("https://api.example.com/data");
    ayanmo data = Ika.json_parse(response);
    pada data;
}

ese transform(records) {
    // Filter and map
    ayanmo result = [];
    fun record ninu records {
        ti record.active == otito {
            ayanmo cleaned = {
                id: record.id,
                name: Ika.uppercase(record.name),
                score: record.value * 100
            };
            Ogunda.fi(result, cleaned);
        }
    }
    pada result;
}

ese load(data) {
    // Write to storage
    Storage.set("pipeline_results", data);
    Irosu.fo("Loaded " + Ogunda.len(data) + " records");
}

// Run pipeline
ayanmo raw = extract();
ayanmo processed = transform(raw);
load(processed);