--- name: clari-local-dev-loop description: 'Set up local development for Clari API integrations with mock data. Use when building forecast dashboards, testing export pipelines, or iterating on Clari data transformations locally. Trigger with phrases like "clari dev setup", "clari local testing", "develop with clari", "clari mock data". ' allowed-tools: Read, Write, Edit, Bash(npm:*), Bash(python3:*), Grep version: 1.0.0 license: MIT author: Jeremy Longshore tags: - saas - revenue-intelligence - forecasting - clari compatibility: Designed for Claude Code --- # Clari Local Dev Loop ## Overview Local development workflow for Clari integrations: mock forecast data for offline testing, schedule recurring exports, and build data transformation pipelines. ## Prerequisites - Completed `clari-install-auth` setup - Python 3.10+ or Node.js 18+ - Local database or data warehouse access for testing ## Instructions ### Step 1: Project Structure ``` clari-integration/ ├── src/ │ ├── clari_client.py # API client wrapper │ ├── export_pipeline.py # Export and transform pipeline │ ├── models.py # Data models for forecast data │ └── config.py # Environment config ├── tests/ │ ├── fixtures/ │ │ ├── forecast_export.json # Sample export response │ │ └── job_status.json # Sample job status │ └── test_pipeline.py ├── .env.local # Dev credentials (git-ignored) ├── .env.example └── requirements.txt ``` ### Step 2: Mock Forecast Data for Testing ```python # tests/fixtures/forecast_export.json MOCK_FORECAST = { "entries": [ { "ownerName": "Jane Smith", "ownerEmail": "jane@example.com", "forecastAmount": 250000, "quotaAmount": 300000, "crmTotal": 180000, "crmClosed": 120000, "adjustmentAmount": 15000, "timePeriod": "2026_Q1" }, { "ownerName": "Bob Johnson", "ownerEmail": "bob@example.com", "forecastAmount": 180000, "quotaAmount": 250000, "crmTotal": 140000, "crmClosed": 90000, "adjustmentAmount": 0, "timePeriod": "2026_Q1" } ] } ``` ### Step 3: Test Pipeline Without API Calls ```python # tests/test_pipeline.py import pytest from src.export_pipeline import transform_forecast_data def test_forecast_aggregation(): data = MOCK_FORECAST result = transform_forecast_data(data) assert result["total_forecast"] == 430000 assert result["total_quota"] == 550000 assert result["attainment_percent"] == pytest.approx(78.2, rel=0.1) assert len(result["reps"]) == 2 def test_handles_empty_export(): result = transform_forecast_data({"entries": []}) assert result["total_forecast"] == 0 ``` ### Step 4: Development Run Script ```bash #!/bin/bash # scripts/dev-export.sh set -euo pipefail source .env.local echo "=== Clari Dev Export ===" python3 src/export_pipeline.py \ --forecast "company_forecast" \ --period "2026_Q1" \ --format json \ --output ./data/latest-export.json echo "Export saved to ./data/latest-export.json" echo "Records: $(jq '.entries | length' ./data/latest-export.json)" ``` ## Error Handling | Error | Cause | Solution | |-------|-------|----------| | Import error | Missing dependency | `pip install -r requirements.txt` | | Empty export | Wrong time period | Use a period with submitted forecasts | | Mock data stale | Schema changed | Re-download a sample from API | | `.env.local` not loading | Missing dotenv | `pip install python-dotenv` | ## Resources - [Clari API Reference](https://developer.clari.com/documentation/external_spec) - [pytest Documentation](https://docs.pytest.org) ## Next Steps See `clari-sdk-patterns` for production-ready API wrappers.