Skills Data Science Orchestrating Hex Projects via API

Orchestrating Hex Projects via API

v20260423
hex-core-workflow-a
This skill provides the core mechanism for integrating Hex into external data pipelines. It enables triggering, monitoring, and managing Hex projects (e.g., via Airflow or Dagster) programmatically. Users can implement parameterized runs, execute multi-step ETL workflows sequentially, and handle status polling and error management, making it ideal for production data orchestration.
Get Skill
372 downloads
Overview

Hex Project Orchestration

Overview

Trigger Hex project runs from external orchestration tools (Airflow, Dagster, cron) with input parameters, status polling, and error handling. This is the primary integration pattern for embedding Hex in data pipelines.

Instructions

Step 1: Parameterized Project Runs

import 'dotenv/config';
const TOKEN = process.env.HEX_API_TOKEN!;
const BASE = 'https://app.hex.tech/api/v1';

interface RunConfig {
  projectId: string;
  inputParams?: Record<string, any>;
  updateCache?: boolean;
  killRunning?: boolean;
}

async function triggerRun(config: RunConfig) {
  const response = await fetch(`${BASE}/project/${config.projectId}/run`, {
    method: 'POST',
    headers: { 'Authorization': `Bearer ${TOKEN}`, 'Content-Type': 'application/json' },
    body: JSON.stringify({
      inputParams: config.inputParams || {},
      updateCacheResult: config.updateCache ?? true,
      killRunningExecution: config.killRunning ?? false,
    }),
  });
  if (!response.ok) throw new Error(`Trigger failed: ${response.status} ${await response.text()}`);
  return response.json();
}

Step 2: Synchronous Run Helper

async function runAndWait(config: RunConfig, timeoutMs = 600000): Promise<any> {
  const { runId, projectId } = await triggerRun(config);
  const startTime = Date.now();

  while (Date.now() - startTime < timeoutMs) {
    const res = await fetch(`${BASE}/project/${projectId}/run/${runId}`, {
      headers: { 'Authorization': `Bearer ${TOKEN}` },
    });
    const status = await res.json();

    switch (status.status) {
      case 'COMPLETED': return { success: true, runId, duration: Date.now() - startTime };
      case 'ERRORED': throw new Error(`Run ${runId} errored: ${status.statusMessage || 'unknown'}`);
      case 'KILLED': throw new Error(`Run ${runId} was killed`);
      default: await new Promise(r => setTimeout(r, 5000));
    }
  }
  throw new Error(`Run ${runId} timed out after ${timeoutMs}ms`);
}

Step 3: Pipeline Orchestration

// Run multiple Hex projects in sequence (data pipeline)
async function runPipeline(steps: RunConfig[]) {
  const results = [];
  for (const step of steps) {
    console.log(`Running: ${step.projectId}`);
    const result = await runAndWait(step);
    console.log(`Completed in ${result.duration}ms`);
    results.push(result);
  }
  return results;
}

// Example: ETL pipeline
await runPipeline([
  { projectId: 'extract-project-id', inputParams: { date: '2025-01-01' } },
  { projectId: 'transform-project-id' },
  { projectId: 'load-project-id', updateCache: true },
]);

Step 4: Cancel Long-Running Projects

async function cancelRun(projectId: string, runId: string) {
  const response = await fetch(`${BASE}/project/${projectId}/run/${runId}`, {
    method: 'DELETE',
    headers: { 'Authorization': `Bearer ${TOKEN}` },
  });
  console.log(`Cancelled run ${runId}: ${response.status}`);
}

Error Handling

Error Cause Solution
429 Too Many Requests Rate limit (20/min, 60/hr) Queue runs with delays
Run ERRORED Project code failed Check project logs in Hex UI
Run KILLED Timeout or manual cancel Increase timeout or fix slow queries
404 Project not published Publish project before triggering runs

Resources

Next Steps

For scheduled runs, see hex-core-workflow-b.

Info
Category Data Science
Name hex-core-workflow-a
Version v20260423
Size 3.98KB
Updated At 2026-04-26
Language