API Reference

Comprehensive API Documentation

Explore our extensive API documentation to seamlessly integrate Inversion into your applications and workflows.

API Overview

Inversion provides a comprehensive set of APIs that allow you to integrate our powerful data processing capabilities into your applications. Our APIs follow RESTful principles and are designed to be intuitive, consistent, and reliable.

Key Features

RESTful and GraphQL interfaces
Secure authentication with API keys and OAuth
Comprehensive SDKs for popular languages
Webhook support for event-driven architectures

Getting Started

To get started with the Inversion API, you'll need to:

Create an Inversion account
Generate API credentials in the dashboard
Choose the appropriate SDK or API endpoint
Make your first API call

REST API

Our RESTful API provides comprehensive access to all Inversion features.

API Endpoints
Authentication
Error Handling
Rate Limiting

Explore REST API

GraphQL API

Our GraphQL API provides flexible querying capabilities for complex data needs.

Schema Reference
Queries
Mutations
Subscriptions

Explore GraphQL API

SDKs

Client libraries for popular programming languages to simplify integration.

JavaScript / TypeScript
Python
Java
Go

API Examples

Example: Data Ingestion

// JavaScript Example
const inversionClient = new InversionClient({
apiKey: 'your-api-key'
});

// Upload a data file for processing
const response = await inversionClient.data.upload({
file: dataFile,
datasetId: 'my-dataset',
options: {
  format: 'csv',
  delimiter: ',',
  hasHeader: true
}
});

console.log(`Data uploaded with ID: ${response.uploadId}`);

This example demonstrates how to upload a data file to Inversion for processing using our JavaScript SDK.

Example: Real-time Processing

# Python Example
from inversion import InversionClient

client = InversionClient(api_key="your-api-key")

# Set up a real-time processing pipeline
pipeline = client.pipelines.create(
  name="real-time-analytics",
  source={
      "type": "stream",
      "connection": "kafka-connection-id",
      "topic": "user-events"
  },
  transformations=[
      {"type": "filter", "field": "event_type", "operator": "equals", "value": "purchase"},
      {"type": "enrich", "using": "user-data", "join_on": "user_id"}
  ],
  destination={
      "type": "dashboard",
      "id": "sales-dashboard"
  }
)

print(f"Pipeline created with ID: {pipeline.id}")
print(f"Status: {pipeline.status}")

This example shows how to set up a real-time processing pipeline using our Python SDK.

API Support

Need help with our API? Our support team is here to assist you with any questions or issues you may encounter.

Developer Community

Join our developer community to connect with other developers, share knowledge, and get help.

Technical Support

Contact our technical support team for assistance with API integration or troubleshooting.