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A curated collection of production-ready workflow examples demonstrating various use cases for Render Workflows. Each example is self-contained, deployment-ready, and showcases different patterns and capabilities.
These examples demonstrate how to build robust, scalable workflows using Render's Python SDK. All examples follow best practices for production deployments and include comprehensive documentation.
Render Workflows support both Python and TypeScript. This repo contains Python examples using the render package, deployed as Workflow services on Render.
New to Workflows? Start with Hello World — it covers the core concepts with minimal complexity.
| Example | Use Case | Key Patterns | Extra Dependencies |
|---|---|---|---|
| Hello World | Learn workflow basics with simple number processing | Task definition, subtask calling with ctx.run, basic orchestration | None |
| ETL Job | Process CSV data with validation and statistics | Subtasks, sequential processing, batch operations, data validation | None |
| OpenAI Agent | AI customer support agent with tool calling | Tool calling, nested subtasks (3 levels deep), stateful workflows, dynamic orchestration | openai |
| File Processing | Batch process multiple file formats in parallel | Parallel execution with asyncio.gather(), multi-format handling, aggregation | None |
| Data Pipeline | Multi-source customer analytics pipeline | Parallel extraction, data enrichment, combining parallel + sequential patterns | httpx |
| File Analyzer | API service calling workflow tasks for file analysis | Client SDK + Task SDK, workflow slugs, service separation, FastAPI integration | fastapi, uvicorn |
The simplest possible workflow — learn the fundamentals through simple number processing.
If you're new to Render Workflows, start here. No CSV files, no APIs, no databases — just pure workflow patterns.
Complete Extract, Transform, Load pipeline — process customer data from CSV files with validation, cleaning, and statistical analysis.
Intelligent conversational agent — a customer support bot that can answer questions, look up orders, and process refunds.
Parallel file processing — batch process files from storage, analyze content, and generate consolidated reports.
View File Processing Example →
Multi-source data pipeline — build customer analytics by combining data from user service, transaction service, and analytics platform.
Complete Client SDK + Task SDK integration — a file analysis API with separate workflow and API services.
The only example that shows both Task SDK and Client SDK together — ideal for understanding how to build APIs that call workflow tasks.
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