render-examples · Borets · Mar 2, 2026 · Mar 2, 2026
diff --git a/README.md b/README.md
@@ -6,7 +6,7 @@ A curated collection of production-ready workflow examples demonstrating various
 
 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 are Python-only (via `render-sdk`) and must be deployed as Workflow services on Render.
+Render Workflows support both Python and TypeScript. This repo contains Python examples using the `render-sdk` package, deployed as Workflow services on Render.
 
 ## Examples
 

diff --git a/data-pipeline/main.py b/data-pipeline/main.py
@@ -494,4 +494,5 @@ async def run_data_pipeline(user_ids: list[str]) -> dict:
         }
 
 
-app.start()
+if __name__ == "__main__":
+    app.start()
diff --git a/etl-job/main.py b/etl-job/main.py
@@ -335,4 +335,5 @@ async def run_etl_pipeline(source_file: str) -> dict:
         }
 
 
-app.start()
+if __name__ == "__main__":
+    app.start()
diff --git a/file-analyzer/api-service/main.py b/file-analyzer/api-service/main.py
@@ -16,7 +16,7 @@
 from typing import Any
 from fastapi import FastAPI, File, UploadFile, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
-from render_sdk import Render
+from render_sdk import RenderAsync
 from render_sdk.client.errors import RenderError, TaskRunError
 from pydantic import BaseModel
 
@@ -62,9 +62,9 @@ class HealthResponse(BaseModel):
 
 
 # Client SDK helper functions
-def get_client() -> Render:
+def get_client() -> RenderAsync:
     """
-    Get Render API client.
+    Get async Render API client.
 
     The Client SDK requires a RENDER_API_KEY environment variable.
     Get your API key from: Render Dashboard → Account Settings → API Keys
@@ -76,7 +76,7 @@ def get_client() -> Render:
             status_code=500,
             detail="RENDER_API_KEY not configured. Get your API key from Render Dashboard → Account Settings → API Keys"
         )
-    return Render()  # Uses RENDER_API_KEY env var automatically
+    return RenderAsync()  # Uses RENDER_API_KEY env var automatically
 
 
 def get_task_identifier(task_name: str) -> str:
@@ -191,26 +191,25 @@ async def analyze_file(file: UploadFile = File(...)):
 
         logger.info(f"Calling workflow task: {task_identifier}")
 
-        # CLIENT SDK CALL: Run the workflow task
-        # Format: client.workflows.run_task(task_identifier, {"arg": value})
-        task_run = await client.workflows.run_task(
+        # CLIENT SDK CALL: Start the workflow task
+        # start_task returns an AwaitableTaskRun immediately
+        started_run = await client.workflows.start_task(
             task_identifier,
             {"file_content": file_content_str}
         )
 
-        logger.info(f"Task started: {task_run.id}")
+        logger.info(f"Task started: {started_run.id}")
 
-        # CLIENT SDK CALL: Await the task completion
-        # This will block until the task finishes
-        result = await task_run
+        # Await the AwaitableTaskRun to wait for completion
+        result = await started_run
 
         logger.info(f"Task completed with status: {result.status}")
 
         return AnalysisResponse(
             task_run_id=result.id,
             status=result.status,
             message=f"File '{file.filename}' analyzed successfully",
-            result=result.results  # Task return value
+            result=result.results
         )
 
     except TaskRunError as e:
@@ -281,16 +280,16 @@ async def analyze_with_custom_task(task_name: str, file: UploadFile = File(...))
 
         logger.info(f"Calling workflow task: {task_identifier}")
 
-        # CLIENT SDK CALL: Run the specified workflow task
-        task_run = await client.workflows.run_task(
+        # CLIENT SDK CALL: Start the specified workflow task
+        started_run = await client.workflows.start_task(
             task_identifier,
             {"file_content": file_content_str}
         )
 
-        logger.info(f"Task started: {task_run.id}")
+        logger.info(f"Task started: {started_run.id}")
 
-        # CLIENT SDK CALL: Await the task completion
-        result = await task_run
+        # Await the AwaitableTaskRun to wait for completion
+        result = await started_run
 
         logger.info(f"Task '{task_name}' completed with status: {result.status}")
 
@@ -325,7 +324,7 @@ async def analyze_with_custom_task(task_name: str, file: UploadFile = File(...))
     import uvicorn
 
     logger.info("Starting File Analyzer API Service")
-    logger.info("This service calls workflow tasks using the Client SDK")
+    logger.info("This service calls workflow tasks using the async Client SDK (RenderAsync)")
     logger.info("Required environment variables:")
     logger.info("  - RENDER_API_KEY: Your Render API key")
     logger.info("  - WORKFLOW_SERVICE_SLUG: Your workflow service slug (e.g., 'file-analyzer-workflows')")

diff --git a/file-analyzer/workflow-service/main.py b/file-analyzer/workflow-service/main.py
@@ -327,4 +327,5 @@ async def analyze_file(file_content: str) -> dict:
     }
 
 
-app.start()
+if __name__ == "__main__":
+    app.start()
diff --git a/file-processing/main.py b/file-processing/main.py
@@ -411,7 +411,6 @@ async def process_file_batch(*file_paths: str) -> dict:
     Returns:
         Dictionary with results for all files
     """
-    # Convert to list for easier handling
     file_paths_list = list(file_paths)
 
     logger.info("=" * 80)
@@ -421,9 +420,7 @@ async def process_file_batch(*file_paths: str) -> dict:
     # Process all files in parallel
     # SUBTASK PATTERN: Call multiple subtasks concurrently using asyncio.gather()
     logger.info("[BATCH] Launching parallel file processing tasks...")
-    # Create list of subtask calls (one per file)
     tasks = [process_single_file(fp) for fp in file_paths_list]
-    # SUBTASK CALLS: Execute all process_single_file subtasks in parallel
     results = await asyncio.gather(*tasks)
 
     # Aggregate results
@@ -513,4 +510,5 @@ async def generate_consolidated_report(batch_result: dict) -> dict:
     return report
 
 
-app.start()
+if __name__ == "__main__":
+    app.start()
diff --git a/hello-world/main.py b/hello-world/main.py
@@ -43,18 +43,6 @@ def double(x: int) -> int:
     Returns:
         The doubled number
     """
-    # Handle case where x might be a dictionary instead of an integer
-    if isinstance(x, dict):
-        if 'x' in x:
-            x = x['x']
-            logger.info(f"[TASK] Extracted x from dictionary: {x}")
-        else:
-            logger.error(f"[TASK] Dictionary input missing 'x' key: {x}")
-            raise ValueError(f"Expected integer or dict with 'x' key, got: {x}")
-    elif not isinstance(x, int):
-        logger.error(f"[TASK] Invalid input type: {type(x)}, value: {x}")
-        raise ValueError(f"Expected integer, got: {type(x)}")
-
     logger.info(f"[TASK] Doubling {x}")
     result = x * 2
     logger.info(f"[TASK] Result: {result}")
@@ -131,7 +119,6 @@ async def process_numbers(*numbers: int) -> dict:
     Returns:
         Dictionary with original numbers and their doubled values
     """
-    # Convert to list for easier handling
     numbers_list = list(numbers)
 
     logger.info(f"[WORKFLOW] Starting: process_numbers({numbers_list})")
@@ -180,7 +167,6 @@ async def calculate_and_process(a: int, b: int, *more_numbers: int) -> dict:
     Returns:
         Dictionary with results from multiple workflow steps
     """
-    # Convert to list for easier handling
     more_numbers_list = list(more_numbers)
 
     logger.info("[WORKFLOW] Starting multi-step workflow")
@@ -206,4 +192,5 @@ async def calculate_and_process(a: int, b: int, *more_numbers: int) -> dict:
     return final_result
 
 
-app.start()
+if __name__ == "__main__":
+    app.start()
diff --git a/openai-agent/main.py b/openai-agent/main.py
@@ -482,7 +482,6 @@ async def multi_turn_conversation(*messages: str) -> dict:
     Returns:
         Dictionary with full conversation and all responses
     """
-    # Convert to list for easier handling
     messages_list = list(messages)
 
     logger.info("=" * 80)
@@ -522,4 +521,5 @@ async def multi_turn_conversation(*messages: str) -> dict:
     }
 
 
-app.start()
+if __name__ == "__main__":
+    app.start()