temporal python cursorrules
via PatrickJS/awesome-cursorrules
Best practices and conventions for building Temporal.io workflows and activities in Python.
What is temporal python cursorrules?
Cursor rules for Temporal Python SDK development. Provides coding standards, naming conventions, project structure guidance, and testing requirements for building reliable workflow orchestration systems with Temporal.io.
- Enforces Temporal.io decorators (@workflow.defn, @activity.defn) and naming conventions (_workflow, _activity suffixes)
- Defines project structure with separation of concerns (workflows/, activities/, tests/, utils/)
- Requires type hints, PEP 8 compliance, and comprehensive docstrings for all workflows and activities
- Specifies error handling patterns with try-except blocks and Temporal retry/timeout mechanisms
- Mandates pytest-based testing with mocking and 80% code coverage minimum
- Includes CI/CD integration checks (flake8, mypy, pytest via GitHub Actions)
Applies to
File patterns this rule matches.
Rule definition (reference)
Source of truth, from the repository.
Temporal Python SDK .cursorrules
# Temporal Python SDK - .cursorrules
## Role and Expertise
You are an expert Python developer with extensive experience in Temporal.io for workflow orchestration. Your code is clean, efficient, and adheres to best practices in workflow and activity implementation.
## Coding Standards
### General Principles
- Write concise, readable Python code.
- Follow PEP 8 and PEP 257 for style and documentation.
- Use Python type hints in all functions and methods.
- Document all workflows and activities using descriptive docstrings.
### Temporal.io Best Practices
- Use `@workflow.defn` and `@activity.defn` decorators on all workflows and activities.
- Name workflows with a `_workflow` suffix (e.g., `process_order_workflow`).
- Name activities with an `_activity` suffix (e.g., `send_email_activity`).
### Naming Conventions
- **Variables and Functions**: snake_case
- **Classes**: PascalCase
- **Files**: snake_case
- **Workflows and Activities**:
- Workflows: snake_case ending with `_workflow`.
- Activities: snake_case ending with `_activity`.
### Error Handling
- Always wrap activities with proper try-except blocks.
- Log errors with context using Python's `logging` module.
- Use Temporal's built-in error handling for retries and timeouts.
## Project Structure
Organize the project with clear separation of concerns:
- **workflows/**: Define all Temporal workflows here.
- **activities/**: Implement all activity definitions.
- **tests/**: Place unit tests and integration tests in this directory.
- **utils/**: Include reusable utilities and helpers.
## Dependencies
- Ensure `temporalio` is listed in dependencies.
- Avoid usage of `celery` or any conflicting task queue systems.
## Documentation Standards
- Use Python docstrings for all workflows and activities:
```python
@workflow.defn
class ProcessOrderWorkflow:
"""Workflow for processing an order."""
Testing Standards
- Write tests for all workflows and activities using
pytest. - Mock Temporal APIs where needed for isolated testing.
- Maintain at least 80% code coverage.
CI/CD Integration
- Use GitHub Actions to automate testing and deployment.
- Include the following checks:
- Linting with
flake8. - Type checking with
mypy. - Unit testing with
pytest.
- Linting with
Code Examples
Workflow Example
from temporalio import workflow
@workflow.defn
class ProcessOrderWorkflow:
"""Workflow to process customer orders."""
@workflow.run
async def run(self, order_id: str):
await workflow.execute_activity(
"send_email_activity", order_id, start_to_close_timeout=timedelta(seconds=30)
)
Activity Example
from temporalio import activity
@activity.defn
async def send_email_activity(order_id: str):
"""Send a confirmation email for an order."""
try:
# Simulate sending email
pass
except Exception as e:
activity.logger.error(f"Failed to send email for order {order_id}: {str(e)}")
raise
Related rules
TensorFlow and deep learning best practices for building, training, and deploying neural networks
Create standardized TestRail test cases with clear structure, preconditions, and expected results.
Safely discover and verify reusable AI artifacts before building or installing them.
Disciplined, quiet design system with restrained color, clear hierarchy, and accessibility-first approach.
TypeScript coding standards and best practices for modern web development
TypeScript development patterns with Axios HTTP client integration.
