Matija
07/25/2024, 5:09 PMMarvin
07/25/2024, 5:10 PMdeployment.yaml
File: Ensure any parameters requiring lists are specified correctly. For example:
yaml
parameters:
my_list_param:
- value1
- value2
2. Use Quotes When Specifying Lists in CLI: When you deploy via CLI, wrap your list values in quotes to ensure they are interpreted correctly.
shell
prefect deployment build ./flow.py:flow_function -n my_deploy -p '{"my_list_param": ["value1", "value2"]}'
3. Ensure Correct Flow Definition: Ensure your flow and task definitions are correctly set to handle parameter values passed.
python
from prefect import flow, task
@task
def say_hello():
print("Hello")
@flow
def my_flow():
say_hello()
if __name__ == "__main__":
my_flow()
4. Validate Parameter Types: Validate that parameters meet the expected types, particularly for infrastructure blocks like Kubernetes jobs where list and dictionary structures are required.
5. Check the Prefect Version and Known Issues: Confirm your Prefect version is up-to-date and review known issues which might affect function validations.
For more details, you can refer to:
- Prefect Flow Concepts
- Kubernetes Job Block details (Prefect Issue #7911)
If none of these resolve your issue, consider sharing more specific parts of your code or setup so we can investigate further.Matija
07/25/2024, 5:15 PMMarvin
07/25/2024, 5:15 PMpython
from prefect import flow
@flow(name="Price Scrapper")
def run_spider():
print("TestING")
def main():
run_spider()
if __name__ == "__main__":
main()
2. Review Deployment and Execution:
- When creating and running deployments, make sure to use correct commands especially around parameter passing. A common source of issues is incorrect parameter formatting.
3. Check Prefect Version Compatibility: Ensure all components of Prefect (SDK, UI, etc.) are compatible and up to date.
- You can check the current Prefect version using:
shell
prefect version
4. CLI Command Formatting:
- If using CLI for deployment, ensure list parameters are correctly formatted. CLI commands can sometimes misinterpret JSON parameters.
shell
prefect deployment build ./__main__.py:run_spider -n my_deploy -p '{"list_param": ["value1", "value2"]}'
5. Check Worker Configuration:
- Ensure your workers are configured correctly and accepting task runs. Mismatched worker configurations can cause unexpected errors.
### Additional Resources
- Prefect Documentation: Flow Concepts
- GitHub Issues and Examples: Check for code snippets and example flows Prefect GitHub Issues
If the issue persists, consider sharing more details on your workflow configuration or any custom infrastructure blocks.