@Marvin I have a flow that skips the wait_for blocks when I submit it through the prefect API, however when I run locally with dashboard connected it works just fine; I checked that both versions use the same code; what could be the cause?

It appears there are no open GitHub issues related to

wait_for

blocks skipping. The behavior you're experiencing could be influenced by several factors: 1. Execution Environment: Your local environment might have different settings or packages installed compared to the Prefect API runtime. 2. Configuration Settings: Check if there are configuration differences between the local setup and API execution. This can include environment variables, Prefect configurations, or even differences in how the flow is being triggered. 3. Version Discrepancy: Ensure that the Prefect versions are the same in both environments. There might be underlying changes between versions that could affect the execution of

wait_for

blocks. Consider checking the Prefect version used in the API. 4. API Specific Issues: Sometimes, running flows via the API can lead to different behaviors due to how the platform manages flows. It might be triggering the flow with flags or parameters that alter its runtime behavior. To help you further, I can check the latest version of Prefect using my tools to ensure you are not dealing with a version-specific bug and provide you with some documentation excerpts related to

wait_for

blocks for more insights. Would you like me to do that?

@Marvin yes please

It seems there was an error while trying to fetch the latest version of Prefect. However, I have obtained information regarding blocks in Prefect: Blocks are a primitive within Prefect that enable the storage of configuration and provide an interface for interacting with external systems. With blocks, you can securely store credentials for authenticating with services like AWS, GitHub, Slack, and any other system you'd like to orchestrate with Prefect. Blocks expose methods that provide pre-built functionality for performing actions against an external system. They can be used both for configuring flow deployments and directly within your flow code. For configuration that will change between flow runs, it is recommended to use parameters instead of blocks. Unfortunately, I was not able to find specific documentation on

wait_for

blocks directly. However, based on the general information on blocks, here are some steps you can take to troubleshoot the issue: 1. Ensure Version Consistency: Try to ascertain and ensure that the Prefect version is consistent across environments. 2. Review Configuration: Compare configurations between the local and API environments. 3. Testing: Experiment with different configurations to see if any specific changes impact the behavior of

wait_for

blocks in the API environment. 4. Logs and Debugging: Check the logs for any clues that might hint at why the blocks are being skipped. Debugging could provide more insight into the flow's execution path. If the problem persists, consider reaching out to the Prefect community or submitting an issue on the Prefect GitHub repository detailing your specific issue, environment setup, flow configuration, and any relevant logs or error messages.

@Marvin I noticed the remote runs show camel case parameters and the locally run show the snake case ones in the UI

The difference in case conventions for parameters between the remote runs and the local runs might hint at a serialization or versioning issue where the way parameters are handled or represented differs. Here are a few steps that could help you diagnose and potentially resolve this inconsistency: 1. Double-check Version Matching: Make sure that both your local environment and the remote Prefect instance are not only using the same Prefect version but also the same version of any relevant libraries, especially those that deal with serialization and deserialization of data. 2. Inspect Serialization Process: Look into how your flow parameters are serialized for submission to the Prefect API and deserialized upon execution. It's possible that different serialization methods are being employed in the two environments. 3. Review API Documentation: Consult the Prefect API documentation to see if there are noted differences or requirements for parameter naming conventions when submitting flows through the API. 4. Compare Configurations: Look for differences in any configuration files (

prefect.config

) or environment variables that might affect how parameters are processed. 5. Examine Flow Code: Ensure that the way parameters are defined and accessed within your flow code does not inadvertently change their case. This might happen if there is some code that is executing conditionally based on environment detection. 6. Prefect Community or Support: If the behavior persists and you're unable to resolve it, consider discussing the issue with the Prefect community or reaching out to Prefect support for assistance. You might need to adjust your flow or the interfacing code that submits your flow to ensure consistent handling of parameter names across both local and remote executions.