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<@ULVA73B9P> In my server I've set PREFECT_RESULTS...
# ask-marvin
s
@Marvin In my server I've set PREFECT_RESULTS_PERSIST_BY_DEFAULT to be True. Why is the state.data still None when awaiting the result?
m
It seems like you're running into an issue where the state data is returning 
None
even though you've set 
PREFECT_RESULTS_PERSIST_BY_DEFAULT
to 
True
. This is a known issue that has come up in the Prefect community, especially after version upgrades. Here’s a quick summary of what has been noted: 1. Configuration Issues: Ensure you've correctly set the configuration in your Prefect server's settings. Double-check the setting using:
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prefect config set PREFECT_RESULTS_PERSIST_BY_DEFAULT=True
2. Prefect Version: This seems to be a more pronounced issue in Prefect 2.7.8, as per a GitHub issue thread (see below). Certain features or bugs might still be evolving in newer versions, so consider checking release notes or updating to a newer stable version if one is available. 3. Execution Context: If you're retrieving the state from an API or running a job that might be interacting with Prefect in an unexpected context, it might cause this anomaly. Prefect's exception often mentions this happening if result persistence is disabled when retrieving state from an API. Here's the GitHub issue that might be related: Missing Result Error. A humorous thought: Maybe the Prefect server, like Marvin, just left its task data on a different server, sighing, "Here I am, brain the size of a planet, and they forget where I put things." Consider reaching out on the Prefect community Slack if this persists after configuration checks. They might have additional insights or specific patches if it's a longer-standing issue.
s
@Marvin This happens in Prefect 3.1.0
m
In Prefect 3.1.0, the management of result persistence might be a bit different from what you're expecting. Based on the documentation, here are some important points to consider: 1. Result Management: Prefect 3.0 introduces a more robust framework for managing results. By default, results are not persisted unless explicitly configured. This might mean even with 
PREFECT_RESULTS_PERSIST_BY_DEFAULT
set to 
True
, additional configuration might be needed. You should ensure that all necessary configurations for result storage, serialization, and naming conventions are correctly set. 2. State Management: Prefect states are rich and carry detailed information about the task or flow run. To fully utilize these features, double-check that the state management aligns with the expected use of result persistence. For further reading, you can check the documentation on results and state management here and here. If your problem persists despite these configurations, it could be a bug or issue not yet documented, as no related GitHub issues were found. It might be helpful to open an issue with details about your experience so it can be reviewed by the Prefect development team. If I had a brain the size of a planet, I'd figure this out. But alas, we rely on documentation and community!
s
@Marvin As I understand it, the result of a flow would be stored in state.data. Is this correct?
m
Yes, in Prefect, the result of a flow or a task is typically stored within the state object, specifically in an attribute like 
state.data
. However, for this to happen, result persistence needs to be configured correctly. By default, Prefect does not persist results unless you explicitly enable it and set up the necessary configurations, such as specifying a storage block or serializer. Here’s a simplified breakdown of the basic concept: - Task and Flow Results: When a task or flow run completes successfully, Prefect can store its output as a result. This result can be accessed via the state's data attribute, like 
state.data
. - State Object: The state object not only holds the result data but also provides comprehensive details about the run's status and history. Make sure your Prefect configuration for results is correctly set, ensuring all requirements for persistence are in place, including storage location and serialization settings. For detailed instruction on result configuration, please check the official Prefect documentation on results. When correctly configured, you should indeed see your flow's result in 
state.data
. If you're still facing difficulties, it might be worth revisiting your configurations to ensure everything is aligned with Prefect's result management requirements.
s
@Marvin How can I pass a locale-file-storage-block as result_storage to a deployed flow?
m
To pass a local-file-storage-block as 
result_storage
to a deployed flow in Prefect 3.x, you can follow these guidelines: 1. Create a Storage Block: First, you need to create a local file storage block. This is where your flow's results will be stored. You can do this in the Prefect UI or by defining it programmatically. 2. Configure Result Storage: Once you have the block ready, you can configure your flow's deployment to use this block for result storage. This is often done in the deployment specification or script. You would pass the storage block when registering or deploying your flow. 3. Update Deployment Configuration: Update the deployment configuration to include the reference to your local file storage block under 
result_storage
. Here are some useful details and sources from the documentation: - Managing Results: Provides insights into configuring result persistence, storage, and managing how results are serialized and stored. - Deployment Overview: Offers a broader context on how deployments work, how you can configure them remotely, and how they can be managed in Prefect. No straightforward Prefect predefined syntax for registering a storage block was found in the latest GitHub issues, implying the approach remains as described. If you're still pondering the meaning of life, the universe, and local file storage, perhaps triply-check your configurations—they might just align the stars for you!
s
@Marvin how can I add the server-file-system Block as result_storage to my deployed flow via prefect-yaml?
m
To add a server-file-system block as 
result_storage
to your deployed flow using a 
prefect.yaml
file, you need to reference the block within the file. Prefect allows you to utilize block references for such configurations. Here's a guideline based on the available documentation: 1. Create the Server File System Block: First, ensure you have a server-file-system block created and registered in your Prefect environment. This block should specify the configuration for how results should be stored. 2. Updating 
prefect.yaml
: In your 
prefect.yaml
file, you can reference Prefect blocks using the syntax 
{{ prefect.blocks.block_type.block_slug }}
. This allows you to dynamically pull in configuration settings from registered blocks. Here's a basic example of what a section of your 
prefect.yaml
might look like:
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yaml
storage:
  - block: {{ prefect.blocks.server-file-system.block_slug }}
3. Block Reference: Replace 
block_slug
with the identifier of your registered server-file-system block. The reference in the YAML file should be enclosed within curly braces and quote marks as per the templating options provided. 4. Testing and Deployment: After updating your 
prefect.yaml
file, deploy your flow to ensure that the configuration is correctly applied and that the results are being stored as expected. For more in-depth details about using 
prefect.yaml
to deploy configurations, check the relevant documentation. If it feels like your 
prefect.yaml
is speaking Vogon poetry, just remember: it's all about those curly braces and proper slugs!
s
@Marvin Can you create a prefect.yaml for a deployment data_loading that is using the block as result_storage?
m
Certainly! Here is an example of a 
prefect.yaml
configuration file for a deployment named 
data_loading
that uses a server-file-system block as 
result_storage
.
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yaml
version: 3
name: data_loading
description: Deployment for loading data with result storage configuration
flow:
  # Specify the path to your flow script
  path: path/to/your/flow_script.py
  # Specify the flow's entry point
  entry_point: flow_function_name
storage:
  - block: "{{ prefect.blocks.server-file-system.data_loading_storage }}"
result_storage:
  - block: "{{ prefect.blocks.server-file-system.data_loading_results }}"
infrastructure:
  - type: process
    # If needed, specify additional infrastructure requirements
parameters:
  param_name1: value1
  param_name2: value2
schedule:
  cron: "0 0 * * *"  # Example CRON schedule -> runs daily at midnight
tags:
  - data_loading
### Key Points: - Flow: The 
flow
section should include the path to your flow script and the entry point (usually your main flow function). - Storage: You can configure storage for the flow script as needed. - Result Storage: The important part is referencing your 
result_storage
block. Replace 
data_loading_storage
and 
data_loading_results
with the actual slugs for your server-file-system blocks. - Infrastructure: You may specify additional infrastructure details like the type (process, docker, etc.). - Parameters: Add any parameters your flow might need. - Schedule: Optional scheduling with CRON if your deployment runs on a schedule. Again, make sure you replace placeholders like 
path/to/your/flow_script.py
, 
flow_function_name
, and block slugs with actual values relevant to your setup. This structure should help ensure your flow can utilize the specified block for result storage effectively. If you configure it, your results will persist without needing to quote any Vogon poetry to them!
s
@Marvin this doesn't work. any other idaes for Prefect 3.1.0
m
In Prefect 3.1.0, setting up a deployment with a server-file-system block as 
result_storage
needs to be configured correctly in your 
prefect.yaml
. Here’s a more detailed approach based on the insights from the documentation: 1. Ensure Block is Registered: First, confirm that your server-file-system block is properly registered in your Prefect environment. This block should define how and where the results of your flow are stored on your server file system. 2. Create a Prefect YAML File: Here's a refined example of how your 
prefect.yaml
should look to integrate the server-file-system block for result storage:
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yaml
version: 3
name: data_loading
description: Deployment for data loading with result storage configuration
flow:
  path: path/to/your/flow_script.py
  entry_point: flow_function_name
storage:
  - type: local
    # Specify the path where the flow script is stored
    path: /path/to/store/flow
result_storage:
  - type: file-system
    # Reference your registered block's name
    block: your_server_file_system_block_slug
infrastructure:
  type: local-process
  # Further definitions for infrastructure can go here
parameters:
  # Include any parameters needed for your deployment
schedule:
  # Example schedule
  cron: "0 0 * * *"
tags:
  - data_loading
### Important Points: - Result Storage Configuration: The key part here is correctly referencing your server-file-system block within 
result_storage
. Ensure the block name in this file exactly matches the block you created. - YAML File Location: The 
prefect.yaml
file can be placed according to your project structure. If not in the root directory, specify its path when deploying with:
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prefect deploy --prefect-file path/to/your_prefect.yaml
- Precise Definitions: Make sure all paths and block references directly align with your setup in Prefect's environment. If this approach still gives issues, further debugging might include checking Prefect logs to ensure there are no underlying configuration errors or typos. Remember, "what earthly use is a slug", Prefect humors, so slugs need to be precise!
s
@Marvin what does this error message mean? TypeError: Result storage configuration must be persisted server-side. Please call 
.save()
on your block before passing it in.
m
The error message you're seeing means that the block you're trying to use for result storage hasn't been properly saved or registered in Prefect's backend. Let's break it down a bit: 1. Persisting the Block Server-Side: In Prefect, blocks such as storage, result, or configuration blocks need to be created and then saved to Prefect's server (either local or cloud) so that they can be accessed and used during flow runs. 2. Call 
.save()
Method: When you create a block, it exists temporarily in your script's memory. To make it permanent and accessible for future use or across different deployments, you need to call the 
.save()
method on the block object. This method takes a name or identifier for the block, which you'll use to reference it later. ### What to Do: - Create and Save the Block: Ensure that you've both created and saved your block. Here’s a quick example using a file system block:
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python
  from prefect.filesystems import LocalFileSystem

  # Create the file system block
  block = LocalFileSystem(basepath="/path/to/store/results")

  # Save the block with a unique name
  block.save(name="my_result_storage")
- Reference Saved Block: After saving, use this name when configuring your flow or deployment to utilize the block, typically in 
prefect.yaml
or wherever you're setting up deployments. In essence, Prefect is nudging you to "remember" this configuration for future use by saving it, preventing you from losing setup details each time your script runs. It's almost like a brain for blocks—because we all need a persistent one once in a while!
s
@Marvin In Prefect 3.1.0 i get the error message: flow() got an unexpected keyword argument 'presist_result' How can I define on a flow level which flows should persist their results?
m
The error message you're encountering, 
flow() got an unexpected keyword argument 'presist_result'
, suggests that 
presist_result
is not a recognized argument in the function definition for a flow in Prefect 3.1.0. To persist results in Prefect, you need to configure result persistence at a different level. Here's how you can define which flows should persist their results: 1. Global Configuration: You can enable result persistence globally by setting the 
PREFECT_RESULTS_PERSIST_BY_DEFAULT
environment variable to 
True
. This tells Prefect to persist results for all flows, unless otherwise specified. 2. Result Storage at the Flow Level: - You need to configure result storage for the flow either via a result storage block or directly in the flow's deployment. - The configuration can be included in the deployment YAML or when creating the flow programmatically. 3. Creating and Using Blocks: - Create a 
ResultStorage
block or specify a storage type that supports result persistence (such as S3, local filesystem, etc.). - Reference this block within your flow configuration. 4. Example Configuration in Code: - Here's an example of how you might configure this within a Python script:
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python
   from prefect import flow
   from prefect.filesystems import LocalFileSystem

   @flow
   def my_flow():
       # Your flow logic here
       return "Hello, results!"

   # Configure the result storage
   storage = LocalFileSystem(basepath="/path/to/results")
   storage.save(name="my_local_result_storage")

   # Use the saved storage block in your deployment or flow config
5. Deployment YAML: - If using 
prefect.yaml
, ensure the result storage configuration is correctly specified, referencing 
ResultStorage
. These configurations allow you to set which flows will persist their results by specifying the storage and serialization of these results, rather than using an unsupported keyword argument like 
persist_result
. For more detailed guidance, refer to the Prefect documentation on result management. By sidestepping the keyword argument approach, like avoiding Vogon poetry recitals at parties, you should ensure smoother flow configurations!
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