Paweł Biernat
10/15/2024, 3:05 PM--job-variable env='{PREFECT_DEFAULT_RESULT_STORAGE_BLOCK: def}'
but this fails with
Response: {'detail': "Error creating deployment: Validation failed for field 'env'. Failure reason: '{PREFECT_DEFAULT_RESULT_STORAGE_BLOCK: def}' is not valid under any of the given schemas"}
For more information check: <https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/422>
Marvin
10/15/2024, 3:06 PMjob_variables
section of your deployment YAML file. Here's a summary of how to approach this:
1. Defining Environment Variables: Within your prefect.yaml
deployment file, you can include a job_variables
section where you specify environment variables. Here's an example:
yaml
deployments:
- name: demo-deployment
entrypoint: demo_project/demo_flow.py:some_work
work_pool:
name: local
job_variables:
env:
PREFECT_DEFAULT_RESULT_STORAGE_BLOCK: "def"
2. Using Environment Variables from Local Environment: If you want to use environment variables that are already set in your local environment, you can reference them in your YAML file using the syntax {{ $ENV_VAR_NAME }}
.
yaml
deployments:
- name: demo-deployment
entrypoint: demo_project/demo_flow.py:some_work
work_pool:
name: local
job_variables:
env:
PREFECT_DEFAULT_RESULT_STORAGE_BLOCK: "{{ $PREFECT_DEFAULT_RESULT_STORAGE_BLOCK }}"
3. Deploy Command: After setting up your YAML file, run the deployment using the Prefect CLI:
bash
prefect deploy -n demo-deployment
This should deploy your flow with the provided job variables, which can be seen in the Configuration tab of the deployment in the Prefect UI.
For more detailed instructions, you may refer to the following links:
- Prefect 2.x Documentation on Overriding Job Variables
- Prefect 3.x Documentation on Customizing Infrastructure
If you continue facing issues, please make sure your Prefect version matches these instructions and consider checking for special syntax or errors in your YAML configuration. If you are using other deployment methods or infrastructure, let me know!Paweł Biernat
10/15/2024, 3:06 PMMarvin
10/15/2024, 3:07 PMconfig.toml
file or using environment variables that Prefect reads at runtime.
2. Custom Utilities: Create a Python utility script or a function that modifies the generated deployment YAML files to include a common set of environment variables before deploying.
3. Use Prefect Blocks (2.x and 3.x): Prefect allows using "Blocks", which are reusable configurations or settings. By defining your environment variables in a Block, you can easily apply them to all deployments:
- Create a Block: You could define a Block specifically for environment configurations.
- Reference the Block: Include this block reference in your job_variables
for each deployment.
Here is an example of how you might define and use configuration globally in Prefect:
python
# This example assumes Prefect 2.x or 3.x blocks are used
from prefect.blocks.system import EnvironmentVariables
# Create an Environment Variables Block
env_vars = EnvironmentVariables(
variables={
"PREFECT_DEFAULT_RESULT_STORAGE_BLOCK": "def",
"ANOTHER_ENV_VAR": "value"
}
)
env_vars.save("global-env-vars", overwrite=True)
Once saved, you can use this Block in your deployment configuration:
yaml
deployments:
- name: demo-deployment
entrypoint: demo_project/demo_flow.py:some_work
work_pool:
name: local
job_variables:
env: "{{ EnvironmentVariables.load('global-env-vars') }}"
This way, any changes to the environment variables only need to be made in one place. Whenever you load the Block in new deployments, they'll automatically use the updated variables.
For more details, you can look into how Prefect 2.x and 3.x handle environment blocks and configurations:
- Prefect 2.x Blocks Documentation
- Prefect 3.x Blocks Documentation
Let me know if you need further help or examples!Paweł Biernat
10/15/2024, 3:08 PM--job-variable env='{PREFECT_DEFAULT_RESULT_STORAGE_BLOCK: def}'
for it to pass the schema validation?Marvin
10/15/2024, 3:08 PM--job-variable
flag without encountering schema validation errors, it's important to ensure the format is aligned with JSON-like string expectations. Here's the correct syntax for your scenario:
bash
--job-variable env='{"PREFECT_DEFAULT_RESULT_STORAGE_BLOCK": "def"}'
### Key Adjustments:
1. JSON Style: Use double quotes around both the keys and values in the JSON-like structure. In the shell, the whole expression should be encapsulated in single quotes.
2. Proper JSON: Ensure that the expression inside conforms to standard JSON format.
These adjustments should allow your environment variable setting to pass the schema validation step.
If you'd like to know more or need additional examples, here are the relevant documentation links:
- Prefect 2.x Overriding Job Variables
- Prefect 3.x Customizing Infrastructure
Using these standardized formats will help avoid similar errors in the future when deploying with Prefect. Let me know if you have any other questions!Paweł Biernat
10/15/2024, 3:09 PMMarvin
10/15/2024, 3:09 PM--job-variable
flag, it's essential to follow the expected format. Based on the information from Prefect 2.x documentation and best practices for setting job variables, here is the correct way to phrase the command with valid syntax:
bash
--job-variable 'env={"PREFECT_DEFAULT_RESULT_STORAGE_BLOCK": "def"}'
### Key Details:
1. Format: Use JSON-like syntax for the environment variables, with double quotes around both keys and values.
2. Shell Compatibility: Enclose the whole expression in single quotes to avoid shell parsing issues.
If this still doesn't work, some additional steps to resolve the problem might include:
- Ensuring that your Prefect version supports this syntax by checking your current Prefect version, as the syntax might be different between versions.
- Double-checking how Prefect interprets command-line arguments. Running a simpler command first to confirm the basics are working can isolate command parsing issues.
- Reviewing Prefect's Overriding Job Variables documentation, which can provide additional context or examples.
If you continue experiencing issues, examining Prefect's logs or error messages for more specific clues can help narrow down the precise cause of validation failures. Let me know if there's anything else I can assist with!