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<@ULVA73B9P> Explain this error and demonstrate pr...
# ask-marvin
r
@Marvin Explain this error and demonstrate proper usage of PrefectClient.create_work_pool(): TypeError: PrefectClient.create_work_pool() got an unexpected keyword argument 'name'
m
The error you're encountering, 
TypeError: PrefectClient.create_work_pool() got an unexpected keyword argument 'name'
, suggests that the 
create_work_pool
method does not accept a 
name
keyword argument. This might be due to either a misunderstanding of the method's API or a mismatch between the Prefect version and the documentation or code you are referencing. Unfortunately, I couldn't find the exact method definition for 
create_work_pool
in the available documentation or module exploration. However, I can provide some guidance on how to proceed: 1. Verify Method Signature: Make sure to check the Prefect documentation or source code for the correct signature of 
create_work_pool
. This might be available in the Prefect GitHub repository or the official Prefect documentation. 2. Using Prefect CLI: As a workaround, you can create work pools using the Prefect CLI with the command 
prefect work-pool create
. This command requires a unique name for the work pool and offers additional configuration options such as 
--paused
or 
--type
. More details can be found in the Prefect 3.x work pools documentation. 3. Version Compatibility: Ensure that your Prefect client and server are compatible, as Prefect aims to maintain backward compatibility. If there is a version mismatch, it might lead to unexpected errors. If you have further details or need more specific assistance, you might want to check the Prefect GitHub repository for any issues related to this method or consult the Prefect community for support.
r
@Marvin In the prefect SDK there is the following documentation:
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create_work_pool(work_pool, overwrite=False)

WorkPoolCreate

Bases: ActionBaseModel

Data used by the Prefect REST API to create a work pool.

Source code in src/prefect/client/schemas/actions.py

class WorkPoolCreate(ActionBaseModel):
    """Data used by the Prefect REST API to create a work pool."""

    name: NonEmptyishName = Field(
        description="The name of the work pool.",
    )
    description: Optional[str] = Field(None)
    type: str = Field(
        description="The work pool type.", default="prefect-agent"
    )  # TODO: change default
    base_job_template: Dict[str, Any] = Field(
        default_factory=dict,
        description="The base job template for the work pool.",
    )
    is_paused: bool = Field(
        default=False,
        description="Whether the work pool is paused.",
    )
    concurrency_limit: Optional[NonNegativeInteger] = Field(
        default=None, description="A concurrency limit for the work pool."
    )
m
From the information you've provided, it seems that the 
create_work_pool
method expects an instance of 
WorkPoolCreate
as its argument, rather than individual keyword arguments like 
name
. Here's how you can properly use `PrefectClient.create_work_pool()`: 1. Create a 
WorkPoolCreate
Object: First, you need to create an instance of 
WorkPoolCreate
with the necessary attributes. 2. Call 
create_work_pool
: Pass this instance to the 
create_work_pool
method of 
PrefectClient
. Here's a basic example:
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python
from prefect.client.orchestration import PrefectClient
from prefect.client.schemas.actions import WorkPoolCreate

# Initialize the Prefect client
client = PrefectClient()

# Create a WorkPoolCreate instance
work_pool_data = WorkPoolCreate(
    name="my-work-pool",
    description="A description for my work pool",
    type="prefect-agent",
    base_job_template={},  # Add your job template details here
    is_paused=False,
    concurrency_limit=10
)

# Use the client to create a work pool
response = client.create_work_pool(work_pool_data)

print(response)
Make sure that you have the correct imports and that your Prefect SDK version supports these classes and methods. This approach should align with the Prefect 3.x documentation and usage patterns. If you encounter any issues, double-check the version compatibility and the Prefect SDK documentation.
r
@Marvin I get the following error:
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prefect.exceptions.PrefectHTTPStatusError: Client error '422 Unprocessable Entity' for url '<http://127.0.0.1:4200/api/work_pools/>'
Response: {'exception_message': 'Invalid request received.', 'exception_detail': [{'type': 'value_error', 'loc': ['body', 'base_job_template'], 'msg': 'Value error, The variables specified in the job configuration template must be present as properties in the variables schema. Your job configuration uses the following undeclared variable(s): image ,env.', 'input': {'variables': {'env': {'type': 'object', 'title': 'Environment Variables', 'description': 'Environment variables to set when starting a flow run.', 'additionalProperties': {'type': 'string'}}, 'image': {'type': 'string', 'title': 'Image', 'example': 'prefecthq/prefect:3.1.15.dev5-python3.11', 'description': 'The image reference of a container image to use for created jobs. If not set, the latest Prefect image will be used.'}}, 'job_configuration': {'env': '{{ env }}', 'image': '{{ image }}'}}, 'ctx': {'error': {}}}], 'request_body': {'name': 'redacted', 'type': 'docker', 'base_job_template': {'variables': {'env': {'type': 'object', 'title': 'Environment Variables', 'description': 'Environment variables to set when starting a flow run.', 'additionalProperties': {'type': 'string'}}, 'image': {'type': 'string', 'title': 'Image', 'example': 'prefecthq/prefect:3.1.15.dev5-python3.11', 'description': 'The image reference of a container image to use for created jobs. If not set, the latest Prefect image will be used.'}}, 'job_configuration': {'env': '{{ env }}', 'image': '{{ image }}'}}, 'is_paused': False}}
For more information check: <https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/422>
m
The error message you're encountering indicates that the 
base_job_template
you provided in the 
WorkPoolCreate
instance contains variables (
env
and 
image
) that are not properly declared in the variables schema. The Prefect API expects these variables to be explicitly defined in the template. Here's how you can address this: 1. Ensure Variables are Declared: Make sure that the variables used in 
job_configuration
are declared in the 
variables
field of 
base_job_template
. 2. Check Variable Names: Ensure that the variable names in 
job_configuration
match exactly with those declared in the 
variables
schema. Here's an example illustrating the correct structure:
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python
from prefect.client.orchestration import PrefectClient
from prefect.client.schemas.actions import WorkPoolCreate

# Initialize the Prefect client
client = PrefectClient()

# Create a WorkPoolCreate instance with the correct base_job_template
work_pool_data = WorkPoolCreate(
    name="my-work-pool",
    description="A description for my work pool",
    type="docker",
    base_job_template={
        "variables": {
            "env": {
                "type": "object",
                "title": "Environment Variables",
                "description": "Environment variables to set when starting a flow run.",
                "additionalProperties": {"type": "string"}
            },
            "image": {
                "type": "string",
                "title": "Image",
                "example": "prefecthq/prefect:3.1.15.dev5-python3.11",
                "description": "The image reference of a container image to use for created jobs. If not set, the latest Prefect image will be used."
            }
        },
        "job_configuration": {
            "env": "{{ env }}",
            "image": "{{ image }}"
        }
    },
    is_paused=False,
    concurrency_limit=10
)

# Use the client to create a work pool
response = client.create_work_pool(work_pool_data)

print(response)
Ensure that the structure of 
base_job_template
is correctly defined and that the variables used are declared in the 
variables
section. This should resolve the 
422 Unprocessable Entity
error.
r
@Marvin I created a work pool, but when I attempt to deploy my code, I get the following error:
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ValueError: Work pool '98c5a5a1-6304-5e0b-b1c0-8ce4f220a6f5' does not support custom Docker images. Please use a work pool with an `image` variable in its base job template or specify a remote storage location for the flow with `.from_source`. If you are attempting to deploy a flow to a local process work pool, consider using `flow.serve` instead. See the documentation for more information: <https://docs.prefect.io/latest/deploy/run-flows-in-local-processes>
m
The error you're encountering indicates that the work pool you created does not support custom Docker images because its base job template lacks an 
image
variable. Here's how you can resolve this issue: 1. Ensure 
image
Variable is Defined: When creating the work pool, make sure that the 
base_job_template
includes an 
image
variable. This variable should be part of the 
variables
schema in the template. 2. Check Work Pool Type: Ensure that the work pool type supports Docker images. For instance, a work pool of type 
docker
should have an 
image
variable in its template. 3. Modify or Recreate Work Pool: If the current work pool doesn't support Docker images, you might need to update its configuration or create a new work pool with the correct template. Here's an example of how to define a work pool with the necessary 
image
variable:
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python
from prefect.client.orchestration import PrefectClient
from prefect.client.schemas.actions import WorkPoolCreate

# Initialize the Prefect client
client = PrefectClient()

# Create a WorkPoolCreate instance with the correct base_job_template
work_pool_data = WorkPoolCreate(
    name="my-docker-work-pool",
    description="A work pool that supports custom Docker images",
    type="docker",
    base_job_template={
        "variables": {
            "env": {
                "type": "object",
                "title": "Environment Variables",
                "description": "Environment variables to set when starting a flow run.",
                "additionalProperties": {"type": "string"}
            },
            "image": {
                "type": "string",
                "title": "Image",
                "example": "prefecthq/prefect:3.1.15.dev5-python3.11",
                "description": "The image reference of a container image to use for created jobs. If not set, the latest Prefect image will be used."
            }
        },
        "job_configuration": {
            "env": "{{ env }}",
            "image": "{{ image }}"
        }
    },
    is_paused=False,
    concurrency_limit=10
)

# Use the client to create a work pool
response = client.create_work_pool(work_pool_data)

print(response)
4. Consider Remote Storage: If modifying the work pool is not an option, you can specify a remote storage location for your flow using 
.from_source
. 5. Local Process Execution: If you intend to run the flow locally, consider using 
flow.serve
as suggested in the error message. Refer to the Prefect documentation for more details on running flows in local processes and configuring work pools.
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