Joshua Newman
09/13/2024, 3:34 PMMarvin
09/13/2024, 3:35 PMJoshua Newman
09/13/2024, 3:36 PMMarvin
09/13/2024, 3:36 PMyaml
schedule:
cron: "0 0 * * *"
2. Updating Deployment Schedules:
You can update your deployment schedules via the UI with simple inputs like cron strings or intervals. When you update a deployment schedule through the UI, it resets the auto-scheduled runs. Here's more on scheduling in deployments.
3. Block-Based Approach:
In the deployment.yaml
, you can freely edit the schedule before running prefect deployment apply
. Ensure that your changes are captured under the schedule
key in the metadata block.
For more details, check:
- Prefect Deployment Concepts
- Deployment Schedule Basics
Hope this helps! Let me know if there's anything specific you need.Joshua Newman
09/13/2024, 7:02 PMschedules
list instead.Marvin
09/13/2024, 7:13 PMschedule
field in Deployment
, you need to adopt the new schedules
list format.
Here's how you can adapt your configuration:
### Old Format (Deprecated)
yaml
# Your existing deployment.yaml
name: my-deployment
schedule:
cron: "0 0 * * *"
timezone: "UTC"
### New Format (Preferred)
yaml
# Updated deployment.yaml
name: my-deployment
schedules:
- cron: "0 0 * * *"
timezone: "UTC"
active: true
Replace your schedule
key with schedules
and make each schedule an item in the list. This will handle multiple schedules if needed.
### Sources:
- Prefect Concepts - Schedules
- Prefect GitHub Issue on Deprecated Schedule Field
This should resolve the warning. Let me know if you need further help!Joshua Newman
09/13/2024, 11:41 PMMarvin
09/13/2024, 11:41 PMflow.deploy
method in Prefect 2.20 exposes the same options as flow.to_deployment
. Here are the key parameters you can use:
1. name: The name of the deployment.
2. schedule: Define a single schedule or a list of schedules.
3. parameters: Default parameter values to pass to the flow.
4. work_queue_name: The name of the work queue that will handle the deployment's runs.
5. tags: Tags to associate with the deployment.
6. infra_overrides: Infrastructure overrides for the deployment.
7. storage: Storage block for the deployment.
8. entrypoint: The location of the flow file (only required if not using an existing flow).
9. description: Optional description of the deployment.
### Example Usage:
python
@flow
def my_flow(param1: int = 1):
print(param1)
my_deployment = my_flow.deploy(
name="my-deployment",
schedule={"cron": "0 0 * * *"},
parameters={"param1": 42},
work_queue_name="my-queue"
)
### Sources:
- Prefect Deployments - Concepts
- Prefect Deployments - Tutorial
This should get you started with using the flow.deploy
method effectively. Let me know if you need more specifics!Joshua Newman
09/14/2024, 6:14 PMMarvin
09/14/2024, 6:15 PMRuntimeError: Failed to generate Dockerfile. Dockerfile already exists in the current directory
, you have a few options:
### 1. Use an Existing Dockerfile
If you already have a Dockerfile
, specify it explicitly in your deployment setup to avoid attempts to auto-generate it.
python
my_flow.deploy(
name="my-deployment",
image=DeploymentImage(
name="my-image",
tag="latest",
dockerfile="Dockerfile", # Reference your existing Dockerfile
),
)
### 2. Remove the Existing Dockerfile
If the Dockerfile is not essential or was generated by mistake, you can manually delete it and let Prefect generate a new one.
bash
rm Dockerfile
### 3. Use Custom Dockerfile Path
Specify a different path if you want to generate a new Dockerfile without removing the existing one.
python
my_flow.deploy(
name="my-deployment",
image=DeploymentImage(
name="my-image",
tag="latest",
dockerfile="custom-path/Dockerfile", # Use a custom Dockerfile path
),
)
### Sources:
- Prefect Deployments Guide
- Example of Docker-based deployment in Prefect
This should help you resolve the conflict with the existing Dockerfile. Let me know if you need more details!