I am working on standing up Prefect 2 0 is a production envi

Question

I am working on standing up Prefect 2 0 is a production environment For internal data pipeline and reverse etl uses so no fire hazards on my end to use 2 0 early here Is there a general preference on YAML vs Code for the deployment specification I noticed you can configure a flow deployment with YAML but I cant find any information on the schema of that document For example ``` name elt salesforce flow location salesforce flows py flow name elt salesforce tags salesforce core parameters destination gcp schedule interval 3600``` Assuming interval is seconds Can I specify another grain Can schedule take a dict If it takes cron does that take a dict Honestly schedule is the primary question point Everything else is straightforward enough

Kevin Kho · Answer

Hi < Alexander Butler> I d need to check with the team tomorrow about this and get back to you

Anna Geller · Answer

Good choice starting with 2 0 directly clap I m more biased towards definition in Python but YAML is also supported Python definition is friendlier and cleaner Here is one example of using YAML ``` name crypto prices etl dev flow location Users anna repos gitops orion flows flows crypto prices etl py flow name crypto prices etl tags dev schedule interval 3600 name repo trending check prefect dev flow location flows repo trending check py flow name repo trending check tags dev parameters repo prefect schedule interval 3600 name repo trending check orion dev flow location Users anna repos gitops orion flows flows repo trending check py flow name repo trending check tags dev parameters repo prefect schedule interval 60``` I believe the same definition via Python `DeploymentSpec` is much cleaner and easier to understand change but YAML is also fine slightly smiling face

Alexander Butler · Answer

I like Python too I think the ambiguous bit is whether `schedule` supports cron or different kwargs for interval

Alexander Butler · Answer

or a different time grain

Alexander Butler · Answer

in yaml

Zanie · Answer

The YAML is loaded using Pydantic models which infers the type based on the keys

Zanie · Answer

So if you did `cron string here` instead of `interval integer` it d be loaded as a cron schedule

Zanie · Answer

From the Pydantic documentation you can provide more rich strings for intervals other than seconds

Zanie · Answer

``` timedelta fields can be timedelta existing timedelta object int or float assumed as seconds str following formats work DD HH MM SS ffffff P DD DT HH H MM M SS S ISO 8601 format for timedelta ```

Zanie · Answer

See <https pydantic docs helpmanual io usage types datetime types>

Zanie · Answer

cc < terrence> this is a good nugget slightly smiling face

terrence · Answer

Good note

Anna Geller · Answer