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Hi folks, quick dumb question : to set to the type of parameter for a flow, do i just use type hints to set the type of parameters?

yes definitely. We use Pydantic to validate the type hints so  most type hints should work. You can disable validating with `validate_parameters=False`

<@U03GUVCV8DS> I am able to set the type of the parameter as type hints, I am facing an issue when setting the parameter in the cloud UI , it automatically converts the list passed as a string. I am able to set the list in the UI but during runtime it takes the list as a string and fails the validation, even disabling validation is not going to resolve this. Can you please help me with this ?

Can you paste an example of how your flow code looks like?

```
@flow(name='prod_pagespeed_metrics')
def pagespeed_metrics(columns:list, device_type:str='mobile', table_name:str='metrics', schema_name:str='dl_pagespeed_api', api_url:str='<https://www.googleapis.com/pagespeedonline/v5/runPagespeed',url_file_path:str='files/page_speed_urls.csv>'):
    url_list = get_url_list(url_file_path)
    category = 'performance'
    metrics = transform_pagespeed_api(url_list=url_list,
                                      device_type=device_type,
                                      category=category,
                                      api_key=google_pagespeed_api_key.get(),
                                       api_url=api_url)

    df_to_redshift(metrics, redshift_user.get(), redshift_password.get(),
                   table_name, redshift_db.get(), schema_name, redshift_host.get())```

Hi <@U03GUVCV8DS> Sorry for the late reply, so basically , I am passing a list of columns as parameter, and when i change this list it shows up as string

also, had another question, How can reuse the same flow function with different parameter and have a deployment for each, For example, i want a flow deployment for device_type  mobile and desktop. Can I reuse the same function ? or I need to create a function for each ?

I just deployed a flow with a list as a parameter:
```from prefect import task, flow


@flow
def test_flow(l: list = [1, 2, 3]):
    assert isinstance(l, list)


if __name__ == "__main__":
    test_flow()```
and changed the value of the parameter when running the deployment.

It worked fine for me. I wonder if you change the value of the parameter through deployment?

Yes, you can use <https://docs.prefect.io/api-ref/prefect/client/#prefect.client.orion.OrionClient.create_flow_run_from_deployment|create_flow_run_from_deployment> to create a flow run from a deployment with a custom parameter. Not sure if that answered your question

<@U03GUVCV8DS> Thanks for this, i was indeed setting type in the function and actually passing the parameter in the UI overriding the default but my assumption was that once you provide a type hint, then it implicitly defines the type of the parameter and i should be able to pass list during run time. Anyway, let me double check this and get back to you