Integrations with Other Libraries

Pydantic

cloudpathlib integrates with Pydantic's data validation. You can declare fields with cloud path classes, and Pydantic's validation mechanisms will run inputs through the cloud path's constructor.

from cloudpathlib import S3Path
from pydantic import BaseModel

class MyModel(BaseModel):
    s3_file: S3Path

inst = MyModel(s3_file="s3://mybucket/myfile.txt")
inst.s3_file
#> S3Path('s3://mybucket/myfile.txt')
inst.model_dump_json()
#> '{"s3_file":"s3://mybucket/myfile.txt"}'

This also works with the AnyPath polymorphic class. Inputs will get dispatched and instantiated as the appropriate class.

from cloudpathlib import AnyPath
from pydantic import BaseModel

class FancyModel(BaseModel):
    path: AnyPath

fancy1 = FancyModel(path="s3://mybucket/myfile.txt")
fancy1.path
#> S3Path('s3://mybucket/myfile.txt')

fancy2 = FancyModel(path="mydir/myfile.txt")
fancy2.path
#> PosixPath('mydir/myfile.txt')
fancy2.model_dump_json()
#> '{"path":"mydir/myfile.txt"}'

As seen above, the default serialization uses the URI but Pydantic supports custom serializers.

from typing import Annotated
from cloudpathlib import S3Path
from pydantic import BaseModel, PlainSerializer

class MyModel(BaseModel):
    s3_file: Annotated[S3Path, PlainSerializer(lambda x: x.as_url())]

inst = MyModel(s3_file="s3://mybucket/myfile.txt")
inst.model_dump_json()
#> '{"s3_file":"https://mybucket.s3.amazonaws.com/myfile.txt"}'

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^{Examples created with reprexlite}