1.0.0 Migration Guide

The 1.0 release of the google-cloud-datalabeling client is a significant upgrade based on a next-gen code generator, and includes substantial interface changes. Existing code written for earlier versions of this library will likely require updates to use this version. This document describes the changes that have been made, and what you need to do to update your usage.

If you experience issues or have questions, please file an issue.

Supported Python Versions

WARNING: Breaking change

The 1.0.0 release requires Python 3.6+.

Method Calls

WARNING: Breaking change

Methods expect request objects. We provide a script that will convert most common use cases.

  • Install the library
python3 -m pip install google-cloud-datalabeling
  • The script fixup_datalabeling_v1_keywords.py is shipped with the library. It expects an input directory (with the code to convert) and an empty destination directory.
$ fixup_datalabeling_v1_keywords.py --input-directory .samples/ --output-directory samples/

Before:

from google.cloud import datalabeling

client = datalabeling.DataLabelingServiceClient()

datasets = client.list_datasets(parent="projects/project")

After:

from google.cloud import datalabeling

client = datalabeling.DataLabelingServiceClient()

datasets = client.list_datasets(request={"parent": "projects/project"})

More Details

In google-cloud-datalabeling<1.0.0, parameters required by the API were positional parameters and optional parameters were keyword parameters.

Before:

    def create_dataset(
        self,
        parent,
        dataset,
        retry=google.api_core.gapic_v1.method.DEFAULT,
        timeout=google.api_core.gapic_v1.method.DEFAULT,
        metadata=None,
    ):

In the 1.0.0 release, all methods have a single positional parameter request. Method docstrings indicate whether a parameter is required or optional.

Some methods have additional keyword only parameters. The available parameters depend on the google.api.method_signature annotation specified by the API producer.

After:

    def create_dataset(
        self,
        request: data_labeling_service.CreateDatasetRequest = None,
        *,
        parent: str = None,
        dataset: gcd_dataset.Dataset = None,
        retry: retries.Retry = gapic_v1.method.DEFAULT,
        timeout: float = None,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gcd_dataset.Dataset:

NOTE: The request parameter and flattened keyword parameters for the API are mutually exclusive. Passing both will result in an error.

Both of these calls are valid:

response = client.create_dataset(
    request={
        "parent": parent,
        "dataset": dataset
    }
)

response = client.create_dataset(
    parent=parent,
    dataset=dataset
)

This call is invalid because it mixes request with a keyword argument dataset. Executing this code will result in an error.

response = client.create_dataset(
    request={
        "parent": parent
    },
    dataset=dataset
)

Enums and Types

WARNING: Breaking change

The submodules enums and types have been removed.

Before:

from google.cloud import datalabeling

data_type = datalabeling.enums.DataType.IMAGE
dataset = datalabeling.types.Dataset(display_name="name")

After:

from google.cloud import datalabeling

data_type = datalabeling.DataType.IMAGE
dataset = datalabeling.Dataset(display_name="name")

Path Helper Methods

The following path helper methods have been removed. Please construct the paths manually.

project="project"
dataset="dataset"
annotated_dataset="annotated_dataset"
annotation_spec_set="annotation_spec_set"
data_item="data_item"
evaluation="evaluation"
evaluation_job="evaluation_job"
example="example"
instruction="instruction"

annotated_dataset_path = f'projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}'
annotation_spec_set_path = f'projects/{project}/annotationSpecSets/{annotation_spec_set}'
data_item_path=f'projects/{project}/datasets/{dataset}/dataItems/{data_item}'
dataset_path=f'projects/{project}/datasets/{dataset}'
evaluation_path=f'projects/{project}/datasets/{dataset}/evaluations/{evaluation}'
evaluation_job_path=f'projects/{project}/evaluationJobs/{evaluation_job}'
example_path=f'projects/{project}/datasets/{dataset}/annotatedDatasets/{annotated_dataset}/examples/{example}'
instruction_path=f'projects/{project}/instructions/{instruction}'
project_path=f'projects/{project}'