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# pylint: disable=line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
import os
import re
import pytest
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import DatasetVersion, DatasetType
from test_base import TestBase, servicePreparer
from devtools_testutils import recorded_by_proxy, is_live_and_not_recording
from azure.core.exceptions import HttpResponseError
# Construct the paths to the data folder and data file used in this test
script_dir = os.path.dirname(os.path.abspath(__file__))
data_folder = os.environ.get("DATA_FOLDER", os.path.join(script_dir, "test_data/datasets"))
data_file1 = os.path.join(data_folder, "data_file1.txt")
data_file2 = os.path.join(data_folder, "data_file2.txt")
class TestDatasets(TestBase):
# To run this test, use the following command in the \sdk\ai\azure-ai-projects folder:
# cls & pytest tests\test_datasets.py::TestDatasets::test_datasets_upload_file -s
@servicePreparer()
@pytest.mark.skipif(
not is_live_and_not_recording(),
reason="Skipped because this test involves network calls from another client (azure.storage.blob) that is not recorded.",
)
@recorded_by_proxy
def test_datasets_upload_file(self, **kwargs):
endpoint = kwargs.pop("azure_ai_projects_tests_project_endpoint")
print("\n=====> Endpoint:", endpoint)
connection_name = self.test_datasets_params["connection_name"]
dataset_name = self.test_datasets_params["dataset_name_1"]
dataset_version = self.test_datasets_params["dataset_version"]
with AIProjectClient(
endpoint=endpoint,
credential=self.get_credential(AIProjectClient, is_async=False),
) as project_client:
print(
f"[test_datasets_upload_file] Upload a single file and create a new Dataset `{dataset_name}`, version `{dataset_version}`, to reference the file."
)
dataset: DatasetVersion = project_client.datasets.upload_file(
name=dataset_name,
version=str(dataset_version),
file_path=data_file1,
connection_name=connection_name,
)
print(dataset)
TestBase.validate_dataset(
dataset,
expected_dataset_type=DatasetType.URI_FILE,
expected_dataset_name=dataset_name,
expected_dataset_version=str(dataset_version),
)
print(f"[test_datasets_upload_file] Get an existing Dataset version `{dataset_version}`:")
dataset = project_client.datasets.get(name=dataset_name, version=dataset_version)
print(dataset)
TestBase.validate_dataset(
dataset,
expected_dataset_type=DatasetType.URI_FILE,
expected_dataset_name=dataset_name,
expected_dataset_version=str(dataset_version),
)
print(
f"[test_datasets_upload_file] Upload a single file and create a new version in existing Dataset `{dataset_name}`, to reference the file."
)
dataset: DatasetVersion = project_client.datasets.upload_file(
name=dataset_name,
version=str(dataset_version + 1),
file_path=data_file2,
connection_name=connection_name,
)
print(dataset)
TestBase.validate_dataset(
dataset,
expected_dataset_type=DatasetType.URI_FILE,
expected_dataset_name=dataset_name,
expected_dataset_version=str(dataset_version + 1),
)
print(f"[test_datasets_upload_file] Get credentials of an existing Dataset version `{dataset_version}`:")
dataset_credential = project_client.datasets.get_credentials(
name=dataset_name, version=str(dataset_version)
)
print(dataset_credential)
TestBase.validate_dataset_credential(dataset_credential)
"""
print("[test_datasets_upload_file] List latest versions of all Datasets:")
empty = True
for dataset in project_client.datasets.list():
empty = False
print(dataset)
TestBase.validate_dataset(dataset)
assert not empty
print(f"[test_datasets_upload_file] Listing all versions of the Dataset named `{dataset_name}`:")
empty = True
for dataset in project_client.datasets.list_versions(name=dataset_name):
empty = False
print(dataset)
TestBase.validate_dataset(dataset, expected_dataset_name=dataset_name)
assert not empty
"""
print(
f"[test_datasets_upload_file] Delete Dataset `{dataset_name}`, version `{dataset_version}` that was created above."
)
project_client.datasets.delete(name=dataset_name, version=str(dataset_version))
project_client.datasets.delete(name=dataset_name, version=str(dataset_version + 1))
print(
"[test_datasets_upload_file] Delete the same (now non-existing) Dataset. REST API call should return 204 (No content). This call should NOT throw an exception."
)
project_client.datasets.delete(name=dataset_name, version=str(dataset_version))
print(
f"[test_datasets_upload_file] Try to get a non-existing Dataset `{dataset_name}`, version `{dataset_version}`. This should throw an exception."
)
try:
exception_thrown = False
dataset = project_client.datasets.get(name=dataset_name, version=str(dataset_version))
except HttpResponseError as e:
exception_thrown = True
print(f"Expected exception occurred: {e}")
assert "Could not find asset with ID" in e.message
assert exception_thrown
# To run this test, use the following command in the \sdk\ai\azure-ai-projects folder:
# cls & pytest tests\test_datasets.py::TestDatasets::test_datasets_upload_folder -s
@servicePreparer()
@pytest.mark.skipif(
not is_live_and_not_recording(),
reason="Skipped because this test involves network calls from another client (azure.storage.blob) that is not recorded.",
)
@recorded_by_proxy
def test_datasets_upload_folder(self, **kwargs):
endpoint = kwargs.pop("azure_ai_projects_tests_project_endpoint")
print("\n=====> Endpoint:", endpoint)
connection_name = self.test_datasets_params["connection_name"]
dataset_name = self.test_datasets_params["dataset_name_2"]
dataset_version = self.test_datasets_params["dataset_version"]
with AIProjectClient(
endpoint=endpoint,
credential=self.get_credential(AIProjectClient, is_async=False),
) as project_client:
print(
f"[test_datasets_upload_folder] Upload files in a folder (including sub-folders) and create a new version `{dataset_version}` in the same Dataset, to reference the files."
)
dataset = project_client.datasets.upload_folder(
name=dataset_name,
version=str(dataset_version),
folder=data_folder,
connection_name=connection_name,
file_pattern=re.compile(r"\.(txt|csv|md)$", re.IGNORECASE),
)
print(dataset)
TestBase.validate_dataset(
dataset,
expected_dataset_type=DatasetType.URI_FOLDER,
expected_dataset_name=dataset_name,
expected_dataset_version=str(dataset_version),
)
print(f"[test_datasets_upload_file] Get an existing Dataset version `{dataset_version}`:")
dataset = project_client.datasets.get(name=dataset_name, version=str(dataset_version))
print(dataset)
TestBase.validate_dataset(
dataset,
expected_dataset_type=DatasetType.URI_FOLDER,
expected_dataset_name=dataset_name,
expected_dataset_version=str(dataset_version),
)
print(f"[test_datasets_upload_file] Get credentials of an existing Dataset version `{dataset_version}`:")
dataset_credential = project_client.datasets.get_credentials(
name=dataset_name, version=str(dataset_version)
)
print(dataset_credential)
TestBase.validate_dataset_credential(dataset_credential)
print(
f"[test_datasets_upload_file] Delete Dataset `{dataset_name}`, version `{dataset_version}` that was created above."
)
project_client.datasets.delete(name=dataset_name, version=str(dataset_version))
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