Importer des données
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Importez des données à l'aide de la méthode import_data.
Exemple de code
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[[["Facile à comprendre","easyToUnderstand","thumb-up"],["J'ai pu résoudre mon problème","solvedMyProblem","thumb-up"],["Autre","otherUp","thumb-up"]],[["Difficile à comprendre","hardToUnderstand","thumb-down"],["Informations ou exemple de code incorrects","incorrectInformationOrSampleCode","thumb-down"],["Il n'y a pas l'information/les exemples dont j'ai besoin","missingTheInformationSamplesINeed","thumb-down"],["Problème de traduction","translationIssue","thumb-down"],["Autre","otherDown","thumb-down"]],[],[],[],null,["# Import data\n\nImports data using the import_data method.\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n from google.cloud import aiplatform\n\n\n def import_data_sample(\n project: str,\n dataset_id: str,\n gcs_source_uri: str,\n import_schema_uri: str,\n location: str = \"us-central1\",\n api_endpoint: str = \"us-central1-aiplatform.googleapis.com\",\n timeout: int = 1800,\n ):\n # The AI Platform services require regional API endpoints.\n client_options = {\"api_endpoint\": api_endpoint}\n # Initialize client that will be used to create and send requests.\n # This client only needs to be created once, and can be reused for multiple requests.\n client = aiplatform.gapic.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.dataset_service.DatasetServiceClient.html(client_options=client_options)\n # Here we use only one import config with one source\n import_configs = [\n {\n \"gcs_source\": {\"uris\": [gcs_source_uri]},\n \"import_schema_uri\": import_schema_uri,\n }\n ]\n name = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.dataset_service.DatasetServiceClient.html#google_cloud_aiplatform_v1_services_dataset_service_DatasetServiceClient_dataset_path(project=project, location=location, dataset=dataset_id)\n response = client.https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform_v1.services.dataset_service.DatasetServiceClient.html#google_cloud_aiplatform_v1_services_dataset_service_DatasetServiceClient_import_data(name=name, import_configs=import_configs)\n print(\"Long running operation:\", response.operation.name)\n import_data_response = response.result(timeout=timeout)\n print(\"import_data_response:\", import_data_response)\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=aiplatform)."]]