Abra o VS Code e, na barra de atividades, clique em Extensões.
Na barra de pesquisa, encontre a extensão Jupyter e clique em
Instalar. Os recursos do BigQuery no VS Code exigem a extensão
Jupyter da Microsoft como uma dependência.
Instalar a extensão Google Cloud
Abra o VS Code e, na barra de atividades, clique em Extensões.
Na barra de pesquisa, encontre a extensão Google Cloud Code e clique em
Instalar.
Se solicitado, reinicie o VS Code.
O ícone do Google Cloud Code agora está visível na barra de atividades.
Configurar a extensão
Abra o VS Code e, na barra de atividades, clique em Google Cloud Code.
Abra a seção Notebooks do BigQuery.
Clique em Fazer login no Google Cloud. Você será redirecionado para fazer login com suas credenciais.
Use a barra de tarefas superior do aplicativo para navegar até
Código > Configurações > Configurações > Extensões.
Encontre o Google Cloud Code e clique no ícone Gerenciar para abrir o menu.
Selecione Configurações.
Na configuração Cloud Code: Projeto, insira o nome do
projetoGoogle Cloud que você quer usar para executar notebooks e
mostrar conjuntos de dados do BigQuery.
Na configuração Cloud Code > Beta: região do BigQuery, insira um local do BigQuery.
A extensão mostra conjuntos de dados desse local.
Desenvolver notebooks do BigQuery
Abra o VS Code e, na barra de atividades, clique em Google Cloud Code.
Abra a seção Notebooks do BigQuery e clique em Notebook do BigQuery. Um novo arquivo .ipynb com um exemplo de código é criado e aberto no editor.
No novo notebook, clique em Selecionar kernel e escolha um kernel do Python.
Os notebooks do BigQuery exigem um kernel Python local para
execução. Você pode criar um novo ambiente virtual ou usar um dos existentes.
Se ela ainda não tiver sido instalada no seu ambiente virtual, instale a biblioteca de cliente
bigframes:
Abra a janela Terminal.
Execute o comando pip install bigframes.
Agora é possível escrever e executar código no notebook do BigQuery.
Analisar e visualizar conjuntos de dados do BigQuery
Abra o VS Code e, na barra de atividades, clique em Google Cloud Code.
Para ver conjuntos de dados e tabelas do projeto e da região especificados, abra a seção Conjuntos de dados do BigQuery. Os conjuntos de dados públicos do BigQuery também ficam visíveis.
Para abrir uma nova guia no editor, clique em qualquer nome de tabela. Essa guia contém os detalhes, o esquema e a prévia da tabela.
Preços
A extensão do Visual Studio Code é gratuita, mas há cobranças pelos
serviçosGoogle Cloud (BigQuery, Dataproc,
Cloud Storage) que você usa.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-09-09 UTC."],[[["\u003cp\u003eThe Google Cloud extension for Visual Studio Code allows users to develop and execute BigQuery notebooks, as well as browse, inspect, and preview BigQuery datasets directly within VS Code.\u003c/p\u003e\n"],["\u003cp\u003eBefore using the extension, you must ensure Python 3.11 or later is installed, install the Google Cloud CLI, initialize the gcloud CLI, configure a default project, set up Application Default Credentials, download VS Code, and install the Jupyter extension.\u003c/p\u003e\n"],["\u003cp\u003eInstalling the Google Cloud Code extension in VS Code is necessary to access its features, including the BigQuery Notebooks and BigQuery Datasets sections.\u003c/p\u003e\n"],["\u003cp\u003eTo develop BigQuery notebooks, users must select a Python kernel, and the \u003ccode\u003ebigframes\u003c/code\u003e client library should be installed in their virtual environment.\u003c/p\u003e\n"],["\u003cp\u003eThe Visual Studio Code extension itself is free, however, usage of Google Cloud services like BigQuery will incur charges.\u003c/p\u003e\n"]]],[],null,["# Use the Google Cloud for Visual Studio Code extension\n=====================================================\n\n|\n| **Preview**\n|\n|\n| This product or feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA products and features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n| **Note:** To provide feedback or ask questions that are related to this Preview feature, contact [bigquery-ide-plugin@google.com](mailto:bigquery-ide-plugin@google.com).\n\nThe Google Cloud [Visual Studio Code (VS Code)](https://code.visualstudio.com/)\nextension lets you do the following in VS Code:\n\n- Develop and execute BigQuery notebooks.\n- Browse, inspect, and preview BigQuery datasets.\n\nBefore you begin\n----------------\n\n1. In your local terminal, check to make sure you have\n [Python 3.11](https://www.python.org/downloads/) or later installed on your\n system:\n\n ```bash\n python3 --version\n ```\n2. [Install the Google Cloud CLI](/sdk/docs/install).\n\n3. In your local terminal,\n [initialize the gcloud CLI](/sdk/docs/initializing):\n\n ```bash\n gcloud init\n ```\n4. Configure a default project:\n\n ```bash\n gcloud config set project PROJECT_ID\n ```\n\n Replace \u003cvar translate=\"no\"\u003e\u003ccode translate=\"no\" dir=\"ltr\"\u003ePROJECT_ID\u003c/code\u003e\u003c/var\u003e with your default project.\n5. Set up [Application Default Credentials](/bigquery/docs/authentication):\n\n ```bash\n gcloud auth application-default login\n ```\n6. [Download and install VS Code](https://code.visualstudio.com/download).\n\n7. Open VS Code, and then in the activity bar, click **Extensions**.\n\n8. Using the search bar, find the **Jupyter** extension, and then click\n **Install**. The BigQuery features in VS Code require the\n Jupyter extension by Microsoft as a dependency.\n\nInstall the Google Cloud extension\n----------------------------------\n\n1. Open VS Code, and then in the activity bar, click **Extensions**.\n2. Using the search bar, find the **Google Cloud Code** extension, and then\n click **Install**.\n\n3. If prompted, restart VS Code.\n\nThe **Google Cloud Code** icon is now visible in the activity bar.\n\nConfigure the extension\n-----------------------\n\n1. Open VS Code, and then in the activity bar, click **Google Cloud Code**.\n2. Open the **BigQuery Notebooks** section.\n3. Click **Login to Google Cloud**. You are redirected to sign in with your credentials.\n4. Use the top-level application taskbar to navigate to **Code \\\u003e Settings \\\u003e Settings \\\u003e Extensions**.\n5. Find **Google Cloud Code** , and click the **Manage** icon to open the menu.\n6. Select **Settings**.\n7. For the **Cloud Code: Project** setting, enter the name of the Google Cloud project that you want to use to execute notebooks and display BigQuery datasets.\n8. For the **Cloud Code \\\u003e Beta: BigQuery Region** setting, enter a [BigQuery location](/bigquery/docs/locations#supported_locations). The extension displays datasets from this location.\n\nDevelop BigQuery notebooks\n--------------------------\n\n1. Open VS Code, and then in the activity bar, click **Google Cloud Code**.\n2. Open the **BigQuery Notebooks** section, and click **BigQuery Notebook** . A new `.ipynb` file containing sample code is created and opened in the editor.\n3. In the new notebook, click **Select Kernel**, and select a Python kernel.\n BigQuery notebooks require a local Python kernel for\n execution. You can create a new virtual environment or use one of the\n existing ones.\n\n4. If it hasn't already been installed in your virtual environment, install the\n `bigframes` client library:\n\n 1. Open the **Terminal** window.\n 2. Run the `pip install bigframes` command.\n\nYou can now write and execute code in your BigQuery notebook.\n\nExplore and preview BigQuery datasets\n-------------------------------------\n\n1. Open VS Code, and then in the activity bar, click **Google Cloud Code**.\n2. To see datasets and tables from your specified project and region, open the **BigQuery Datasets** section. BigQuery public datasets are also visible.\n3. To open a new tab in the editor, click any table name. This tab contains the table details, schema, and preview.\n\nPricing\n-------\n\nThe Visual Studio Code extension is free, but you are charged for any\nGoogle Cloud services (BigQuery, Dataproc,\nCloud Storage) that you use.\n\nWhat's next\n-----------\n\n- Learn more about [notebooks in BigQuery](/bigquery/docs/programmatic-analysis).\n- Learn more about [BigQuery DataFrames](/bigquery/docs/bigquery-dataframes-introduction)."]]
