Abre VS Code y, luego, en la barra de actividades, haz clic en Extensiones.
En la barra de búsqueda, busca la extensión Jupyter y, luego, haz clic en Instalar. Las funciones de BigQuery en VS Code requieren la extensión de Jupyter de Microsoft como dependencia.
Instala la extensión de Google Cloud
Abre VS Code y, luego, en la barra de actividades, haz clic en Extensiones.
En la barra de búsqueda, busca la extensión Google Cloud Code y, luego, haz clic en Instalar.
Si se te solicita, reinicia VS Code.
El ícono de Google Cloud Code ahora está visible en la barra de actividades.
Configura la extensión
Abre VS Code y, luego, en la barra de actividades, haz clic en Google Cloud Code.
Abre la sección Notebooks de BigQuery.
Haz clic en Acceder a Google Cloud. Se te redireccionará para que accedas con tus credenciales.
Usa la barra de tareas de nivel superior de la aplicación para navegar a Código > Configuración > Configuración > Extensiones.
Busca Google Cloud Code y haz clic en el ícono Administrar para abrir el menú.
Selecciona Configuración.
En el parámetro de configuración Cloud Code: Project, ingresa el nombre del proyectoGoogle Cloud que deseas usar para ejecutar notebooks y mostrar conjuntos de datos de BigQuery.
En el parámetro de configuración Cloud Code > Beta: BigQuery Region, ingresa una ubicación de BigQuery.
La extensión muestra los conjuntos de datos de esta ubicación.
Desarrolla notebooks de BigQuery
Abre VS Code y, luego, en la barra de actividades, haz clic en Google Cloud Code.
Abre la sección Notebooks de BigQuery y haz clic en Notebook de BigQuery. Se crea un nuevo archivo .ipynb que contiene código de muestra y se abre en el editor.
En el notebook nuevo, haz clic en Seleccionar kernel y elige un kernel de Python.
Los notebooks de BigQuery requieren un kernel de Python local para la ejecución. Puedes crear un entorno virtual nuevo o usar uno de los existentes.
Si aún no se instaló en tu entorno virtual, instala la biblioteca cliente de bigframes:
Abre la ventana de Terminal.
Ejecuta el comando pip install bigframes.
Ahora puedes escribir y ejecutar código en tu notebook de BigQuery.
Explora y obtén una vista previa de los conjuntos de datos de BigQuery
Abre VS Code y, luego, en la barra de actividades, haz clic en Google Cloud Code.
Para ver los conjuntos de datos y las tablas del proyecto y la región que especificaste, abre la sección BigQuery Datasets. También se ven los conjuntos de datos públicos de BigQuery.
Para abrir una pestaña nueva en el editor, haz clic en cualquier nombre de tabla. Esta pestaña contiene los detalles, el esquema y la vista previa de la tabla.
Precios
La extensión de Visual Studio Code es gratuita, pero se te cobrará por los servicios deGoogle Cloud que uses (BigQuery, Dataproc, Cloud Storage).
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-09-04 (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)."]]
