Apri VS Code, quindi fai clic su Estensioni nella barra delle attività.
Utilizza la barra di ricerca per trovare l'estensione Jupyter, quindi fai clic su
Installa. Le funzionalità di BigQuery in VS Code richiedono l'estensione Jupyter di Microsoft come dipendenza.
Installa l' Google Cloud estensione
Apri VS Code, quindi fai clic su Estensioni nella barra delle attività.
Utilizzando la barra di ricerca, trova l'estensione Google Cloud Code, quindi
fai clic su Installa.
Se richiesto, riavvia VS Code.
L'icona Google Cloud Code è ora visibile nella barra delle attività.
Configurare l'estensione
Apri VS Code, poi fai clic su Google Cloud Code nella barra delle attività.
Apri la sezione BigQuery Notebooks.
Fai clic su Accedi a Google Cloud. Viene visualizzata la pagina di accesso con le tue
credenziali.
Utilizza la barra delle applicazioni di primo livello per andare a
Code > Settings > Settings > Extensions.
Trova Google Cloud Code e fai clic sull'icona Gestisci per aprire il menu.
Seleziona Settings (Impostazioni).
Per l'impostazione Cloud Code: Project, inserisci il nome del progettoGoogle Cloud che vuoi utilizzare per eseguire i blocchi note e visualizzare i set di dati BigQuery.
Per l'impostazione Cloud Code > Beta: BigQuery Region, inserisci una
posizione BigQuery.
L'estensione mostra i set di dati di questa posizione.
Sviluppare notebook BigQuery
Apri VS Code, poi fai clic su Google Cloud Code nella barra delle attività.
Apri la sezione BigQuery Notebooks e fai clic su BigQuery Notebook. Un
nuovo file .ipynb contenente codice campione viene creato e aperto nell'editor.
Nel nuovo notebook, fai clic su Seleziona kernel e seleziona un kernel Python.
I notebook BigQuery richiedono un kernel Python locale per l'esecuzione. Puoi creare un nuovo ambiente virtuale o utilizzarne uno esistente.
Se non è già stata installata nell'ambiente virtuale, installa la libreria client
bigframes:
Apri la finestra Terminale.
Esegui il comando pip install bigframes.
Ora puoi scrivere ed eseguire codice nel tuo blocco note BigQuery.
Esplorare e visualizzare l'anteprima dei set di dati BigQuery
Apri VS Code, poi fai clic su Google Cloud Code nella barra delle attività.
Per visualizzare i set di dati e le tabelle del progetto e della regione specificati, apri la sezione
Set di dati BigQuery. Sono visibili anche i set di dati pubblici BigQuery.
Per aprire una nuova scheda nell'editor, fai clic sul nome di una tabella. Questa scheda contiene i dettagli, lo schema e l'anteprima della tabella.
Prezzi
L'estensione Visual Studio Code è gratuita, ma ti vengono addebitati costi per tutti i serviziGoogle Cloud (BigQuery, Dataproc, Cloud Storage) che utilizzi.
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 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)."]]
