Loading...
    • Guide du développeur
    • Référence API
    • MCP
    • Ressources
    • Notes de version
    Search...
    ⌘K
    Ressources
    AperçuGlossairePrompts système
    Bibliothèque de promptsCosmic KeystrokesCorporate clairvoyantWebsite wizardExcel formula expertGoogle apps scripterPython bug busterTime travel consultantStorytelling sidekickCite your sourcesSQL sorcererDream interpreterPun-ditCulinary creatorPortmanteau poetHal the humorous helperLaTeX legendMood colorizerGit gudSimile savantEthical dilemma navigatorMeeting scribeIdiom illuminatorCode consultantFunction fabricatorNeologism creatorCSV converterEmoji encoderProse polisherPerspectives pondererTrivia generatorMindfulness mentorSecond-grade simplifierVR fitness innovatorPII purifierMemo maestroCareer coachGrading guruTongue twisterInterview question crafterGrammar genieRiddle me thisCode clarifierAlien anthropologistData organizerBrand builderEfficiency estimatorReview classifierDirection decoderMotivational museEmail extractorMaster moderatorLesson plannerSocratic sageAlliteration alchemistFuturistic fashion advisorPolyglot superpowersProduct naming proPhilosophical musingsSpreadsheet sorcererSci-fi scenario simulatorAdaptive editorBabel's broadcastsTweet tone detectorAirport code analyst
    Console
    Log in
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...
    Loading...

    Solutions

    • AI agents
    • Code modernization
    • Coding
    • Customer support
    • Education
    • Financial services
    • Government
    • Life sciences

    Partners

    • Amazon Bedrock
    • Google Cloud's Vertex AI

    Learn

    • Blog
    • Catalog
    • Courses
    • Use cases
    • Connectors
    • Customer stories
    • Engineering at Anthropic
    • Events
    • Powered by Claude
    • Service partners
    • Startups program

    Company

    • Anthropic
    • Careers
    • Economic Futures
    • Research
    • News
    • Responsible Scaling Policy
    • Security and compliance
    • Transparency

    Learn

    • Blog
    • Catalog
    • Courses
    • Use cases
    • Connectors
    • Customer stories
    • Engineering at Anthropic
    • Events
    • Powered by Claude
    • Service partners
    • Startups program

    Help and security

    • Availability
    • Status
    • Support
    • Discord

    Terms and policies

    • Privacy policy
    • Responsible disclosure policy
    • Terms of service: Commercial
    • Terms of service: Consumer
    • Usage policy
    Bibliothèque de prompts

    Sorcier SQL

    Transformez le langage courant en requêtes SQL.

    Copiez cette invite dans notre Console développeur pour l'essayer vous-même !

    Contenu
    SystèmeTransformez les demandes en langage naturel suivantes en requêtes SQL valides. Supposez qu'une base de données avec les tables et colonnes suivantes existe :

    Customers:
    - customer_id (INT, PRIMARY KEY)
    - first_name (VARCHAR)
    - last_name (VARCHAR)
    - email (VARCHAR)
    - phone (VARCHAR)
    - address (VARCHAR)
    - city (VARCHAR)
    - state (VARCHAR)
    - zip_code (VARCHAR)

    Products:
    - product_id (INT, PRIMARY KEY)
    - product_name (VARCHAR)
    - description (TEXT)
    - category (VARCHAR)
    - price (DECIMAL)
    - stock_quantity (INT)

    Orders:
    - order_id (INT, PRIMARY KEY)
    - customer_id (INT, FOREIGN KEY REFERENCES Customers)
    - order_date (DATE)
    - total_amount (DECIMAL)
    - status (VARCHAR)

    Order_Items:
    - order_item_id (INT, PRIMARY KEY)
    - order_id (INT, FOREIGN KEY REFERENCES Orders)
    - product_id (INT, FOREIGN KEY REFERENCES Products)
    - quantity (INT)
    - price (DECIMAL)

    Reviews:
    - review_id (INT, PRIMARY KEY)
    - product_id (INT, FOREIGN KEY REFERENCES Products)
    - customer_id (INT, FOREIGN KEY REFERENCES Customers)
    - rating (INT)
    - comment (TEXT)
    - review_date (DATE)

    Employees:
    - employee_id (INT, PRIMARY KEY)
    - first_name (VARCHAR)
    - last_name (VARCHAR)
    - email (VARCHAR)
    - phone (VARCHAR)
    - hire_date (DATE)
    - job_title (VARCHAR)
    - department (VARCHAR)
    - salary (DECIMAL)

    Fournissez la requête SQL qui récupérerait les données basées sur la demande en langage naturel.
    UtilisateurObtenez la liste des clients qui ont passé des commandes mais n'ont fourni aucun avis, ainsi que le montant total qu'ils ont dépensé en commandes.

    Exemple de sortie

    SELECT c.first_name, c.last_name, SUM(o.total_amount) AS total_spent
    FROM Customers c
    INNER JOIN Orders o ON c.customer_id = o.customer_id
    LEFT JOIN Reviews r ON c.customer_id = r.customer_id
    WHERE r.review_id IS NULL
    GROUP BY c.customer_id, c.first_name, c.last_name;
    

    Requête API


    • Exemple de sortie
    • Requête API