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docs/pt/docs/tutorial/body-fields.md
Você irá aprender mais sobre adicionar informações extras posteriormente nessa documentação, quando estiver aprendendo a declarar exemplos. ## Recapitulando Você pode usar `Field` do Pydantic para declarar validações extras e metadados para atributos do modelo.
Registered: Sun Sep 07 07:19:17 UTC 2025 - Last Modified: Mon Nov 18 02:25:44 UTC 2024 - 2.1K bytes - Viewed (0) -
docs/en/docs/tutorial/dependencies/dependencies-with-yield.md
would be valid to use as a **FastAPI** dependency. In fact, FastAPI uses those two decorators internally. /// ## A database dependency with `yield` { #a-database-dependency-with-yield } For example, you could use this to create a database session and close it after finishing. Only the code prior to and including the `yield` statement is executed before creating a response:
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docs/sts/dex.md
time="2020-07-12T20:45:50Z" level=info msg="config issuer: http://127.0.0.1:5556/dex" time="2020-07-12T20:45:50Z" level=info msg="config storage: sqlite3" time="2020-07-12T20:45:50Z" level=info msg="config static client: Example App" time="2020-07-12T20:45:50Z" level=info msg="config connector: mock" time="2020-07-12T20:45:50Z" level=info msg="config connector: local passwords enabled"
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okhttp-logging-interceptor/src/main/kotlin/okhttp3/logging/HttpLoggingInterceptor.kt
* * Example: * ``` * --> POST /greeting http/1.1 (3-byte body) * * <-- 200 OK (22ms, 6-byte body) * ``` */ BASIC, /** * Logs request and response lines and their respective headers. * * Example: * ``` * --> POST /greeting http/1.1 * Host: example.com * Content-Type: plain/text
Registered: Fri Sep 05 11:42:10 UTC 2025 - Last Modified: Thu Aug 21 14:27:04 UTC 2025 - 11.4K bytes - Viewed (0) -
docs/es/docs/tutorial/request-forms-and-files.md
Asegúrate de crear un [entorno virtual](../virtual-environments.md){.internal-link target=_blank}, actívalo y luego instálalo, por ejemplo: ```console $ pip install python-multipart ``` /// ## Importar `File` y `Form` {* ../../docs_src/request_forms_and_files/tutorial001_an_py39.py hl[3] *} ## Definir parámetros `File` y `Form`
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docs/en/docs/python-types.md
For example "**Python 3.6+**" means it's compatible with Python 3.6 or above (including 3.7, 3.8, 3.9, 3.10, etc). And "**Python 3.9+**" means it's compatible with Python 3.9 or above (including 3.10, etc). If you can use the **latest versions of Python**, use the examples for the latest version, those will have the **best and simplest syntax**, for example, "**Python 3.10+**". #### List { #list }
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docs/en/docs/tutorial/request-files.md
As all these methods are `async` methods, you need to "await" them. For example, inside of an `async` *path operation function* you can get the contents with: ```Python contents = await myfile.read() ``` If you are inside of a normal `def` *path operation function*, you can access the `UploadFile.file` directly, for example: ```Python contents = myfile.file.read() ``` /// note | `async` Technical Details
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docs/fr/docs/tutorial/path-params.md
{* ../../docs_src/path_params/tutorial001.py hl[6:7] *} La valeur du paramètre `item_id` sera transmise à la fonction dans l'argument `item_id`. Donc, si vous exécutez cet exemple et allez sur <a href="http://127.0.0.1:8000/items/foo" class="external-link" target="_blank">http://127.0.0.1:8000/items/foo</a>, vous verrez comme réponse : ```JSON {"item_id":"foo"} ```
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docs/en/docs/advanced/additional-responses.md
**FastAPI** will keep the additional information from `responses`, and combine it with the JSON Schema from your model. For example, you can declare a response with a status code `404` that uses a Pydantic model and has a custom `description`. And a response with a status code `200` that uses your `response_model`, but includes a custom `example`: {* ../../docs_src/additional_responses/tutorial003.py hl[20:31] *}
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docs/en/docs/tutorial/query-params.md
For example, in the URL: ``` http://127.0.0.1:8000/items/?skip=0&limit=10 ``` ...the query parameters are: * `skip`: with a value of `0` * `limit`: with a value of `10` As they are part of the URL, they are "naturally" strings. But when you declare them with Python types (in the example above, as `int`), they are converted to that type and validated against it.
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