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docs/en/docs/img/sponsors/scalar.svg
scalar.svg...
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docs/tr/docs/tutorial/path-params.md
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docs/en/data/translators.yml
avatarUrl: https://avatars.githubusercontent.com/u/53824764?u=db3d0cea2f5fab64d810113c5039a369699a2774&v=4 url: https://github.com/timothy-jeong gerry-sabar: login: gerry-sabar count: 3 avatarUrl: https://avatars.githubusercontent.com/u/1120123?v=4 url: https://github.com/gerry-sabar Rishat-F: login: Rishat-F count: 3 avatarUrl: https://avatars.githubusercontent.com/u/66554797?v=4 url: https://github.com/Rishat-F
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docs/en/data/github_sponsors.yml
url: https://github.com/requestly - login: acsone avatarUrl: https://avatars.githubusercontent.com/u/7601056?v=4 url: https://github.com/acsone - - login: scalar avatarUrl: https://avatars.githubusercontent.com/u/301879?v=4 url: https://github.com/scalar - login: Trivie avatarUrl: https://avatars.githubusercontent.com/u/8161763?v=4 url: https://github.com/Trivie - - login: takashi-yoneyaRegistered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Mon Dec 01 06:30:56 UTC 2025 - 20.1K bytes - Viewed (0) -
docs/pt/docs/deployment/docker.md
4. Instale as dependências de pacote vindas do arquivo de requisitos. A opção `--no-cache-dir` diz ao `pip` para não salvar os pacotes baixados localmente, pois isso só aconteceria se `pip` fosse executado novamente para instalar os mesmos pacotes, mas esse não é o caso quando trabalhamos com contêineres. /// note | NotaRegistered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Wed Nov 12 16:23:57 UTC 2025 - 32.1K bytes - Viewed (0) -
README.md
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docs/en/data/topic_repos.yml
- name: langserve html_url: https://github.com/langchain-ai/langserve stars: 2215 owner_login: langchain-ai owner_html_url: https://github.com/langchain-ai - name: solara html_url: https://github.com/widgetti/solara stars: 2122 owner_login: widgetti owner_html_url: https://github.com/widgetti - name: mangum html_url: https://github.com/Kludex/mangum stars: 2029 owner_login: Kludex
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docs/pt/docs/tutorial/security/simple-oauth2.md
Neste ponto temos os dados do usuário do nosso banco de dados, mas não verificamos a senha. Vamos colocar esses dados primeiro no modelo `UserInDB` do Pydantic. Você nunca deve salvar senhas em texto simples, portanto, usaremos o sistema de hashing de senhas (falsas). Se as senhas não corresponderem, retornaremos o mesmo erro. #### Hashing de senha { #password-hashing }
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docs/en/docs/tutorial/query-params-str-validations.md
Then with `random.choice()` we can get a **random value** from the list, so, we get a tuple with `(id, name)`. It will be something like `("imdb-tt0371724", "The Hitchhiker's Guide to the Galaxy")`. Then we **assign those two values** of the tuple to the variables `id` and `name`. So, if the user didn't provide an item ID, they will still receive a random suggestion.
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docs/en/docs/tutorial/response-model.md
You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc. {* ../../docs_src/response_model/tutorial001_01_py310.py hl[16,21] *} FastAPI will use this return type to: * **Validate** the returned data.Registered: Sun Dec 28 07:19:09 UTC 2025 - Last Modified: Sat Dec 20 15:55:38 UTC 2025 - 15.5K bytes - Viewed (0)