Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

## Segunda dependência, "injetável" e "dependente"

Então, você pode criar uma outra função para uma dependência (um "injetável") que ao mesmo tempo declara sua própria dependência (o que faz dela um "dependente" também):

{* ../../docs_src/dependencies/tutorial005_an_py310.py hl[13] *}

Vamos focar nos parâmetros declarados:

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

/// info

If you are using containers, for example with Docker or Kubernetes, I'll tell you more about that in the next chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers { #multiple-workers }

## Why Pull Requests?

Pull Requests (PRs) drive quality in MinIO’s codebase by:
- Enabling peer review without pair programming.
- Documenting changes for future reference.
- Ensuring commits tell a clear story of development.

**A poor commit lasts forever, even if code is refactored.**

## Crafting a Quality PR

A strong MinIO PR:
- Delivers a complete, valuable change (feature, bug fix, or improvement).

    url: https://github.com/fastapi/fastapi/discussions/categories/questions
  - name: Show and tell
    about: Show what you built with FastAPI or to be used with FastAPI.
    url: https://github.com/fastapi/fastapi/discussions/categories/show-and-tell
  - name: Translations
    about: Coordinate translations in GitHub Discussions.

      description: If compiling from source
  - type: textarea
    id: what-happened
    attributes:
      label: Current behavior?
      description: Also tell us, what did you expect to happen?
      placeholder: Tell us what you see!
    validations:
      required: true
  - type: textarea
    id: code-to-reproduce
    attributes:
      label: Standalone code to reproduce the issue

In many frameworks and systems just handling security and authentication takes a big amount of effort and code (in many cases it can be 50% or more of all the code written).

**FastAPI** provides several tools to help you deal with **Security** easily, rapidly, in a standard way, without having to study and learn all the security specifications.

But first, let's check some small concepts.

## In a hurry? { #in-a-hurry }

 
<!--- Provide a general summary of the issue in the Title above -->

## Expected Behavior
<!--- If you're describing a bug, tell us what should happen -->
<!--- If you're suggesting a change/improvement, tell us how it should work -->

## Current Behavior
<!--- If describing a bug, tell us what happens instead of the expected behavior -->
<!--- If suggesting a change/improvement, explain the difference from current behavior -->

# Note that numpy 2.1.0 does not support python 3.9
numpy >= 2.0.0, < 2.2.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras