### The Problem

So, what's the problem with installing packages in the global Python environment?

At some point, you will probably end up writing many different programs that depend on **different packages**. And some of these projects you work on will depend on **different versions** of the same package. 😱

  // Most recently observed status of the Deployment.
  // +optional
  optional DeploymentStatus status = 3;
}

// DeploymentCondition describes the state of a deployment at a certain point.
message DeploymentCondition {
  // Type of deployment condition.
  optional string type = 1;

  // Status of the condition, one of True, False, Unknown.
  optional string status = 2;

    }
    public static int enc_floatbe( float f, byte[] dst, int di )
    {
        return enc_uint32be( Float.floatToIntBits( f ), dst, di );
    }

    /* Decode floating point numbers
     */

    public static float dec_floatle( byte[] src, int si )
    {
        return Float.intBitsToFloat( dec_uint32le( src, si ));
    }
    public static float dec_floatbe( byte[] src, int si )

                                return response.addrEntry[0];
                            } else if( resolveOrder[i] == RESOLVER_WINS ) {
                                /* If WINS reports negative, no point in retry
                                 */
                                break;
                            }
                        }
                        break;
                }

        for (RepositorySystemSessionExtender extender : sessionExtenders.values()) {
            extender.extend(request, configProps, mirrorSelector, proxySelector, authSelector);
        }

        // at this point we have "config" with pure MANDATORY resolver config, so resolver final config properties are
        // mergedProperties + configProperties
        HashMap<String, Object> finalConfigProperties = new HashMap<>();

	bucketCh := make(chan BucketInfo, len(buckets))

	// Shuffle buckets to ensure total randomness of buckets, being scanned.
	// Otherwise same set of buckets get scanned across erasure sets always.
	// at any given point in time. This allows different buckets to be scanned
	// in different order per erasure set, this wider spread is needed when
	// there are lots of buckets with different order of objects in them.

  // +optional
  optional DaemonSetStatus status = 3;
}

// DaemonSetCondition describes the state of a DaemonSet at a certain point.
message DaemonSetCondition {
  // Type of DaemonSet condition.
  optional string type = 1;

  // Status of the condition, one of True, False, Unknown.
  optional string status = 2;

# We have some invalid linker scripts in the build,
# so we need to disable this check
build:release_linux_base --linkopt=-Wl,--undefined-version

# Container environment settings below this point.
# Use Python 3.X as installed in container image
build:release_linux_base --action_env PYTHON_BIN_PATH="/usr/bin/python3"
build:release_linux_base --action_env PYTHON_LIB_PATH="/usr/lib/tf_python"

/// check

So, with the same Python type declaration, **FastAPI** gives you data validation.

Notice that the error also clearly states exactly the point where the validation didn't pass.

This is incredibly helpful while developing and debugging code that interacts with your API.

///

## Documentation

### Étape 2 : créer une "instance" `FastAPI`

```Python hl_lines="3"
{!../../docs_src/first_steps/tutorial001.py!}
```

Ici la variable `app` sera une "instance" de la classe `FastAPI`.

Ce sera le point principal d'interaction pour créer toute votre API.

Cette `app` est la même que celle à laquelle fait référence `uvicorn` dans la commande :

<div class="termy">

```console
$ uvicorn main:app --reload