Sehen wir uns an, was jede dieser Optionen bedeutet:

* `main:app`: Das ist die gleiche Syntax, die auch von Uvicorn verwendet wird. `main` bedeutet das Python-Modul mit dem Namen `main`, also eine Datei `main.py`. Und `app` ist der Name der Variable, welche die **FastAPI**-Anwendung ist.
    * Stellen Sie sich einfach vor, dass `main:app` einer Python-`import`-Anweisung wie der folgenden entspricht:

        ```Python
        from main import app
        ```

        // buildOrThrow(). We would want an exception to include two values for the duplicate key.
        if (entries == entryArray) {
          // Temporary variable is necessary to defeat bad smartcast (entries adopting the type of
          // entryArray) in the Kotlin translation.
          Entry<K, V>[] originalEntries = entries;
          entries = originalEntries.clone();
        }

///

### Step 2: create a `FastAPI` "instance" { #step-2-create-a-fastapi-instance }

{* ../../docs_src/first_steps/tutorial001.py hl[3] *}

Here the `app` variable will be an "instance" of the class `FastAPI`.

This will be the main point of interaction to create all your API.

### Step 3: create a *path operation* { #step-3-create-a-path-operation }

#### Path { #path }

চাইলে এই সম্পর্কে আরো বিস্তারিত পড়তে পারেন <a href="https://en.wikipedia.org/wiki/Environment_variable" class="external-link" target="_blank">Wikipedia for Environment Variable</a> এ।

অনেক ক্ষেত্রে, দেখা মাত্রই এনভায়রনমেন্ট ভেরিয়েবল কীভাবে প্রয়োজন হবে  তা স্পষ্ট হয় না। কিন্তু ডেভেলপমেন্টের সময় আপনি নানা রকম পরিস্থিতিতে এগুলোর সম্মুখীন হবেন, তাই এগুলো সম্পর্কে জেনে রাখা ভালো।

# GPU version of TensorFlow for Python 3.12, using the public TF bazel cache and
# a local build cache:
TFCI=py312,linux_x86_cuda,public_cache,disk_cache ci/official/wheel.sh

# First, set your TFCI variable to choose the environment settings.
#   TFCI is a comma-separated list of filenames from the envs directory, which
#   are all settings for the scripts. TF's CI jobs are all made of a combination
#   of these env files.
#

Escribes Python estándar con tipos:

```Python
from datetime import date

from pydantic import BaseModel

# Declara una variable como un str
# y obtiene soporte del editor dentro de la función
def main(user_id: str):
    return user_id


# Un modelo de Pydantic
class User(BaseModel):
    id: int
    name: str
    joined: date

        lenient().when(tree.isConnected()).thenReturn(connected);
        lenient().when(tree.isSMB2()).thenReturn(smb2);
    }

    @Test
    @DisplayName("Constructor with null tree throws NPE (byte[] fid variant)")
    void constructor_nullTree_byteArray_throwsNPE() {
        lenient().when(cfg.isTraceResourceUsage()).thenReturn(false);
        assertThrows(NullPointerException.class,

</li>

</ul>

<p>
The value of <code>GOMIPS</code> environment variable (<code>hardfloat</code> or
<code>softfloat</code>) is made available to assembly code by predefining either
<code>GOMIPS_hardfloat</code> or <code>GOMIPS_softfloat</code>.
</p>

<p>
The value of <code>GOMIPS64</code> environment variable (<code>hardfloat</code> or

/// info
Nếu bạn đã biết về các môi trường ảo, cách tạo chúng và sử dụng chúng, bạn có thể bỏ qua phần này. 🤓

///

/// tip

Một **môi trường ảo** khác với một **biến môi trường (environment variable)**.

Một **biến môi trường** là một biến trong hệ thống có thể được sử dụng bởi các chương trình.

Một **môi trường ảo** là một thư mục với một số tệp trong đó.

///

/// info

Bạn viết chuẩn Python với kiểu dữ liệu như sau:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str
# and get editor support inside the function
def main(user_id: str):
    return user_id


# A Pydantic model
class User(BaseModel):
    id: int
    name: str
    joined: date
```