//tensorflow/python:mixed_precision
//tensorflow/python:tf_optimizer
//tensorflow/python:compare_test_proto_py
//tensorflow/python/framework:test_file_system.so
//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py

<div class="termy">

```console
$ python myapp.py
```

</div>

但當其他檔案匯入它時不會執行，例如：

```Python
from myapp import app
```

#### 更多細節 { #more-details }

假設你的檔名是 `myapp.py`。

如果你用以下方式執行它：

<div class="termy">

```console
$ python myapp.py
```

</div>

那麼在你的檔案中，由 Python 自動建立的內部變數 `__name__`，其值會是字串 `"__main__"`。

因此，這段：

```Python

![ReDoc](https://fastapi.tiangolo.com/img/index/index-06-redoc-02.png)

### 現代的なPythonのみ { #just-modern-python }

すべて標準の **Python の型** 宣言（Pydantic に感謝）に基づいています。新しい構文を学ぶ必要はありません。標準的でモダンな Python だけです。

（FastAPI を使わない場合でも）Python の型の使い方を 2 分で復習したい場合は、短いチュートリアル [Python の型](python-types.md) を参照してください。

型を使った標準的な Python を記述します:

```Python
from datetime import date

from pydantic import BaseModel

它們大致位於相反兩端，彼此互補。

Requests 設計非常簡單直觀、容易使用，且有合理的預設值。同時它也非常強大且可自訂。

因此，如其官網所言：

> Requests is one of the most downloaded Python packages of all time

用法非常簡單。例如，發出一個 `GET` 請求，你會寫：

```Python
response = requests.get("http://example.com/some/url")
```

相對地，FastAPI 的 API 路徑操作（path operation）可能像這樣：

```Python hl_lines="1"
@app.get("/some/url")
def read_url():
    return {"message": "Hello World"}
```

# Code blocks { #code-blocks }

Some text

```python
# This is a sample Python code block
def hello_world():
    # Comment with indentation
    print("Hello, world!")  # Print greeting
```

Some more text

The following block is missing first line:

```toml
title = "TOML Example"  # Title of the document
```

And more text

```console
// Use the command "live" and pass the language code as a CLI argument

Some text

```python
# This is a sample Python code block
def hello_world():
    # Comment with indentation
    print("Hello, world!")  # Print greeting
```

Some more text

```toml
# This is a sample TOML code block
title = "TOML Example"  # Title of the document
```

And more text

```console
// Use the command "live" and pass the language code as a CLI argument
$ python ./scripts/docs.py live es

        ```bash
        python -c "import pydantic; print(pydantic.version.VERSION)"
        ```
    validations:
      required: true
  - type: input
    id: python-version
    attributes:
      label: Python Version
      description: |
        What Python version are you using?

        You can find the Python version with:

        ```bash
        python --version

/tenosrflow/core/debug @caisq
/tensorflow/core/kernels/mkl/ @penpornk
/tensorflow/core/kernels/sparse/ @penpornk
/tensorflow/core/nccl/ @azaks2 @chsigg
/tensorflow/python/autograph/ @mdanatg
/tensorflow/python/debug @caisq
/tensorflow/python/eager @rohan100jain
/tensorflow/tools/docs/ @markdaoust
/tensorflow/compiler/mlir/ @aminim
/tensorflow/core/ir/ @aminim
/tensorflow/core/transforms/ @aminim

그렇다면 "timing attack"이란 무엇일까요?

공격자들이 사용자명과 비밀번호를 추측하려고 한다고 가정해봅시다.

그리고 사용자명 `johndoe`, 비밀번호 `love123`으로 요청을 보냅니다.

그러면 애플리케이션의 Python 코드는 대략 다음과 같을 것입니다:

```Python
if "johndoe" == "stanleyjobson" and "love123" == "swordfish":
    ...
```

/// warning

The Pydantic team stopped support for Pydantic v1 for the latest versions of Python, starting with **Python 3.14**.

This includes `pydantic.v1`, which is no longer supported in Python 3.14 and above.

If you want to use the latest features of Python, you will need to make sure you use Pydantic v2.

///