assertFalse("Unsafe file should be blocked", FileUtil.isPathSafe(unsafeFile, baseDir));
    }

    /**
     * Test isPathSafe with path inside base directory
     *
     * @throws Exception
     */
    @Test
    public void testIsPathSafe_PathInsideBase() throws Exception {
        final Path baseDir = tempFolder.getRoot().toPath();

You write standard Python with types:

```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
```

That can then be used like:

```Python

# This Dockerfile creates an image that has:
# - the correct MTU setting for networking from inside the container to work.
# - Visual Studio 2022 Build Tools
# - MSVC 14.39
# - LLVM/Clang 18.1.4
# - MSYS2 + curl, git, patch, vim, unzip, zip
# - Python 3.9 - 3.13
# - Bazelisk 1.22.1
# - JDK 21 (Azul Zulu)

FROM mcr.microsoft.com/windows/servercore:ltsc2022

SHELL ["powershell.exe", "-ExecutionPolicy", "Bypass", "-Command", \

So, if you have another file `importer.py` with:

```Python
from myapp import app

# Some more code
```

in that case, the automatically created variable `__name__` inside of `myapp.py` will not have the value `"__main__"`.

So, the line:

```Python
    uvicorn.run(app, host="0.0.0.0", port=8000)
```

will not be executed.

/// info

You can use `async def` or normal `def`.

And you can declare dependencies with `async def` inside of normal `def` *path operation functions*, or `def` dependencies inside of `async def` *path operation functions*, etc.

It doesn't matter. **FastAPI** will know what to do.

/// note

# above is tagged with "py3-none-any". We cannot change the tags by simply
# renaming the wheels as uploading to PyPI would fail with "File already exists"
# error. In order to upload to PyPI, we unpack the wheel and change the tag
# inside a metadata file to the one we want (e.g cp38-cp38-win_amd) and then
# re-pack it to generate it as a platform specific wheel with this new wheel
#tag.
python3 -m wheel unpack "${pure_python_whl}"

# Dependencies in path operation decorators { #dependencies-in-path-operation-decorators }

In some cases you don't really need the return value of a dependency inside your *path operation function*.

Or the dependency doesn't return a value.

But you still need it to be executed/solved.

For those cases, instead of declaring a *path operation function* parameter with `Depends`, you can add a `list` of `dependencies` to the *path operation decorator*.

Then, behind the scenes, it would put that JSON-compatible data (e.g. a `dict`) inside of a `JSONResponse` that would be used to send the response to the client.

But you can return a `JSONResponse` directly from your *path operations*.

It might be useful, for example, to return custom headers or cookies.

The way it works is that you write the definition of the schema using YAML format inside the docstring of each function handling a route.

And it generates OpenAPI schemas.

That's how it works in Flask, Starlette, Responder, etc.

But then, we have again the problem of having a micro-syntax, inside of a Python string (a big YAML).

    try {
      return fromValid(specifier);
    } catch (IllegalArgumentException e) {
      // Since the IAE can originate at several different points inside
      // fromValid(), we implement this method in terms of that one rather
      // than the reverse.

      ParseException parseException = new ParseException("Invalid host specifier: " + specifier, 0);