from pdm.backend.hooks import Context

TIANGOLO_BUILD_PACKAGE = os.getenv("TIANGOLO_BUILD_PACKAGE", "fastapi")


def pdm_build_initialize(context: Context) -> None:
    metadata = context.config.metadata
    # Get custom config for the current package, from the env var
    config: Dict[str, Any] = context.config.data["tool"]["tiangolo"][
        "_internal-slim-build"
    ]["packages"][TIANGOLO_BUILD_PACKAGE]

          # cache: "pip"
          # cache-dependency-path: pyproject.toml
      - name: Install build dependencies
        run: pip install build
      - name: Build distribution
        env:
          TIANGOLO_BUILD_PACKAGE: ${{ matrix.package }}
        run: python -m build
      - name: Publish
        uses: pypa/gh-action-pypi-publish@v1.8.14
      - name: Dump GitHub context
        env:

        uses: actions/setup-python@v5
        with:
          python-version: "3.10"
      - name: Install build dependencies
        run: pip install build
      - name: Build source distribution
        env:
          TIANGOLO_BUILD_PACKAGE: ${{ matrix.package }}
        run: python -m build --sdist
      - name: Decompress source distribution
        run: |
          cd dist
          tar xvf fastapi*.tar.gz

* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.
    * But it provides you the tools to build simple web applications, with routing based on paths, etc.
    * If you are comparing Starlette, compare it against Sanic, Flask, Django, etc. Web frameworks (or microframeworks).
* **FastAPI**:

## Previous tools

### <a href="https://www.djangoproject.com/" class="external-link" target="_blank">Django</a>

It's the most popular Python framework and is widely trusted. It is used to build systems like Instagram.

It's relatively tightly coupled with relational databases (like MySQL or PostgreSQL), so, having a NoSQL database (like Couchbase, MongoDB, Cassandra, etc) as the main store engine is not very easy.

---

"_Honestly, what you've built looks super solid and polished. In many ways, it's what I wanted **Hug** to be - it's really inspiring to see someone build that._"

---

"_Honestly, what you've built looks super solid and polished. In many ways, it's what I wanted **Hug** to be - it's really inspiring to see someone build that._"

* <a href="https://github.com/django/daphne" class="external-link" target="_blank">Daphne</a>: the ASGI server built for Django Channels.

## Server Machine and Server Program

There's a small detail about names to keep in mind. 💡

# Using Dataclasses

FastAPI is built on top of **Pydantic**, and I have been showing you how to use Pydantic models to declare requests and responses.

But FastAPI also supports using <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a> the same way:

```Python hl_lines="1  7-12  19-20"
{!../../../docs_src/dataclasses/tutorial001.py!}
```

This also means that if something changed it will be **reflected** on the client code automatically. And if you **build** the client it will error out if you have any **mismatch** in the data used.