path: ${{ env.pythonLocation }}
          key: ${{ runner.os }}-python-${{ env.pythonLocation }}-${{ hashFiles('pyproject.toml') }}-publish
      - name: Install build dependencies
        run: pip install build
      - name: Build distribution
        run: python -m build
      - name: Publish
        uses: pypa/gh-action-pypi-publish@v1.8.14
        with:
          password: ${{ secrets.PYPI_API_TOKEN }}

.idea
.ipynb_checkpoints
.mypy_cache
.vscode
__pycache__
.pytest_cache
htmlcov
dist
site
.coverage
coverage.xml
.netlify
test.db
log.txt
Pipfile.lock
env3.*
env
docs_build
site_build
venv
docs.zip
archive.zip

# vim temporary files
*~
.*.sw?
.cache

# macOS

Once you are done, you can also test it all as it would look online, including all the other languages.

To do that, first build all the docs:

<div class="termy">

```console
// Use the command "build-all", this will take a bit
$ python ./scripts/docs.py build-all

Building docs for: en
Building docs for: es
Successfully built docs for: es
```

</div>

    branches:
      - master
    types:
      - closed
  workflow_dispatch:
    inputs:
      number:
        description: PR number
        required: true
      debug_enabled:
        description: 'Run the build with tmate debugging enabled (https://github.com/marketplace/actions/debugging-with-tmate)'
        required: false
        default: 'false'

jobs:
  latest-changes:
    runs-on: ubuntu-latest
    steps:

👈, 🥇 🏗 🌐 🩺:

<div class="termy">

```console
// Use the command "build-all", this will take a bit
$ python ./scripts/docs.py build-all

Updating es
Updating en
Building docs for: en
Building docs for: es
Successfully built docs for: es
Copying en index.md to README.md
```

</div>

👈 🏗 🌐 🩺 `./docs_build/` 🔠 🇪🇸. 👉 🔌 ❎ 🙆 📁 ⏮️ ❌ ✍, ⏮️ 🗒 💬 👈 "👉 📁 🚫 ✔️ ✍". ✋️ 👆 🚫 ✔️ 🕳 ⏮️ 👈 📁.

* **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.

* Allez dans le répertoire du projet (dans lequel se trouve votre `Dockerfile`, contenant votre répertoire `app`).
* Construisez votre image FastAPI :

<div class="termy">

```console
$ docker build -t myimage .

---> 100%
```

</div>

## Démarrer le conteneur Docker

* Exécutez un conteneur basé sur votre image :

<div class="termy">

```console

</p>
<p align="center">
<a href="https://travis-ci.com/tiangolo/fastapi" target="_blank">
    <img src="https://travis-ci.com/tiangolo/fastapi.svg?branch=master" alt="Build Status">
</a>
<a href="https://codecov.io/gh/tiangolo/fastapi" target="_blank">
    <img src="https://img.shields.io/codecov/c/github/tiangolo/fastapi" alt="Coverage">
</a>

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.