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docs/en/docs/contributing.md
### Using your local FastAPI If you create a Python file that imports and uses FastAPI, and run it with the Python from your local environment, it will use your cloned local FastAPI source code. And if you update that local FastAPI source code when you run that Python file again, it will use the fresh version of FastAPI you just edited.
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docs/en/docs/advanced/behind-a-proxy.md
## Testing locally with Traefik You can easily run the experiment locally with a stripped path prefix using <a href="https://docs.traefik.io/" class="external-link" target="_blank">Traefik</a>. <a href="https://github.com/containous/traefik/releases" class="external-link" target="_blank">Download Traefik</a>, it's a single binary, you can extract the compressed file and run it directly from the terminal.
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docs/en/docs/tutorial/first-steps.md
# First Steps The simplest FastAPI file could look like this: ```Python {!../../../docs_src/first_steps/tutorial001.py!} ``` Copy that to a file `main.py`. Run the live server: <div class="termy"> ```console $ <font color="#4E9A06">fastapi</font> dev <u style="text-decoration-style:single">main.py</u> <font color="#3465A4">INFO </font> Using path <font color="#3465A4">main.py</font>
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docs/en/docs/advanced/generate-clients.md
"devDependencies": { "@hey-api/openapi-ts": "^0.27.38", "typescript": "^4.6.2" } } ``` After having that NPM `generate-client` script there, you can run it with: <div class="termy"> ```console $ npm run generate-client frontend-app@1.0.0 generate-client /home/user/code/frontend-app > openapi-ts --input http://localhost:8000/openapi.json --output ./src/client --client axios ```
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docs/en/docs/deployment/concepts.md
### Separate Program To achieve this, you will normally have a **separate program** that would make sure your application is run on startup. And in many cases, it would also make sure other components or applications are also run, for example, a database. ### Example Tools to Run at Startup Some examples of the tools that can do this job are: * Docker * Kubernetes * Docker Compose * Docker in Swarm Mode
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.github/actions/people/app/main.py
logging.info("Setting up GitHub Actions git user") subprocess.run(["git", "config", "user.name", "github-actions"], check=True) subprocess.run( ["git", "config", "user.email", "******@****.***"], check=True ) branch_name = "fastapi-people" logging.info(f"Creating a new branch {branch_name}") subprocess.run(["git", "checkout", "-b", branch_name], check=True)
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docs/ko/docs/deployment/docker.md
# (2) WORKDIR /tmp # (3) RUN pip install poetry # (4) COPY ./pyproject.toml ./poetry.lock* /tmp/ # (5) RUN poetry export -f requirements.txt --output requirements.txt --without-hashes # (6) FROM python:3.9 # (7) WORKDIR /code # (8) COPY --from=requirements-stage /tmp/requirements.txt /code/requirements.txt # (9)
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docs/em/docs/contributing.md
$ python ./scripts/docs.py serve Warning: this is a very simple server. For development, use mkdocs serve instead. This is here only to preview a site with translations already built. Make sure you run the build-all command first. Serving at: http://127.0.0.1:8008 ``` </div> ## ๐ฏ ๐ค โ ๐ ๐ ๐ช ๐ ๐ ๐ฏ ๐ ๐ & ๐ ๐ฐ ๐ ๐ธ: <div class="termy"> ```console
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docs/en/docs/alternatives.md
It is the recommended server for Starlette and **FastAPI**. !!! check "**FastAPI** recommends it as" The main web server to run **FastAPI** applications. You can combine it with Gunicorn, to have an asynchronous multi-process server. Check more details in the [Deployment](deployment/index.md){.internal-link target=_blank} section.
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docs/pt/docs/deployment.md
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