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tests/test_tutorial/test_extra_data_types/test_tutorial001.py
Python - Registered: Sun Apr 28 07:19:10 GMT 2024 - Last Modified: Fri Apr 19 00:11:40 GMT 2024 - 6.8K bytes - Viewed (0) -
docs/en/docs/reference/background.md
# Background Tasks - `BackgroundTasks` You can declare a parameter in a *path operation function* or dependency function with the type `BackgroundTasks`, and then you can use it to schedule the execution of background tasks after the response is sent. You can import it directly from `fastapi`: ```python from fastapi import BackgroundTasks ```
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docs/en/docs/benchmarks.md
* If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers. * **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.
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docs/en/docs/advanced/generate-clients.md
}, "author": "", "license": "", "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
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docs/en/docs/alternatives.md
### Flask REST frameworks There are several Flask REST frameworks, but after investing the time and work into investigating them, I found that many are discontinued or abandoned, with several standing issues that made them unfit.
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docs/en/docs/tutorial/testing.md
## Run it After that, you just need to install `pytest`: <div class="termy"> ```console $ pip install pytest ---> 100% ``` </div>
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fastapi/param_functions.py
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.github/actions/people/app/main.py
if response.status_code != 200: logging.error( f"Response was not 200, after: {after}, category_id: {category_id}" ) logging.error(response.text) raise RuntimeError(response.text) data = response.json() if "errors" in data: logging.error(f"Errors in response, after: {after}, category_id: {category_id}") logging.error(data["errors"])
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docs_src/extra_data_types/tutorial001.py
end_datetime: datetime = Body(), process_after: timedelta = Body(), repeat_at: Union[time, None] = Body(default=None), ): start_process = start_datetime + process_after duration = end_datetime - start_process return { "item_id": item_id, "start_datetime": start_datetime, "end_datetime": end_datetime, "process_after": process_after, "repeat_at": repeat_at,
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docs/de/docs/deployment/cloud.md
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