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fastapi/security/oauth2.py
Python - Registered: Sun May 05 07:19:11 GMT 2024 - Last Modified: Tue Apr 02 02:48:51 GMT 2024 - 21.1K bytes - Viewed (1) -
fastapi/param_functions.py
'Whitelist' validation step. The parameter field will be the single one allowed by the alias or set of aliases defined. """ ), ] = None, serialization_alias: Annotated[ Union[str, None], Doc( """ 'Blacklist' validation step. The vanilla parameter field will be the single one of the alias' or set of aliases' fields and all the other
Python - Registered: Sun May 05 07:19:11 GMT 2024 - Last Modified: Thu Apr 18 19:40:57 GMT 2024 - 62.5K bytes - Viewed (0) -
docs/en/docs/deployment/concepts.md
But in most cases, you will want to perform these steps only **once**. So, you will want to have a **single process** to perform those **previous steps**, before starting the application.
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docs/en/docs/deployment/manually.md
## Use the `fastapi run` Command In short, use `fastapi run` to serve your FastAPI application: <div class="termy"> ```console $ <font color="#4E9A06">fastapi</font> run <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/tutorial/bigger-applications.md
# Bigger Applications - Multiple Files If you are building an application or a web API, it's rarely the case that you can put everything on a single file. **FastAPI** provides a convenience tool to structure your application while keeping all the flexibility. !!! info If you come from Flask, this would be the equivalent of Flask's Blueprints. ## An example file structure Let's say you have a file structure like this: ``` . ├── app
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docs/en/docs/tutorial/first-steps.md
{!../../../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/behind-a-proxy.md
<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. Then create a file `traefik.toml` with: ```TOML hl_lines="3" [entryPoints] [entryPoints.http] address = ":9999"
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docs/en/docs/how-to/async-sql-encode-databases.md
It is compatible with: * PostgreSQL * MySQL * SQLite In this example, we'll use **SQLite**, because it uses a single file and Python has integrated support. So, you can copy this example and run it as is. Later, for your production application, you might want to use a database server like **PostgreSQL**. !!! tip
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docs/en/docs/tutorial/response-model.md
=== "Python 3.8+" ```Python hl_lines="10" {!> ../../../docs_src/response_model/tutorial003_04.py!} ``` ...this fails because the type annotation is not a Pydantic type and is not just a single `Response` class or subclass, it's a union (any of the two) between a `Response` and a `dict`. ### Disable Response Model
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docs/en/docs/alternatives.md
They are, more or less, at opposite ends, complementing each other. Requests has a very simple and intuitive design, it's very easy to use, with sensible defaults. But at the same time, it's very powerful and customizable. That's why, as said in the official website: > Requests is one of the most downloaded Python packages of all time The way you use it is very simple. For example, to do a `GET` request, you would write: ```Python
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