# Alternativen, Inspiration und Vergleiche { #alternatives-inspiration-and-comparisons }

Was hat **FastAPI** inspiriert, wie es sich im Vergleich zu Alternativen verhält und was es von ihnen gelernt hat.

## Einführung { #intro }

**FastAPI** würde ohne die frühere Arbeit anderer nicht existieren.

Es wurden zuvor viele Tools entwickelt, die als Inspiration für seine Entwicklung dienten.

# Альтернативи, натхнення та порівняння { #alternatives-inspiration-and-comparisons }

Що надихнуло **FastAPI**, як він порівнюється з альтернативами та чого він у них навчився.

## Вступ { #intro }

**FastAPI** не існувало б, якби не попередні роботи інших.

Раніше було створено багато інструментів, які надихнули на його створення.

Here's a little bit of that history.

## Alternatives { #alternatives }

I have been creating APIs with complex requirements for several years (Machine Learning, distributed systems, asynchronous jobs, NoSQL databases, etc), leading several teams of developers.

As part of that, I needed to investigate, test and use many alternatives.

The history of **FastAPI** is in great part the history of its predecessors.

        #### Utility: compare with alternatives


        There is always *some* alternative to adding a new feature to Guava, even if it's just
        forking Guava yourself.


        We want to see that new features have some significant advantage over the alternatives.
        These advantages can take

      required: false
  - type: textarea
    id: context
    attributes:
      label: Context
      description: |
        How has this issue affected you? What are you trying to accomplish? What other alternatives have you considered?
        Providing context helps us come up with a solution that is most useful in the real world
    validations:

- **Cross-Language Compatibility:**
Java serialization is inherently Java-centric and does not support cross-language scenarios well.

- **Type Safety:**
Java serialization does not enforce type safety as strictly as some alternatives, potentially leading to runtime errors.

## Decision

We do not use Java serialization.
Instead, we use custom serialization where we explicitly describe how data objects should be serialized and deserialized.

   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

![Swagger UI](https://fastapi.tiangolo.com/img/index/index-01-swagger-ui-simple.png)

### Alternative API docs { #alternative-api-docs }

And now, go to [http://127.0.0.1:8000/redoc](http://127.0.0.1:8000/redoc).

You will see the alternative automatic documentation (provided by [ReDoc](https://github.com/Rebilly/ReDoc)):

![ReDoc](https://fastapi.tiangolo.com/img/index/index-02-redoc-simple.png)

$ python main.py

I solemnly swear 🐺
```

</div>

## Alternatives { #alternatives }

This is a simple guide to get you started and teach you how everything works **underneath**.

There are many **alternatives** to managing virtual environments, package dependencies (requirements), projects.

> 這個專案的歷史是什麼？看起來它在短短幾週內從默默無名變得非常厲害 [...]

以下是其中一小段歷史。

## 替代方案 { #alternatives }

多年來我一直在打造具有複雜需求的 API（機器學習、分散式系統、非同步工作、NoSQL 資料庫等），並帶領多個開發團隊。

在此過程中，我需要調查、測試並使用許多替代方案。

**FastAPI** 的歷史，在很大程度上也是其前身工具的歷史。

如在[替代方案](alternatives.md)一節所述：

<blockquote markdown="1">

若沒有他人的前期成果，就不會有 **FastAPI**。

先前已有許多工具啟發了它的誕生。