"kamēr", "# Particles", "ar", "diezin", "droši", "diemžēl", "nebūt", "ik", "it", "taču", "nu", "pat", "tiklab", "iekšpus", "nedz", "tik", "nevis", "turpretim", "jeb", "iekam", "iekām", "iekāms", "kolīdz", "līdzko", "tiklīdz", "jebšu", "tālab", "tāpēc", "nekā", "itin", "jā", "jau", "jel", "nē", "nezin", "tad", "tikai", "vis", "tak", "iekams", "vien", "# modal verbs", "būt  ", "biju ", "biji", "bija", "bijām", "bijāt", "esmu", "esi", "esam", "esat ", "būšu     ", "būsi", "būs", "būsim", "būsiet", "tikt",...

## 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.

This means that you can send only the data that you want to update, leaving the rest intact.

/// note

`PATCH` is less commonly used and known than `PUT`.

And many teams use only `PUT`, even for partial updates.

You are **free** to use them however you want, **FastAPI** doesn't impose any restrictions.

But this guide shows you, more or less, how they are intended to be used.

///

## Meinungen

„_[...] Ich verwende **FastAPI** heutzutage sehr oft. [...] Ich habe tatsächlich vor, es für alle **ML-Dienste meines Teams bei Microsoft** zu verwenden. Einige davon werden in das Kernprodukt **Windows** und einige **Office**-Produkte integriert._“

Using it led to the creation of several Flask full-stack generators. These are the main stacks I (and several external teams) have been using up to now:

* <a href="https://github.com/tiangolo/full-stack" class="external-link" target="_blank">https://github.com/tiangolo/full-stack</a>

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