@Test fun validateCompactTableInvariants() {
    // Less than 16,834 bytes, because we binary search on a 14-bit index.
    assertThat(compactTable.sections.length).isLessThan(1 shl 14)

    // Less than 65,536 bytes, because we binary search on a 14-bit index with a stride of 4 bytes.
    assertThat(compactTable.ranges.length).isLessThan((1 shl 14) * 4)

    return when {
      offset >= 0 -> offset * 4 // This section was found by binary search.
      else -> (-offset - 2) * 4 // Not found? Use the preceding element.
    }
  }

  /**
   * Binary search [ranges] for [codePoint], looking at its bottom 7 bits.
   *
   * This binary searches over 4-byte entries, and so it needs to adjust binary search indices
   * in (by dividing by 4) and out (by multiplying by 4).
   */

 */

package org.jetbrains.kotlin.analysis.api.descriptors.components

import com.intellij.openapi.project.Project
import com.intellij.psi.search.GlobalSearchScope
import com.intellij.psi.search.ProjectScope
import org.jetbrains.kotlin.analysis.api.components.KtSymbolContainingDeclarationProvider
import org.jetbrains.kotlin.analysis.api.descriptors.KtFe10AnalysisSession

[![GitHub license](https://img.shields.io/badge/license-Apache%20License%202.0-blue.svg?style=flat)](https://www.apache.org/licenses/LICENSE-2.0)
[![Revved up by Develocity](https://img.shields.io/badge/Revved%20up%20by-Develocity-06A0CE?logo=Gradle&labelColor=02303A)](https://ge.jetbrains.com/scans?search.rootProjectNames=Kotlin)

### Modelle für maschinelles Lernen mit spaCy und FastAPI – Funktionen

* **spaCy** NER-Modellintegration.
* **Azure Cognitive Search**-Anforderungsformat integriert.
* **Produktionsbereit** Python-Webserver, verwendet Uvicorn und Gunicorn.
* **Azure DevOps** Kubernetes (AKS) CI/CD-Deployment integriert.

* However, when a Markdown document is translated, the `#hash-parts` in links to its headings may change. Update these links if possible.
    * Search for such links in the translated document using the regex `#[^# ]`.
    * Search in all documents already translated into your language for `your-translated-document.md`. For example VS Code has an option "Edit" -> "Find in Files".

## Futur

À ce stade, il est déjà clair que **FastAPI** et ses idées sont utiles pour de nombreuses personnes.

Elle a été préférée aux solutions précédentes parce qu'elle convient mieux à de nombreux cas d'utilisation.

De nombreux développeurs et équipes dépendent déjà de **FastAPI** pour leurs projets (y compris moi et mon équipe).

```Python
{!> ../../../docs_src/app_testing/app_b/test_main.py!}
```

Whenever you need the client to pass information in the request and you don't know how to, you can search (Google) how to do it in `httpx`, or even how to do it with `requests`, as HTTPX's design is based on Requests' design.

Then you just do the same in your tests.

E.g.:

It is used by many companies including Mozilla, Red Hat and Eventbrite.

It was one of the first examples of **automatic API documentation**, and this was specifically one of the first ideas that inspired "the search for" **FastAPI**.

!!! note
    Django REST Framework was created by Tom Christie. The same creator of Starlette and Uvicorn, on which **FastAPI** is based.


!!! check "Inspired **FastAPI** to"

There are also several other companies offering similar services that you can search and find online. 🤓

## Generate a TypeScript Frontend Client

Let's start with a simple FastAPI application:

=== "Python 3.9+"

    ```Python hl_lines="7-9  12-13  16-17  21"