with:
          python-version: ${{ matrix.python-version }}
          # Issue ref: https://github.com/actions/setup-python/issues/436
          # cache: "pip"
          # cache-dependency-path: pyproject.toml
      - uses: actions/cache@v4
        id: cache
        with:
          path: ${{ env.pythonLocation }}

name: Publish

on:
  release:
    types:
      - created

jobs:
  publish:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        package:
          - fastapi
          - fastapi-slim
    permissions:
      id-token: write
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"
      - uses: actions/checkout@v4

on:
  push:
    branches:
      - master
  pull_request:
    types:
      - opened
      - synchronize

jobs:
  test-redistribute:
    runs-on: ubuntu-latest
    strategy:
      matrix:
        package:
          - fastapi
          - fastapi-slim
    steps:
      - name: Dump GitHub context
        env:
          GITHUB_CONTEXT: ${{ toJson(github) }}
        run: echo "$GITHUB_CONTEXT"

        run: python ./scripts/docs.py update-languages
      - uses: actions/cache@v4
        with:
          key: mkdocs-cards-${{ matrix.lang }}-${{ github.ref }}
          path: docs/${{ matrix.lang }}/.cache
      - name: Build Docs
        run: python ./scripts/docs.py build-lang ${{ matrix.lang }}
      - uses: actions/upload-artifact@v3
        with:
          name: docs-site
          path: ./site/**

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

* **Maschinelles Lernen**: Normalerweise sind viele „Matrix“- und „Vektor“-Multiplikationen erforderlich. Stellen Sie sich eine riesige Tabelle mit Zahlen vor, in der Sie alle Zahlen gleichzeitig multiplizieren.

* Fix empty log message in docs example about handling errors. PR [#1815](https://github.com/tiangolo/fastapi/pull/1815) by [@manlix](https://github.com/manlix).
* Reword text to reduce ambiguity while not being gender-specific. PR [#1824](https://github.com/tiangolo/fastapi/pull/1824) by [@Mause](https://github.com/Mause).

### Internal

# Copyright (c) 2016-2023 Martin Donath <martin******@****.***>

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
# sell copies of the Software, and to permit persons to whom the Software is

* **Bilgisayar görüsü**: bir görüntü milyonlarca pikselden oluşur, her pikselin 3 değeri / rengi vardır, bu pikseller üzerinde aynı anda bir şeyler hesaplamayı gerektiren işleme.
* **Makine Öğrenimi**: Çok sayıda "matris" ve "vektör" çarpımı gerektirir. Sayıları olan ve hepsini aynı anda çarpan büyük bir elektronik tablo düşünün.