ent:"\f394"}.fa-docker:before{content:"\f395"}.fa-dog:before{content:"\f6d3"}.fa-dollar-sign:before{content:"\f155"}.fa-dolly:before{content:"\f472"}.fa-dolly-flatbed:before{content:"\f474"}.fa-donate:before{content:"\f4b9"}.fa-door-closed:before{content:"\f52a"}.fa-door-open:before{content:"\f52b"}.fa-dot-circle:before{content:"\f192"}.fa-dove:before{content:"\f4ba"}.fa-download:before{content:"\f019"}.fa-draft2digital:before{content:"\f396"}.fa-drafting-compass:before{content:"\f568"}.fa-drago...

    // The Dolphin algorithm is attractive because it does the fewest array reads and writes: each
    // array slot is read and written exactly once. However, it can have very poor memory locality:
    // benchmarking shows it can take 7 times longer than the other two in some cases. The other two
    // do n swaps, minus a delta (0 or 2 for Reversal, gcd(d, n) for Successive), so that's about

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## Meinungen { #opinions }

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

///

### Einen `APIRouter` mit benutzerdefinierten `prefix`, `tags`, `responses` und `dependencies` einfügen { #include-an-apirouter-with-a-custom-prefix-tags-responses-and-dependencies }

Stellen wir uns nun vor, dass Ihre Organisation Ihnen die Datei `app/internal/admin.py` gegeben hat.

Sie enthält einen `APIRouter` mit einigen administrativen *Pfadoperationen*, die Ihre Organisation zwischen mehreren Projekten teilt.

    // and reduces the false-positive probability.
    static final int MAX_RUN_MULTIPLIER = 13;

    /**
     * Checks the whole hash table for poor hash distribution. Takes O(n) in the worst case, O(n /
     * log n) on average.
     *
     * <p>The online hash flooding detecting in RegularSetBuilderImpl.add can detect e.g. many

   * WeakReference} (by default, strong references are used).
   *
   * <p>Weak values will be garbage collected once they are weakly reachable. This makes them a poor
   * candidate for caching; consider {@link #softValues} instead.
   *
   * <p><b>Note:</b> when this method is used, the resulting cache will use identity ({@code ==})
   * comparison to determine equality of values.

Kurz bevor ich mich entschied, **FastAPI** zu erstellen, fand ich den **APIStar**-Server. Er hatte fast alles, was ich suchte, und ein tolles Design.

Er war eine der ersten Implementierungen eines Frameworks, die ich je gesehen hatte (vor NestJS und Molten), welches Python-Typhinweise zur Deklaration von Parametern und Requests verwendeten. Ich habe ihn mehr oder weniger zeitgleich mit Hug gefunden. Aber APIStar nutzte den OpenAPI-Standard.

   * WeakReference} (by default, strong references are used).
   *
   * <p>Weak values will be garbage collected once they are weakly reachable. This makes them a poor
   * candidate for caching; consider {@link #softValues} instead.
   *
   * <p><b>Note:</b> when this method is used, the resulting cache will use identity ({@code ==})
   * comparison to determine equality of values.

      return new WeakValueReferenceImpl<>(queue, get(), entry);
    }
  }

  /**
   * Applies a supplemental hash function to a given hash code, which defends against poor quality
   * hash functions. This is critical when the concurrent hash map uses power-of-two length hash
   * tables, that otherwise encounter collisions for hash codes that do not differ in lower or upper
   * bits.
   *

      return new WeakValueReferenceImpl<>(queue, get(), entry);
    }
  }

  /**
   * Applies a supplemental hash function to a given hash code, which defends against poor quality
   * hash functions. This is critical when the concurrent hash map uses power-of-two length hash
   * tables, that otherwise encounter collisions for hash codes that do not differ in lower or upper
   * bits.
   *