May 2025
Intermediate to advanced
524 pages
16h 25m
German
Content preview from High Performance Python, 3. Auflage
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Kapitel 12. Weniger RAM verwenden
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Wir denken selten darüber nach, wie viel Arbeitsspeicher wir verbrauchen, bis er uns ausgeht. Wenn dir der Speicherplatz ausgeht, während du deinen Code skalierst, kann das zu einem plötzlichen Hindernis werden. Mehr Arbeitsspeicher bedeutet, dass weniger Rechner verwaltet werden müssen, und gibt dir die Möglichkeit, Kapazitäten für größere Projekte zu planen. Wenn du weißt, warum der Arbeitsspeicher verbraucht wird, und dir überlegst, wie du diese knappe Ressource effizienter nutzen kannst, kannst du mit Skalierungsproblemen umgehen. Wir werden den Memory Profiler und die IPython Memory Usage Tools verwenden, um die tatsächliche RAM-Nutzung zu messen, sowie einige Tools, die Objekte untersuchen, um herauszufinden, wie viel RAM sie verwenden.
Eine andere Möglichkeit, Arbeitsspeicher zu sparen, ist die Verwendung von Containern, die Merkmale in deinen Daten zur Komprimierung nutzen. In diesem Kapitel sehen wir uns eine Trie (geordnete Datenstruktur) an, mit der eine ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.