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  • 1
    Online Resource
    Online Resource
    High Performance Python, 2nd Edition (2020)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (87 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Your Python code may run correctly, but you need it to run faster. By exploring the fundamental theory behind design choices, the updated edition of this practical guide, expanded and enhanced for Python 3, helps you gain a deeper understanding of Python’s implementation. You’ll learn how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. How can you take advantage of multicore architectures or clusters? Or build a system that can scale up and down without losing reliability? Experienced Python programmers and students alike will learn concrete solutions to these and other issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and other situations. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Understand performant pandas Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix, vector, and even tensor computations Use tools to compile Python down to machine code, on CPUs and GPUs Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on a local or remote cluster Deploy code faster using tools like Docker Solve large problems while using less RAM Get real-life stories and lessons from Python programmers
    Note: Online resource; Title from title page (viewed June 25, 2020)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    ハイパフォーマンスPython (2015)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Japan, Inc. | Boston, MA : Safari
    Details
    ISBN: 9784873117409
    Language: English , Japanese
    Pages: 1 online resource (360 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Pythonの高速化技法について一歩踏み込んだプロユースの解説書。ボトルネックの測定方法から、最適なデータ構造の使い分け、CythonやPyPyなどのコンパイラの比較、numpyなどのパッケージの使い方、マルチコアCPUの活用法、メモリ効率を劇的に改善するトライ構造や近似計算まで、シンプルな実例プログラムを用いながらわかりやすく説明します。高性能なプログラムの書き方だけでなく、高性能なシステムの作り方を総合的に学ぶことができるPythonエキスパート必携の一冊です。
    Note: Online resource; Title from title page (viewed November 19, 2015) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    High performance Python (2014)
    Sebastopol, CA : O'Reilly
    Details
    Language: English
    Pages: 1 online resource (1 v.) , ill. cm.
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Your Python code may run correctly, but you need it to run faster. By exploring the fundamental theory behind design choices, this practical guide helps you gain a deeper understanding of Python's implementation. You'll learn how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. How can you take advantage of multi-core architectures or clusters? Or build a system that can scale up and down without losing reliability? Experienced Python programmers will learn concrete solutions to these and other issues, along with war stories from companies that use high performance Python for social media analytics, productionized machine learning, and other situations. Get a better grasp of numpy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on a local or remote cluster Solve large problems while using less RAM
    Note: "Practical performant programming for humans"--Cover. - Includes bibliographical references and index. - Description based on print version record
    URL: lizenzpflichtig
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    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Python : programuj szybko i wydajnie (2015)
    Gliwice : Helion
    Details
    Language: Polish
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Computer programming ; Electronic books ; Electronic books ; local
    Abstract: ;Python to skryptowy język programowania istniejący na rynku od wielu lat -- jego pierwsza wersja pojawiła się w 1991 roku. Przejrzystość kodu źródłowego była jednym z głównych celów Guida van Rossuma, twórcy tego języka. Dziś Python cieszy się dużą popularnością, co z jednej strony świadczy o jego przydatności, a z drugiej gwarantuje użytkownikom szerokie wsparcie społeczności programistów języka. Python jest elastyczny, dopuszcza różne style programowania, a dzięki temu znajduje zastosowanie w wielu miejscach świata IT. Jeżeli chcesz w pełni wykorzystać możliwości Pythona i tworzyć wydajne rozwiązania, to koniecznie zaopatrz się w tę książkę! Dzięki niej dowiesz się, jak wykorzystać profilowanie do lokalizowania "wąskich gardeł", oraz poznasz efektywne techniki wyszukiwania danych na listach, w słownikach i zbiorach. Ponadto zdobędziesz wiedzę na temat obliczeń macierzowych i wektorowych oraz zobaczysz, jak kompilacja do postaci kodu C wpływa na wydajność Twojego rozwiązania. Osobne rozdziały zostały poświęcone współbieżności oraz modułowi multiprocessing. Opanowanie tych zagadnień pozwoli Ci ogromnie przyspieszyć działanie Twojej aplikacji. Na sam koniec nauczysz się tworzyć klastry i kolejki zadań oraz optymalizować zużycie pamięci RAM. Rozdział dwunasty to gratka dla wszystkich -- zawiera najlepsze porady specjalistów z branży! Książka ta jest obowiązkową lekturą dla wszystkich programistów chcących tworzyć wydajne rozwiązania w języku Python.
    Note: Includes index. - Originally published in English as: High performance Python, c2014. - Translated by Piotr Pilch. - Description based on online resource; title from title page (Safari, viewed May 26, 2015)
    URL: lizenzpflichtig
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  • 5
    Online Resource
    Online Resource
    高效能 Python 程式設計 (2015)
    [Erscheinungsort nicht ermittelbar] : GoTop Information, Inc. | Boston, MA : Safari
    Details
    ISBN: 9789863477105
    Language: English , Chinese
    Pages: 1 online resource (384 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: 「儘管在學界與業界都非常普遍，但 Python 經常因為在實際應用上過於緩慢而遭人詬病，這本書透過詳盡的策略介紹，將那些誤解與疑慮通通掃除掉，讓我們能夠利用 Python 建立快速且具高度擴充性的計算機制。」 — Jake VanderPlas, 華盛頓大學 你的 Python 程式碼可能運作無誤，但你需要它執行得更快速。透過探索設計選項背後的基礎理論，這本實用指南幫助你對 Python 實作獲得更深入的瞭解。你將學習如何找出效能瓶頸，並且在高資料量(high-data-volume)的程式中大幅加快你的程式碼運作。 如何善用多核心架構或叢集？或者建立能夠擴充及縮小規模，但又不失可靠性的系統？有經驗的 Python 程式人員將學到這些議題與其他問題的具體解法，並且獲悉各家公司利用高效能 Python 從事社群媒體分析(social media analytics)，機器學習(machine learning)，以及各種議題的英雄史。 ‧更深入理解 numpy，Cython 及效能分析器 ‧熟悉 Python 如何抽象化底層的電腦架構 ‧利用效能分析尋找 CPU 時間與記憶體使用量的瓶頸 ‧透過選擇合適的資料結構撰寫有效率的程式 ‧加速矩陣與向量計算 ‧使用工具將 Python 編譯成機器碼 ‧並行管理多個 I/O 與計算操作 ‧將 multiprocessing 程式碼轉換成執行在本地或遠端的叢集上 ‧使用較少的 RAM 解決大型的問題
    Note: Online resource; Title from title page (viewed August 13, 2015) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Hai pafōmansu Python (2023)
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Details
    Orig.schr. Ausgabe: 第 2版.
    Title: ハイパフォーマンスPython /
    Publisher: オライリー・ジャパン,
    ISBN: 9784873119908 , 4873119901
    Language: Japanese
    Pages: 1 online resource (452 pages)
    Edition: Dai 2-han.
    Uniform Title: High performance Python
    DDC: 005.133
    Keywords: Python (Computer program language)
    Abstract: "A guide to programming with Python, updated for Python 3, explores the fundamental theory behind design choices and offers a better understanding of Python implementation, covering such topics as locating performance bottlenecks, how Python abstracts the underlying computer architecture, and tools to compile Python down to machine code." --
    Note: In Japanese.
    URL: lizenzpflichtig
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    MPI Ethno. Forsch.
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