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Python High Performance. Build high-performing, concurrent, and distributed applications - Second Edition Dr. Gabriele Lanaro

(ebook) (audiobook) (audiobook) Książka w języku angielskim
Python High Performance. Build high-performing, concurrent, and distributed applications - Second Edition Dr. Gabriele Lanaro - okladka książki

Python High Performance. Build high-performing, concurrent, and distributed applications - Second Edition Dr. Gabriele Lanaro - okladka książki

Python High Performance. Build high-performing, concurrent, and distributed applications - Second Edition Dr. Gabriele Lanaro - audiobook MP3

Python High Performance. Build high-performing, concurrent, and distributed applications - Second Edition Dr. Gabriele Lanaro - audiobook CD

Autor:
Dr. Gabriele Lanaro
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
270
Dostępne formaty:
     PDF
     ePub
     Mobi
Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language.

Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications.

The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark.

By the end of the book, readers will have learned to achieve performance and scale from their Python applications.

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O autorze książki

Dr. Gabriele Lanaro is passionate about good software and is the author of the chemlab and chemview open source packages. His interests span machine learning, numerical computing visualization, and web technologies. In 2013, he authored the first edition of the book High Performance Python Programming. He has been conducting research to study the formation and growth of crystals using medium and large-scale computer simulations. In 2017, he obtained his PhD in theoretical chemistry.

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