Cython

Author: Kurt W. Smith
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491901762
Release Date: 2015-01-21
Genre: Computers

Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP

Cython

Author: Kurt W. Smith
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491901755
Release Date: 2015-01-21
Genre: Computers

Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP

Cython

Author: Kurt W. Smith
Publisher: Oreilly & Associates Incorporated
ISBN: 1491901551
Release Date: 2015-01-31
Genre: Computers

Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease. Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal. Use Cython’s static typing to speed up Python code Gain hands-on experience using Cython features to boost your numeric-heavy Python Create new types with Cython—and see how fast object-oriented programming in Python can be Effectively organize Cython code into separate modules and packages without sacrificing performance Use Cython to give Pythonic interfaces to C and C++ libraries Optimize code with Cython’s runtime and compile-time profiling tools Use Cython’s prange function to parallelize loops transparently with OpenMP

Learning Cython Programming

Author: Philip Herron
Publisher: Packt Publishing Ltd
ISBN: 9781783280803
Release Date: 2013-09-25
Genre: Computers

A practical and a fast-paced guide that gives you all the information you need to start programming using Cython.This book is for developers who love C/C++ for low latency and speed but who also require the ability to add more dynamic features to applications both fast and reliably. It will also show you how you can get new applications off the ground by reusing Python libraries to get started.

High Performance Python

Author: Micha Gorelick
Publisher: "O'Reilly Media, Inc."
ISBN: 9781449361761
Release Date: 2014-08-22
Genre: Computers

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

Python High Performance Programming

Author: Gabriele Lanaro
Publisher: Packt Publishing Ltd
ISBN: 9781783288465
Release Date: 2013-12-23
Genre: Computers

An exciting, easy-to-follow guide illustrating the techniques to boost the performance of Python code, and their applications with plenty of hands-on examples. If you are a programmer who likes the power and simplicity of Python and would like to use this language for performance-critical applications, this book is ideal for you. All that is required is a basic knowledge of the Python programming language. The book will cover basic and advanced topics so will be great for you whether you are a new or a seasoned Python developer.

Python High Performance Second Edition

Author: Gabriele Lanaro
Publisher:
ISBN: 1787282899
Release Date: 2017-05-24
Genre: Computers

Learn how to use Python to create efficient applicationsAbout This Book* Identify the bottlenecks in your applications and solve them using the best profiling techniques* Write efficient numerical code in NumPy, Cython, and Pandas* Adapt your programs to run on multiple processors and machines with parallel programmingWho This Book Is ForThe book is aimed at Python developers who want to improve the performance of their application. Basic knowledge of Python is expectedWhat You Will Learn* Write efficient numerical code with the NumPy and Pandas libraries* Use Cython and Numba to achieve native performance* Find bottlenecks in your Python code using profilers* Write asynchronous code using Asyncio and RxPy* Use Tensorflow and Theano for automatic parallelism in Python* Set up and run distributed algorithms on a cluster using Dask and PySparkIn DetailPython 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.Style and approachA step-by-step practical guide filled with real-world use cases and examples

Python in Practice

Author: Mark Summerfield
Publisher: Pearson Education
ISBN: 9780321905635
Release Date: 2013
Genre: Computers

Winner of the 2014 Jolt Award for "Best Book" "Whether you are an experienced programmer or are starting your career, Python in Practice is full of valuable advice and example to help you improve your craft by thinking about problems from different perspectives, introducing tools, and detailing techniques to create more effective solutions." --Doug Hellmann, Senior Developer, DreamHost If you're an experienced Python programmer, Python in Practice will help you improve the quality, reliability, speed, maintainability, and usability of all your Python programs. Mark Summerfield focuses on four key themes: design patterns for coding elegance, faster processing through concurrency and compiled Python (Cython), high-level networking, and graphics. He identifies well-proven design patterns that are useful in Python, illuminates them with expert-quality code, and explains why some object-oriented design patterns are irrelevant to Python. He also explodes several counterproductive myths about Python programming--showing, for example, how Python can take full advantage of multicore hardware. All examples, including three complete case studies, have been tested with Python 3.3 (and, where possible, Python 3.2 and 3.1) and crafted to maintain compatibility with future Python 3.x versions. All code has been tested on Linux, and most code has also been tested on OS X and Windows. All code may be downloaded atwww.qtrac.eu/pipbook.html. Coverage includes Leveraging Python's most effective creational, structural, and behavioral design patterns Supporting concurrency with Python's multiprocessing, threading, and concurrent.futures modules Avoiding concurrency problems using thread-safe queues and futures rather than fragile locks Simplifying networking with high-level modules, including xmlrpclib and RPyC Accelerating Python code with Cython, C-based Python modules, profiling, and other techniques Creating modern-looking GUI applications with Tkinter Leveraging today's powerful graphics hardware via the OpenGL API using pyglet and PyOpenGL

Expert Python Programming

Author: Tarek Ziade
Publisher: Packt Publishing Ltd
ISBN: 9781847194954
Release Date: 2008-09-19
Genre: Computers

Best practices for designing, coding, and distributing your Python software.

NumPy Essentials

Author: Leo (Liang-Huan) Chin
Publisher: Packt Publishing Ltd
ISBN: 9781784392185
Release Date: 2016-04-28
Genre: Computers

Boost your scientific and analytic capabilities in no time at all by discovering how to build real-world applications with NumPy About This Book Optimize your Python scripts with powerful NumPy modules Explore the vast opportunities to build outstanding scientific/ analytical modules by yourself Packed with rich examples to help you master NumPy arrays and universal functions Who This Book Is For If you are an experienced Python developer who intends to drive your numerical and scientific applications with NumPy, this book is for you. Prior experience or knowledge of working with the Python language is required. What You Will Learn Manipulate the key attributes and universal functions of NumPy Utilize matrix and mathematical computation using linear algebra modules Implement regression and curve fitting for models Perform time frequency / spectral density analysis using the Fourier Transform modules Collate with the distutils and setuptools modules used by other Python libraries Establish Cython with NumPy arrays Write extension modules for NumPy code using the C API Build sophisticated data structures using NumPy array with libraries such as Panda and Scikits In Detail In today's world of science and technology, it's all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features. Style and approach This quick guide will help you get to grips with the nitty-gritties of NumPy using with practical programming examples. Each topic is explained in both theoretical and practical ways with hands-on examples providing you efficient way of learning and adequate knowledge to support your professional work.

Fluent Python

Author: Luciano Ramalho
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491946251
Release Date: 2015-07-30
Genre: Computers

Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3. This book covers: Python data model: understand how special methods are the key to the consistent behavior of objects Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work

Expert Python Programming Second Edition

Author: Michal Jaworski
Publisher: Packt Publishing
ISBN: 1785886851
Release Date: 2016-05-20
Genre: Computers

Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5About This Book- Based on the latest stable version of Python (version 3.5)- Creating well manageable code that will run in various environments with different sets of dependencies- Packed with advanced concepts and best practices to write efficient Python codeWho This Book Is ForThe book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected.What You Will Learn- Conventions and best practices that are widely adopted in the python community- Package python code effectively for community and production use- Easy and lightweight ways to automate code deployment on remote systems- Improve your code's quality, reliability, and performance- Write concurrent code in python- Extend python with code written in different languagesIn DetailPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered.You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization.By the end of the book, you will be an expert in writing efficient and maintainable code.Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming

Python Cookbook

Author: Alex Martelli
Publisher: "O'Reilly Media, Inc."
ISBN: 0596554745
Release Date: 2005-03-18
Genre: Computers

Portable, powerful, and a breeze to use, Python is the popular open source object-oriented programming language used for both standalone programs and scripting applications. It is now being used by an increasing number of major organizations, including NASA and Google.Updated for Python 2.4, The Python Cookbook, 2nd Edition offers a wealth of useful code for all Python programmers, not just advanced practitioners. Like its predecessor, the new edition provides solutions to problems that Python programmers face everyday.It now includes over 200 recipes that range from simple tasks, such as working with dictionaries and list comprehensions, to complex tasks, such as monitoring a network and building a templating system. This revised version also includes new chapters on topics such as time, money, and metaprogramming.Here's a list of additional topics covered: Manipulating text Searching and sorting Working with files and the filesystem Object-oriented programming Dealing with threads and processes System administration Interacting with databases Creating user interfaces Network and web programming Processing XML Distributed programming Debugging and testing Another advantage of The Python Cookbook, 2nd Edition is its trio of authors--three well-known Python programming experts, who are highly visible on email lists and in newsgroups, and speak often at Python conferences.With scores of practical examples and pertinent background information, The Python Cookbook, 2nd Edition is the one source you need if you're looking to build efficient, flexible, scalable, and well-integrated systems.

Python and HDF5

Author: Andrew Collette
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491945018
Release Date: 2013-10-21
Genre: Computers

Gain hands-on experience with HDF5 for storing scientific data in Python. This practical guide quickly gets you up to speed on the details, best practices, and pitfalls of using HDF5 to archive and share numerical datasets ranging in size from gigabytes to terabytes. Through real-world examples and practical exercises, you’ll explore topics such as scientific datasets, hierarchically organized groups, user-defined metadata, and interoperable files. Examples are applicable for users of both Python 2 and Python 3. If you’re familiar with the basics of Python data analysis, this is an ideal introduction to HDF5. Get set up with HDF5 tools and create your first HDF5 file Work with datasets by learning the HDF5 Dataset object Understand advanced features like dataset chunking and compression Learn how to work with HDF5’s hierarchical structure, using groups Create self-describing files by adding metadata with HDF5 attributes Take advantage of HDF5’s type system to create interoperable files Express relationships among data with references, named types, and dimension scales Discover how Python mechanisms for writing parallel code interact with HDF5

Numerical Methods in Engineering with Python 3

Author: Jaan Kiusalaas
Publisher: Cambridge University Press
ISBN: 9781107033856
Release Date: 2013-01-21
Genre: Computers

Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language.