If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms. Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works. Topics include: Data Structures and Algorithms Strings and Text Numbers, Dates, and Times Iterators and Generators Files and I/O Data Encoding and Processing Functions Classes and Objects Metaprogramming Modules and Packages Network and Web Programming Concurrency Utility Scripting and System Administration Testing, Debugging, and Exceptions C Extensions
Author: Allen B. Downey
Publisher: O'Reilly Germany
Release Date: 2014-08-27
Python ist eine moderne, interpretierte, interaktive und objektorientierte Skriptsprache, vielseitig einsetzbar und sehr beliebt. Mit mathematischen Vorkenntnissen ist Python leicht erlernbar und daher die ideale Sprache für den Einstieg in die Welt des Programmierens. Das Buch führt Sie Schritt für Schritt durch die Sprache, beginnend mit grundlegenden Programmierkonzepten, über Funktionen, Syntax und Semantik, Rekursion und Datenstrukturen bis hin zum objektorientierten Design. Zur aktualisierten Auflage Diese Auflage behandelt Python 3, geht dabei aber auch auf Unterschiede zu Python 2 ein. Außerdem wurde das Buch um die Themen Unicode, List und Dictionary Comprehensions, den Mengen-Typ Set, die String-Format-Methode und print als Funktion ergänzt. Jenseits reiner Theorie Jedes Kapitel enthält passende Übungen und Fallstudien, kurze Verständnistests und kleinere Projekte, an denen Sie die neu erlernten Programmierkonzepte gleich ausprobieren und festigen können. Auf diese Weise können Sie das Gelernte direkt anwenden und die jeweiligen Programmierkonzepte nachvollziehen. Lernen Sie Debugging-Techniken kennen Am Ende jedes Kapitels finden Sie einen Abschnitt zum Thema Debugging, der Techniken zum Aufspüren und Vermeiden von Bugs sowie Warnungen vor entsprechenden Stolpersteinen in Python enthält.
This book is for anyone who builds and administers servers, especially in a web operations context. It requires some experience of Linux systems administration, including familiarity with the command line, file system, and text editing. No programming experience is required.
Useful in many roles, from design and prototyping to testing, deployment, and maintenance, Python is consistently ranked among today’s most popular programming languages. The third edition of this practical book provides a quick reference to the language—including Python 3.5, 2.7, and highlights of 3.6—commonly used areas of its vast standard library, and some of the most useful third-party modules and packages. Ideal for programmers with some Python experience, and those coming to Python from other programming languages, this book covers a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. Discover how Python provides a unique mix of elegance, simplicity, practicality, and sheer power. This edition covers: Python syntax, Object-Oriented Python, standard library modules, and third-party Python packages Python’s support for file and text operations, persistence and databases, concurrent execution, and numeric computations Networking basics, event-driven programming, and client-side network protocol modules Python extension modules, and tools for packaging and distributing extensions, modules, and applications
The book kicks off with the fundamentals of starting to use Python with ArcGIS, followed by recipes on managing map documents and layers, including how to find and fix broken data links in these files. In the second part of the book, you will learn to create custom geoprocessing tools and how to use the Attribute and Location tools to select specific features. The third part of the book covers topics for advanced users including the REST API, and also teaches you how to use Python with ArcGIS Pro. The book finishes with appendices covering how to automate Python scripts, and the five things that should be at the back of every GIS programmer's mind.
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 at www.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
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
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
This book is for intermediate Solr Developers who are willing to learn and implement Pro-level practices, techniques, and solutions. This edition will specifically appeal to developers who wish to quickly get to grips with the changes and new features of Apache Solr 5.