The Python Language Reference Manual

The Python Language Reference Manual PDF Author: Guido Van Rossum
Publisher: Network Theory.
ISBN: 9781906966140
Category : Computers
Languages : en
Pages : 150

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Book Description
This is a printed edition of the official Python language reference manual from the Python 3.2 distribution. It describes the syntax of Python 3 and its built-in datatypes and operators. Python is an interpreted object-oriented programming language, suitable for rapid application development and scripting. This manual is intended for advanced users who need a complete description of the Python 3 language syntax and object system. A simpler tutorial suitable for new users of Python is available in the companion volume "An Introduction to Python (for Python version 3.2)" (ISBN 978-1-906966-13-3). For each copy of this manual sold USD 1 is donated to the Python Software Foundation by the publisher, Network Theory Ltd.

The Python Library Reference

The Python Library Reference PDF Author: Guido van Rossum
Publisher:
ISBN: 9781680921588
Category : Computers
Languages : en
Pages : 1102

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Book Description
This book is the first half of The Python Library Reference for Release 3.6.4, and covers chapters 1-18. The second book may be found with ISBN 9781680921090. The original Python Library Reference book is 1920 pages long. This book contains the original page numbers and index, along with the back sections fully intact. While reference-index describes the exact syntax and semantics of the Python language, this library reference manual describes the standard library that is distributed with Python. It also describes some of the optional components that are commonly included in Python distributions. Python's standard library is very extensive, offering a wide range of facilities as indicated by the long table of contents listed below. The library contains built-in modules (written in C) that provide access to system functionality such as file I/O that would otherwise be inaccessible to Python programmers, as well as modules written in Python that provide standardized solutions for many problems that occur in everyday programming. Some of these modules are explicitly designed to encourage and enhance the portability of Python programs by abstracting away platform-specifics into platform-neutral APIs. This book is available for free as a PDF at python.org.

Python Essential Reference

Python Essential Reference PDF Author: David M Beazley
Publisher: Addison-Wesley Professional
ISBN: 0768687020
Category : Computers
Languages : en
Pages : 745

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Book Description
Python Essential Reference is the definitive reference guide to the Python programming language — the one authoritative handbook that reliably untangles and explains both the core Python language and the most essential parts of the Python library. Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source. Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms. This fourth edition of Python Essential Reference features numerous improvements, additions, and updates: Coverage of new language features, libraries, and modules Practical coverage of Python's more advanced features including generators, coroutines, closures, metaclasses, and decorators Expanded coverage of library modules related to concurrent programming including threads, subprocesses, and the new multiprocessing module Up-to-the-minute coverage of how to use Python 2.6’s forward compatibility mode to evaluate code for Python 3 compatibility Improved organization for even faster answers and better usability Updates to reflect modern Python programming style and idioms Updated and improved example code Deep coverage of low-level system and networking library modules — including options not covered in the standard documentation

Python Standard Library

Python Standard Library PDF Author: Fredrik Lundh
Publisher: "O'Reilly Media, Inc."
ISBN: 9780596000967
Category : Computers
Languages : en
Pages : 312

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Book Description
CD-ROM contains: programming examples from the book and a demo of the PythonWorks IDE.

The Python Quick Syntax Reference

The Python Quick Syntax Reference PDF Author: Gregory Walters
Publisher: Apress
ISBN: 1430264799
Category : Computers
Languages : en
Pages : 140

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Book Description
The Python Quick Syntax Reference is the "go to" book that contains an easy to read and use guide to Python programming and development. This condensed code and syntax reference presents the Python language in a well-organized format designed to be used time and again. You won't find jargon, bloated samples, case studies, or history of Hello World and computer theory in this handy reference. This Python syntax reference is packed with useful information and is a must-have for any Python developer.

PYTHON 36 LANGUAGE REF

PYTHON 36 LANGUAGE REF PDF Author: Guido Van Rossum
Publisher: Samurai Media Limited
ISBN: 9789888406883
Category : Computers
Languages : en
Pages : 160

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Book Description
This reference manual describes the syntax and "core semantics" of the language. It is terse, but attempts to be exact and complete. This book is a paper version of the freely available electronic documentation of the python project.

The Hitchhiker's Guide to Python

The Hitchhiker's Guide to Python PDF Author: Kenneth Reitz
Publisher: "O'Reilly Media, Inc."
ISBN: 1491933224
Category : Computers
Languages : en
Pages : 331

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Book Description
The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversityâ??and possibly dilution. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhikerâ??s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

Natural Language Processing with Python

Natural Language Processing with Python PDF Author: Steven Bird
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555717
Category : Computers
Languages : en
Pages : 506

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Book Description
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

The Python Language Reference

The Python Language Reference PDF Author: Guido van Rossum
Publisher:
ISBN: 9781680921618
Category : Computers
Languages : en
Pages : 168

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Book Description
The Python Language Reference Release 3.6.4 describes the syntax and "core semantics" of the language. It is terse, but attempts to be exact and complete. The semantics of non-essential built-in object types and of the built-in functions and modules are described in library-index. For an informal introduction to the language, see tutorial-index. For C or C++ programmers, two additional manuals exist: extending-index describes the high-level picture of how to write a Python extension module, and the c-api-index describes the interfaces available to C/C++ programmers in detail. This book is available for free as a PDF at python.org.

Python Data Science Handbook

Python Data Science Handbook PDF Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609

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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms