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.

Learn Python in a Weekend! This book is an (informal) language reference on the Python programming language. Python is one of the most widely used languages in many different application areas. We go through all essential features of the modern Python programming language, including the match statement (3.10) and exception groups (3.11). Although the book is written as a reference, you can read it more or less from beginning to end and you should be able to get the overall picture of the Python language if you have some prior experience with programming in Python. The book covers * Python program top-level components. * Python package/module import system. * Builtin type hierarchy. Data model. * List, map, tuple literals. * Expressions. Simple and compound statements. * Function, class definitions. * Object oriented programming in Python. * Structural pattern matching. * Coroutines, async/await. Order your copy today and learn Python this weekend!

Here is a description for the book *"Python Mastery: A Complete Guide to Programming Excellence"*: Unlock your full potential as a programmer with *"Python Mastery: A Complete Guide to Programming Excellence"*. This comprehensive book is designed to guide you from the fundamentals of Python programming to advanced concepts and best practices. Through clear explanations and hands-on exercises, you'll gain a solid understanding of core topics such as data types, control structures, functions, and modules. Dive deeper into object-oriented programming, file handling, and libraries like NumPy and Pandas. Explore powerful techniques for debugging, testing, and optimizing your code. Whether you're a beginner or an experienced developer, this guide will help you achieve mastery in Python and elevate your programming skills to new heights.

This book is published open access under a CC BY 4.0 license. This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using pandas, numpy, and plotnine. Code is provided to prepare common open-source and proprietary financial data sources (CRSP, Compustat, Mergent FISD, TRACE) and organize them in a database. We reuse these data in all the subsequent chapters, which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation, portfolio sorts, performance analysis, Fama-French factors) to modeling and machine learning applications (fixed effects estimation, clustering standard errors, difference-in-difference estimators, ridge regression, Lasso, Elastic net, random forests, neural networks) and portfolio optimization techniques. Key Features: Self-contained chapters on the most important applications and methodologies in finance, which can easily be used for the reader’s research or as a reference for courses on empirical finance. Each chapter is reproducible in the sense that the reader can replicate every single figure, table, or number by simply copying and pasting the code we provide. A full-fledged introduction to machine learning with scikit-learn based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods. We show how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat, including detailed explanations of the most relevant data characteristics. Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises.

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.

Treat yourself to a lively, intuitive, and easy-to-follow introduction to computer programming in Python. The book was written specifically for biologists with little or no prior experience of writing code - with the goal of giving them not only a foundation in Python programming, but also the confidence and inspiration to start using Python in their own research. Virtually all of the examples in the book are drawn from across a wide spectrum of life science research, from simple biochemical calculations and sequence analysis, to modeling the dynamic interactions of genes and proteins in cells, or the drift of genes in an evolving population. Best of all, Python for the Life Sciences shows you how to implement all of these projects in Python, one of the most popular programming languages for scientific computing. If you are a life scientist interested in learning Python to jump-start your research, this is the book for you. What You'll Learn Write Python scripts to automate your lab calculations Search for important motifs in genome sequences Use object-oriented programming with Python Study mining interaction network data for patterns Review dynamic modeling of biochemical switches Who This Book Is For Life scientists with little or no programming experience, including undergraduate and graduate students, postdoctoral researchers in academia and industry, medical professionals, and teachers/lecturers. “A comprehensive introduction to using Python for computational biology... A lovely book with humor and perspective” -- John Novembre, Associate Professor of Human Genetics, University of Chicago and MacArthur Fellow “Fun, entertaining, witty and darn useful. A magical portal to the big data revolution” -- Sandro Santagata, Assistant Professor in Pathology, Harvard Medical School “Alex and Gordon’s enthusiasm for Python is contagious” -- Glenys Thomson Professor of Integrative Biology, University of California, Berkeley

Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certified as 100% Pure Java. Jython is freely available for both commercial and noncommercial use and is distributed with source code. Jython is complementary to Java. The Definitive Guide to Jython, written by the official Jython team leads, covers Jython 2.5 (or 2.5.x)—from the basics to more advanced features. This book begins with a brief introduction to the language and then journeys through Jython’s different features and uses. The Definitive Guide to Jython is organized for beginners as well as advanced users of the language. The book provides a general overview of the Jython language itself, but it also includes intermediate and advanced topics regarding database, web, and graphical user interface (GUI) applications; Web services/SOA; and integration, concurrency, and parallelism, to name a few.

This book constitutes the proceedings of the 36th International Conference on Application and Theory of Petri Nets and Concurrency, PETRI NETS 2015, held in Brussels, Belgium, in June 2015. The 12 regular papers and 2 tool papers presented in this volume were carefully reviewed and selected from 34 submissions. In addition the book contains 3 invited talks in full paper length. The papers cover various topics in the field of Petri nets and related models of concurrency.

PYTHON 3 Reference Manual (Python Documentation MANUAL Part 2). Python is an easy to learn object-oriented programming language, which combines power with clear syntax. It has modules, classes, exceptions, very high level data types, and dynamic typing. Python is free software. It can be used with GNU (GNU/Linux), Unix, Microsoft Windows and many other systems. This is a printed softcover copy of the official Python documentation from the latest Python 3.0 distribution. For each copy sold $1 will be donated to the Python Software Foundation by the publisher. This book is part of a brand new six-part series of Python documentation books. Searching for "Python Documentation Manual" will show all six available books. ABOUT THE AUTHOR: Guido van Rossum, is the inventor of Python. Fred L. Drake, Jr. is the official editor of the Python documentation.