Python in a Nutshell

2006-07-14

Author: Alex Martelli

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449379100

Category: Computers

Page: 738

View: 256

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This book offers Python programmers one place to look when they needhelp remembering or deciphering the syntax of this open source languageand its many powerful but scantily documented modules. Thiscomprehensive reference guide makes it easy to look up the mostfrequently needed information--not just about the Python languageitself, but also the most frequently used parts of the standard libraryand the most important third-party extensions. Ask any Python aficionado and you'll hear that Python programmers haveit all: an elegant object-oriented language with readable andmaintainable syntax, that allows for easy integration with componentsin C, C++, Java, or C#, and an enormous collection of precoded standardlibrary and third-party extension modules. Moreover, Python is easy tolearn, yet powerful enough to take on the most ambitious programmingchallenges. But what Python programmers used to lack is a concise andclear reference resource, with the appropriate measure of guidance inhow best to use Python's great power. Python in aNutshell fills this need. Python in a Nutshell, Second Edition covers morethan the language itself; it also deals with the mostfrequently used parts of the standard library, and the most popular andimportant third party extensions. Revised and expanded forPython 2.5, this book now contains the gory details of Python's newsubprocess module and breaking news about Microsoft's newIronPython project. Our "Nutshell" format fits Python perfectly bypresenting the highlights of the most important modules and functionsin its standard library, which cover over 90% of your practicalprogramming needs. This book includes: A fast-paced tutorial on the syntax of the Python language An explanation of object-oriented programming in Python Coverage of iterators, generators, exceptions, modules,packages, strings, and regular expressions A quick reference for Python's built-in types and functionsand key modules Reference material on important third-party extensions,such as Numeric and Tkinter Information about extending and embedding Python Python in a Nutshell provides a solid,no-nonsense quick reference to information that programmers rely on themost. This book will immediately earn its place in any Pythonprogrammer's library. Praise for the First Edition: "In a nutshell, Python in a Nutshell serves oneprimary goal: to act as an immediately accessible goal for the Pythonlanguage. True, you can get most of the same core information that ispresented within the covers of this volume online, but this willinvariably be broken into multiple files, and in all likelihood lackingthe examples or the exact syntax description necessary to trulyunderstand a command." --Richard Cobbett, Linux Format "O'Reilly has several good books, of which Python in aNutshell by Alex Martelli is probably the best for giving yousome idea of what Python is about and how to do useful things with it." --Jerry Pournelle, Byte Magazine

Neuronale Netze Selbst Programmieren

2017

Author: Tariq Rashid

Publisher:

ISBN: 1492064041

Category:

Page: 232

View: 184

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Neuronale Netze sind Schlüsselelemente des Deep Learning und der Künstlichen Intelligenz, die heute zu Erstaunlichem in der Lage sind. Dennoch verstehen nur wenige, wie Neuronale Netze tatsächlich funktionieren. Dieses Buch nimmt Sie mit auf eine unterhaltsame Reise, die mit ganz einfachen Ideen beginnt und Ihnen Schritt für Schritt zeigt, wie Neuronale Netze arbeiten. Dafür brauchen Sie keine tieferen Mathematik-Kenntnisse, denn alle mathematischen Konzepte werden behutsam und mit vielen Illustrationen erläutert. Dann geht es in die Praxis: Sie programmieren Ihr eigenes Neuronales Netz mit Python und bringen ihm bei, handgeschriebene Zahlen zu erkennen, bis es eine Performance wie ein professionell entwickeltes Netz erreicht. Zum Schluss lassen Sie das Netz noch auf einem Raspberry Pi Zero laufen. - Tariq Rashid hat eine besondere Fähigkeit, schwierige Konzepte verständlich zu erklären, dadurch werden Neuronale Netze für jeden Interessierten zugänglich und praktisch nachvollziehbar.

Learning Python

2009-10-06

Author: Mark Lutz

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449379322

Category: Computers

Page: 1216

View: 347

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Google and YouTube use Python because it's highly adaptable, easy to maintain, and allows for rapid development. If you want to write high-quality, efficient code that's easily integrated with other languages and tools, this hands-on book will help you be productive with Python quickly -- whether you're new to programming or just new to Python. It's an easy-to-follow self-paced tutorial, based on author and Python expert Mark Lutz's popular training course. Each chapter contains a stand-alone lesson on a key component of the language, and includes a unique Test Your Knowledge section with practical exercises and quizzes, so you can practice new skills and test your understanding as you go. You'll find lots of annotated examples and illustrations to help you get started with Python 3.0. Learn about Python's major built-in object types, such as numbers, lists, and dictionaries Create and process objects using Python statements, and learn Python's general syntax model Structure and reuse code using functions, Python's basic procedural tool Learn about Python modules: packages of statements, functions, and other tools, organized into larger components Discover Python's object-oriented programming tool for structuring code Learn about the exception-handling model, and development tools for writing larger programs Explore advanced Python tools including decorators, descriptors, metaclasses, and Unicode processing

Python Cookbook

2005-03-18

Author: Alex Martelli

Publisher: "O'Reilly Media, Inc."

ISBN: 9780596554743

Category: Computers

Page: 846

View: 430

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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.

Derivatives Analytics with Python

2015-06-15

Author: Yves Hilpisch

Publisher: John Wiley & Sons

ISBN: 9781119038009

Category: Business & Economics

Page: 376

View: 369

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Supercharge options analytics and hedging using the power of Python Derivatives Analytics with Python shows you how to implement market-consistent valuation and hedging approaches using advanced financial models, efficient numerical techniques, and the powerful capabilities of the Python programming language. This unique guide offers detailed explanations of all theory, methods, and processes, giving you the background and tools necessary to value stock index options from a sound foundation. You'll find and use self-contained Python scripts and modules and learn how to apply Python to advanced data and derivatives analytics as you benefit from the 5,000+ lines of code that are provided to help you reproduce the results and graphics presented. Coverage includes market data analysis, risk-neutral valuation, Monte Carlo simulation, model calibration, valuation, and dynamic hedging, with models that exhibit stochastic volatility, jump components, stochastic short rates, and more. The companion website features all code and IPython Notebooks for immediate execution and automation. Python is gaining ground in the derivatives analytics space, allowing institutions to quickly and efficiently deliver portfolio, trading, and risk management results. This book is the finance professional's guide to exploiting Python's capabilities for efficient and performing derivatives analytics. Reproduce major stylized facts of equity and options markets yourself Apply Fourier transform techniques and advanced Monte Carlo pricing Calibrate advanced option pricing models to market data Integrate advanced models and numeric methods to dynamically hedge options Recent developments in the Python ecosystem enable analysts to implement analytics tasks as performing as with C or C++, but using only about one-tenth of the code or even less. Derivatives Analytics with Python — Data Analysis, Models, Simulation, Calibration and Hedging shows you what you need to know to supercharge your derivatives and risk analytics efforts.

Graph Drawing

2005-02-10

Author: Janos Pach

Publisher: Springer

ISBN: 9783540318439

Category: Computers

Page: 540

View: 708

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This book constitutes the thoroughly refereed post-proceedings of the 12th International Symposium on Graph Drawing, GD 2004, held in New York, NY, USA in September/October 2004. The 39 revised full papers and 12 revised short papers presented together with 4 posters and a report on the graph drawing context were carefully selected during two rounds of reviewing and improvement. All current aspects in graph drawing are addressed ranging from foundational and methodological issues to applications for various classes of graphs in a variety of fields.

Python Interviews

2018-02-28

Author: Michael Driscoll

Publisher: Packt Publishing Ltd

ISBN: 9781788391764

Category: Computers

Page: 366

View: 756

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Mike Driscoll takes you on a journey talking to a hall-of-fame list of truly remarkable Python experts. You’ll be inspired every time by their passion for the Python language, as they share with you their experiences, contributions, and careers in Python. Key Features Hear from these key Python thinkers about the current status of Python, and where it's heading in the future Listen to their close thoughts on significant Python topics, such as Python's role in scientific computing, and machine learning Understand the direction of Python, and what needs to change for Python 4 Book Description Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips. • Brett Cannon - former director of the PSF, Python core developer, led the migration to Python 3. • Steve Holden - tireless Python promoter and former chairman and director of the PSF. • Carol Willing - former director of the PSF and Python core developer, Project Jupyter Steering Council member. • Nick Coghlan - founding member of the PSF's Packaging Working Group and Python core developer. • Jessica McKellar - former director of the PSF and Python activist. • Marc-André Lemburg - Python core developer and founding member of the PSF. • Glyph Lefkowitz - founder of Twisted and fellow of the PSF • Doug Hellmann - fellow of the PSF, creator of the Python Module of the Week blog, Python community member since 1998. • Massimo Di Pierro - fellow of the PSF, data scientist and the inventor of web2py. • Alex Martelli - fellow of the PSF and co-author of Python in a Nutshell. • Barry Warsaw - fellow of the PSF, Python core developer since 1995, and original member of PythonLabs. • Tarek Ziadé - founder of Afpy and author of Expert Python Programming. • Sebastian Raschka - data scientist and author of Python Machine Learning. • Wesley Chun - fellow of the PSF and author of the Core Python Programming books. • Steven Lott - Python blogger and author of Python for Secret Agents. • Oliver Schoenborn - author of Pypubsub and wxPython mailing list contributor. • Al Sweigart - bestselling author of Automate the Boring Stuff with Python and creator of the Python modules Pyperclip and PyAutoGUI. • Luciano Ramalho - fellow of the PSF and the author of Fluent Python. • Mike Bayer - fellow of the PSF, creator of open source libraries including SQLAlchemy. • Jake Vanderplas - data scientist and author of Python Data Science Handbook. What you will learn How successful programmers think The history of Python Insights into the minds of the Python core team Trends in Python programming Who this book is for Python programmers and students interested in the way that Python is used – past and present – with useful anecdotes. It will also be of interest to those looking to gain insights from top programmers.

Python Scripting for Computational Science

2013-03-14

Author: Hans Petter Langtangen

Publisher: Springer Science & Business Media

ISBN: 9783662054505

Category: Computers

Page: 732

View: 266

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Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries.

Programming Python

2010-12-14

Author: Mark Lutz

Publisher: "O'Reilly Media, Inc."

ISBN: 9781449302856

Category: Computers

Page: 1632

View: 850

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Provides information and tutorials on Python's application domains and its use in databases, networking, scripting layers, and text processing.

The Hitchhiker's Guide to Python

2016-08-30

Author: Kenneth Reitz

Publisher: "O'Reilly Media, Inc."

ISBN: 9781491933237

Category: Computers

Page: 338

View: 800

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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 diversity—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 Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

Fluent Python

2022-03-31

Author: Luciano Ramalho

Publisher: "O'Reilly Media, Inc."

ISBN: 9781492056324

Category: Computers

Page: 1014

View: 507

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Don't waste time bending Python to fit patterns you've learned in other languages. Python's simplicity lets you become productive quickly, but often this means you aren't using everything the language has to offer. With the updated edition of this hands-on guide, you'll learn how to write effective, modern Python 3 code by leveraging its best ideas. Discover and apply idiomatic Python 3 features beyond your past experience. Author Luciano Ramalho guides you through Python's core language features and libraries and teaches you how to make your code shorter, faster, and more readable. Complete with major updates throughout, this new edition features five parts that work as five short books within the book: Data structures: Sequences, dicts, sets, Unicode, and data classes Functions as objects: First-class functions, related design patterns, and type hints in function declarations Object-oriented idioms: Composition, inheritance, mixins, interfaces, operator overloading, protocols, and more static types Control flow: Context managers, generators, coroutines, async/await, and thread/process pools Metaprogramming: Properties, attribute descriptors, class decorators, and new class metaprogramming hooks that replace or simplify metaclasses

Python Multiprocessing Interview Questions

Author: Jason Brownlee

Publisher: SuperFastPython.com

ISBN:

Category: Computers

Page: 114

View: 377

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How well do you know Python multiprocessing? The multiprocessing module provides process-based concurrency in Python and few developers know about it, let alone, how to use it well. The main reason is because it is widely thought that Python does not fully support concurrency. This is false. In fact, processes provide the best path to full parallelism in Python for CPU-bound tasks. * Do you know how to start a new process? * Do you know how to use mutex locks with Python processes? * Do you know how to use a manager or a pool? Discover 180+ interview questions on Python multiprocessing. * Study the questions and answers and improve your skill. * Test yourself to see what you really know, and what you don't. * Select questions to interview developers on a new role. Prepare for an interview or test your Python multiprocessing skills today.

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