Learn Python Programming 2nd edition - Original PDF

دانلود کتاب Learn Python Programming 2nd edition - Original PDF

Author:  Fabrizio Romano

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توضیحات کتاب :

Learn the fundamentals of Python (3.7) and how to apply it to data science, programming, and web development. Fully updated to include hands-on tutorials and projects. Key Features Learn the fundamentals of Python programming with interactive projects Apply Python to data science with tools such as IPython and Jupyter Utilize Python for web development and build a real-world app using Django

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Book Description

Learn Python Programming is a quick, thorough, and practical introduction to Python - an extremely flexible and powerful programming language that can be applied to many disciplines.

Unlike other books, it doesn't bore you with elaborate explanations of the basics but gets you up-and-running, using the language. You will begin by learning the fundamentals of Python so that you have a rock-solid foundation to build upon.

You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens.

Learn Python Programming will give you a thorough understanding of the Python language. You'll learn how to write programs, build websites, and work with data by harnessing Python's renowned data science libraries. Filled with real-world examples and projects, the book covers various types of applications, and concludes by building real-world projects based on the concepts you have learned.

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Learn Python Programming مقدمه ای سریع، کامل و کاربردی برای Python است - یک زبان برنامه نویسی بسیار انعطاف پذیر و قدرتمند که می تواند در بسیاری از رشته ها اعمال شود.

برخلاف کتاب‌های دیگر، با توضیحات مفصل درباره اصول اولیه شما را خسته نمی‌کند، اما با استفاده از زبان، شما را سرحال می‌کند. شما با یادگیری اصول پایتون شروع خواهید کرد تا پایه ای محکم برای ساختن داشته باشید.

شما مبانی برنامه نویسی پایتون را بررسی خواهید کرد و یاد خواهید گرفت که چگونه پایتون را می توان برای دستیابی به نتایج دستکاری کرد. پارادایم های مختلف برنامه نویسی را کاوش کنید و بهترین رویکرد را برای یک موقعیت پیدا کنید. درک نحوه انجام بهینه سازی عملکرد و اشکال زدایی موثر؛ کنترل جریان یک برنامه؛ و از یک فرمت تبادل برای تبادل داده استفاده کنید. همچنین می‌توانید از طریق سرویس‌های رمزنگاری در Python قدم بزنید و نشانه‌های امن را درک کنید.

Learn Python Programming به شما درک کاملی از زبان پایتون می دهد. شما یاد خواهید گرفت که چگونه برنامه بنویسید، وب سایت بسازید، و با استفاده از کتابخانه های علم داده معروف پایتون، با داده ها کار کنید. این کتاب که پر از مثال‌ها و پروژه‌های واقعی است، انواع مختلفی از برنامه‌ها را پوشش می‌دهد و با ساختن پروژه‌های دنیای واقعی بر اساس مفاهیمی که آموخته‌اید به پایان می‌رسد.

 

ادامه ...

  • Title: Learn Python Programming - Second Edition
  • Author(s): Fabrizio Romano
  • Release date: June 2018
  • Publisher(s): Packt Publishing
  • ISBN: 9781788996662
 
 
 
 

ادامه ...

Title Page Copyright and Credits Learn Python Programming Second Edition Dedication Packt Upsell Why subscribe? PacktPub.com Foreword Contributors About the author About the reviewers Packt is searching for authors like you Preface Who this book is for What this book covers To get the most out of this book Download the example code files Conventions used Get in touch Reviews A Gentle Introduction to Python A proper introduction Enter the Python About Python Portability Coherence Developer productivity An extensive library Software quality Software integration Satisfaction and enjoyment What are the drawbacks? Who is using Python today? Setting up the environment Python 2 versus Python 3 Installing Python Setting up the Python interpreter About virtualenv Your first virtual environment Your friend, the console How you can run a Python program Running Python scripts Running the Python interactive shell Running Python as a service Running Python as a GUI application How is Python code organized? How do we use modules and packages? Python's execution model Names and namespaces Scopes Objects and classes Guidelines on how to write good code The Python culture A note on IDEs Summary Built-in Data Types Everything is an object Mutable or immutable? That is the question Numbers Integers Booleans Real numbers Complex numbers Fractions and decimals Immutable sequences Strings and bytes Encoding and decoding strings Indexing and slicing strings String formatting Tuples Mutable sequences Lists Byte arrays Set types Mapping types – dictionaries The collections module namedtuple defaultdict ChainMap Enums Final considerations Small values caching How to choose data structures About indexing and slicing About the names Summary Iterating and Making Decisions Conditional programming A specialized else – elif The ternary operator Looping The for loop Iterating over a range Iterating over a sequence Iterators and iterables Iterating over multiple sequences The while loop The break and continue statements A special else clause Putting all this together A prime generator Applying discounts A quick peek at the itertools module Infinite iterators Iterators terminating on the shortest input sequence Combinatoric generators Summary Functions, the Building Blocks of Code Why use functions? Reducing code duplication Splitting a complex task Hiding implementation details Improving readability Improving traceability Scopes and name resolution The global and nonlocal statements Input parameters Argument-passing Assignment to argument names doesn't affect the caller Changing a mutable affects the caller How to specify input parameters Positional arguments Keyword arguments and default values Variable positional arguments Variable keyword arguments Keyword-only arguments Combining input parameters Additional unpacking generalizations Avoid the trap! Mutable defaults Return values Returning multiple values A few useful tips Recursive functions Anonymous functions Function attributes Built-in functions One final example Documenting your code Importing objects Relative imports Summary Saving Time and Memory The map, zip, and filter functions map zip filter Comprehensions Nested comprehensions Filtering a comprehension dict comprehensions set comprehensions Generators Generator functions Going beyond next The yield from expression Generator expressions Some performance considerations Don't overdo comprehensions and generators Name localization Generation behavior in built-ins One last example Summary OOP, Decorators, and Iterators Decorators A decorator factory Object-oriented programming (OOP) The simplest Python class Class and object namespaces Attribute shadowing Me, myself, and I – using the self variable Initializing an instance OOP is about code reuse Inheritance and composition Accessing a base class Multiple inheritance Method resolution order Class and static methods Static methods Class methods Private methods and name mangling The property decorator Operator overloading Polymorphism – a brief overview Data classes Writing a custom iterator Summary Files and Data Persistence Working with files and directories Opening files Using a context manager to open a file Reading and writing to a file Reading and writing in binary mode Protecting against overriding an existing file Checking for file and directory existence Manipulating files and directories Manipulating pathnames Temporary files and directories Directory content File and directory compression Data interchange formats Working with JSON Custom encoding/decoding with JSON IO, streams, and requests Using an in-memory stream Making HTTP requests Persisting data on disk Serializing data with pickle Saving data with shelve Saving data to a database Summary Testing, Profiling, and Dealing with Exceptions Testing your application The anatomy of a test Testing guidelines Unit testing Writing a unit test Mock objects and patching Assertions Testing a CSV generator Boundaries and granularity Testing the export function Final considerations Test-driven development Exceptions Profiling Python When to profile? Summary Cryptography and Tokens The need for cryptography Useful guidelines Hashlib Secrets Random numbers Token generation Digest comparison HMAC JSON Web Tokens Registered claims Time-related claims Auth-related claims Using asymmetric (public-key) algorithms Useful references Summary Concurrent Execution Concurrency versus parallelism Threads and processes – an overview Quick anatomy of a thread Killing threads Context-switching The Global Interpreter Lock Race conditions and deadlocks Race conditions Scenario A – race condition not happening Scenario B – race condition happening Locks to the rescue Scenario C – using a lock Deadlocks Quick anatomy of a process Properties of a process Multithreading or multiprocessing? Concurrent execution in Python Starting a thread Starting a process Stopping threads and processes Stopping a process Spawning multiple threads Dealing with race conditions A thread's local data Thread and process communication Thread communication Sending events Inter-process communication with queues Thread and process pools Using a process to add a timeout to a function Case examples Example one – concurrent mergesort Single-thread mergesort Single-thread multipart mergesort Multithreaded mergesort Multiprocess mergesort Example two – batch sudoku-solver What is Sudoku? Implementing a sudoku-solver in Python Solving sudoku with multiprocessing Example three – downloading random pictures Downloading random pictures with asyncio Summary Debugging and Troubleshooting Debugging techniques Debugging with print Debugging with a custom function Inspecting the traceback Using the Python debugger Inspecting log files Other techniques Profiling Assertions Where to find information Troubleshooting guidelines Using console editors Where to inspect Using tests to debug Monitoring Summary GUIs and Scripts First approach – scripting The imports Parsing arguments The business logic Second approach – a GUI application The imports The layout logic The business logic Fetching the web page Saving the images Alerting the user How can we improve the application? Where do we go from here? The turtle module wxPython, PyQt, and PyGTK The principle of least astonishment Threading considerations Summary Data Science IPython and Jupyter Notebook Installing the required libraries Using Anaconda Starting a Notebook Dealing with data Setting up the Notebook Preparing the data Cleaning the data Creating the DataFrame Unpacking the campaign name Unpacking the user data Cleaning everything up Saving the DataFrame to a file Visualizing the results Where do we go from here? Summary Web Development What is the web? How does the web work? The Django web framework Django design philosophy The model layer The view layer The template layer The Django URL dispatcher Regular expressions A regex website Setting up Django Starting the project Creating users Adding the Entry model Customizing the admin panel Creating the form Writing the views The home view The entry list view The form view Tying up URLs and views Writing the templates The future of web development Writing a Flask view Building a JSON quote server in Falcon Summary Farewell Other Books You May Enjoy Leave a review - let other readers know what you think

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