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    1. Data och IT
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    Unlocking Python

    A Comprehensive Guide for Beginners

    AvRyan Mitchell

    Häftad, Engelska, 2025

    368 kr

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    E-bok

    618 kr

    E-bok

    618 kr

    Beskrivning

    A fun and practical guide to learning Python with a special focus on data science, web scraping, and web applications In Unlocking Python: A Comprehensive Guide for Beginners, veteran software engineer, educator, and author Ryan Mitchell delivers an intuitive, engaging, and practical roadmap to Python programming. The author walks you through the vocabulary, tools, foundational knowledge, and occasional pop-culture references you'll need to hone your skills with this popular programming language. You'll learn how to install and run Python on your own machine, get up and coding with the language quickly, and best practices for programming both independently and in the workplace. You'll also find: Key concepts in computer and data science explained from the ground upAdvanced Python topics such as logging, unit testing, multiprocessing, and interacting with databases.Introductions to some of Python's most popular third-party libraries: Flask, Django, Scrapy, Scikit-Learn, Numpy, and PandasAmusing anecdotes from the trenches of industryPerfect for tech-savvy professionals at any stage of their careers who are interested in diving into Python programming. Unlocking Python is also a must-read for readers who work in a technical role but are interested in getting more directly involved with programming, as well as non-Python programmers who want to apply their technical skill to a new language.

    Produktinformation

    • Utgivningsdatum:2025-05-06
    • Mått:188 x 231 x 28 mm
    • Vikt:635 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:448
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394288496

    Utforska kategorier

    • Programspråk inom Data och IT

    Mer om författaren

    RYAN MITCHELL is the author of Unlocking Python (Wiley), Web Scraping with Python (O’Reilly), and multiple courses on LinkedIn Learning including Python Essential Training. She holds a master’s degree in software engineering from Harvard University Extension School and has worked as principal software engineer and data scientist on the search team at the Gerson Lehrman Group for the last six years.

    Innehållsförteckning

    • Part I: ProgrammingChapter 1: Introduction to Programming 3Programming as a Career 4Myths About Programmers 4How Computers Work 7A Brief History of Modern Computing 12The Unix Operating System 12Modern Programming 13Talking About Programming Languages 14Problem-Solving as a Programmer 17Chapter 2: Programming Tools 21Shell 21Version Control Systems 25Authenticating with GitHub with SSH Keys 27Integrated Development Environments 33Web Browsers 34Chapter 3: About Python 37The Python Software Foundation 38The Zen of Python 39The Python Interpreter 40The Python Standard Library 41Third-Party Libraries 42Versions and Development 43Part II: PythonChapter 4: Installing and Running Python 47Installing Python 47Windows 48macOS 48Linux 49Installing and Using pip 50Windows 51macOS 51Linux 51Installing and Using Jupyter for IPython files 52Virtual Environments 54Anaconda 56Chapter 5: Python Quickstart 59Variables 59Data Types 62Operators 67Arithmetic Operators 67Operators and Assignments 69Comparison Operators 70Identity Operators 71Boolean Operators 73Membership Operators 73Control Flow 74If and Else 75For 76While 76Functions 78Classes 80Everything Is an Object 82Data Structures 82Lists 83Dictionaries 84Tuples 86Sets 86Exercises 88Chapter 6: Lists and Strings 91String Operations 91String Methods 92List Operations 95Slicing 97List Comprehensions 100Exercises 103Chapter 7: Dictionaries, Sets, and Tuples 105Dictionaries 105Dictionary Comprehensions 108Reducing to Dictionaries 110Sets 112Tuples 114Exercises 116Chapter 8: other Types of Objects 119Other Numbers 119Dates 124Bytes 129Exercises 132Chapter 9: Iterables, Iterators, Generators, and Loops 135Iterables and Iterators 135Generators 137Looping with Pass, Break, Else, and Continue 139Assignment Expressions 143Walrus Operators 143Recursion 144Exercises 148Chapter 10: Functions 149Positional Arguments and Keyword Arguments 149Functions as First-Class Objects 155Lambda Functions 158Namespaces 160Decorators 163Exercises 168Chapter 11: Classes 171Static Methods and Attributes 173Inheritance 175Multiple Inheritance 178Encapsulation 182Polymorphism 186Exercises 188Chapter 12: Writing Cleaner Code 189PEP 8 and Code Styles 189Comments and Docstrings 190Documentation 194Linting 196Formatting 199Type Hints 200Part III: Advanced TopicsChapter 13: Errors and Exceptions 207Handling Exceptions 207Else and Finally 210Raising Exceptions 212Custom Exceptions 214Exception Handling Patterns 217Exercises 223Chapter 14: Modules and Packages 225Modules 225Import This 228Packages 229Installing Packages 235Exercises 240Chapter 15: Working with Files 243Reading Files 243Writing Files 247Binary Files 250Buffering Data 252Creating and Deleting Files and Directories 254Serializing, Deserializing, and Pickling Data 256Exercises 259Chapter 16: Logging 261The Logging Module 261Handlers 266Formatting 269Exercises 272Chapter 17: Threads and Processes 275How Threads and Processes Work 275Threading Module 276Locking 280Queues 283Multiprocessing Module 285Exercises 292Chapter 18: Databases 293Installing and Using SQLite 294Installing SQLite 294Using SQLite 296Query Language Syntax 297Using SQLite with Python 300Object Relational Mapping 303Exercises 306Chapter 19: Unit Testing 307The Unit Testing Framework 309Setting Up and Tearing Down 312Mocking Methods 314Mocking with Side Effects 318Part IV: Python FrameworksChapter 20: Rest Apis and Flask 323HTTP and APIs 323Getting Started with Flask Applications 327APIs in Flask 330Databases 333Authentication 336Sessions 338Templates 342Chapter 21: Django 345Installing Django and Starting Django 346Databases and Migrations 351Django Admin Interface 353Models 355More Views and Templates 358More Resources 361Chapter 22: Web Scraping and Scrapy 363Installing and Using Scrapy 364Parsing HTML 366Items 371Crawling with Scrapy 372Item Pipelines 376Chapter 23: Data Analysis with Numpy and Pandas 379NumPy Arrays 380Pandas DataFrames 383Cleaning 387Filtering and Querying 391Grouping and Aggregating 393Chapter 24: Machine Learning with Matplotlib And Scikit-learn 397Types of Machine Learning Models 398Exploratory Analysis with Matplotlib 400Building Supervised Models with Scikit-Learn 409Evaluating Classification Models with Scikit-Learn 415Index 421