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