Python All–in–One For Dummies

John Shovic is a computer science faculty member at the University of Idaho. Alan Simpson is a web development professional and prolific tech author with over 100 publications to his credit.

Introduction 1


About This Book 1


Foolish Assumptions 2


Icons Used in This Book 2


Beyond the Book 3


Where to Go from Here 3


Book 1: Getting Started with Python 5


Chapter 1: Starting with Python 7


Why Python is Hot 8


Choosing the Right Python 9


Tools for Success 11


An excellent, free learning environment 12


Installing Anaconda and VS Code 13


Writing Python in VS Code 17


Choosing your Python interpreter 19


Writing some Python code 20


Getting back to VS Code Python 21


Using Jupyter Notebook for Coding 21


Chapter 2: Interactive Mode, Getting Help, Writing Apps 27


Using Python Interactive Mode 27


Opening Terminal 28


Getting your Python version 28


Going into the Python Interpreter 30


Entering commands 30


Using Python’s built-in help 31


Exiting interactive help 33


Searching for specific help topics online 33


Lots of free cheat sheets 34


Creating a Python Development Workspace 34


Creating a Folder for your Python Code 37


Typing, Editing, and Debugging Python Code 39


Writing Python code 40


Saving your code 41


Running Python in VS Code 41


Simple debugging 42


The VS Code Python debugger 43


Writing Code in a Jupyter Notebook 45


Creating a folder for Jupyter Notebook 45


Creating and saving a Jupyter notebook 46


Typing and running code in a notebook 46


Adding some Markdown text 47


Saving and opening notebooks 48


Chapter 3: Python Elements and Syntax 49


The Zen of Python 49


Object-Oriented Programming 53


Indentations Count, Big Time 54


Using Python Modules 56


Syntax for importing modules 58


Using an alias with modules 59


Chapter 4: Building Your First Python Application 61


Open the Python App File 62


Typing and Using Python Comments 63


Understanding Python Data Types 64


Numbers 65


Words (strings) 66


True/false Booleans 68


Doing Work with Python Operators 69


Arithmetic operators 69


Comparison operators 70


Boolean operators 71


Creating and Using Variables 72


Creating valid variable names 73


Creating variables in code 74


Manipulating variables 75


Saving your work 76


Running your Python app in VS Code 76


What Syntax is and Why It Matters 78


Putting Code Together 82


Book 2: Understanding Python Building Blocks 83


Chapter 1: Working with Numbers, Text, and Dates 85


Calculating Numbers with Functions 86


Still More Math Functions 88


Formatting Numbers 91


Formatting with f-strings 91


Showing dollar amounts 92


Formatting percent numbers 93


Making multiline format strings 95


Formatting width and alignment 96


Grappling with Weirder Numbers 98


Binary, octal, and hexadecimal numbers 98


Complex numbers 99


Manipulating Strings 100


Concatenating strings 101


Getting the length of a string 102


Working with common string operators 102


Manipulating strings with methods 105


Uncovering Dates and Times 107


Working with dates 108


Working with times 112


Calculating timespans 114


Accounting for Time Zones 118


Working with Time Zones 120


Chapter 2: Controlling the Action 125


Main Operators for Controlling the Action 125


Making Decisions with if 126


Adding else to your if login 130


Handling multiple else’s with elif 131


Ternary operations 133


Repeating a Process with for 134


Looping through numbers in a range 134


Looping through a string 136


Looping through a list 137


Bailing out of a loop 138


Looping with continue 140


Nesting loops 140


Looping with while 141


Starting while loops over with continue 143


Breaking while loops with break 144


Chapter 3: Speeding Along with Lists and Tuples 147


Defining and Using Lists 147


Referencing list items by position 148


Looping through a list 150


Seeing whether a list contains an item 150


Getting the length of a list 151


Adding an item to the end of a list 151


Inserting an item into a list 152


Changing an item in a list 153


Combining lists 153


Removing list items 154


Clearing out a list 156


Counting how many times an item appears in a list 157


Finding an list item’s index 158


Alphabetizing and sorting lists 159


Reversing a list 161


Copying a list 162


What’s a Tuple and Who Cares? 163


Working with Sets 165


Chapter 4: Cruising Massive Data with Dictionaries 169


Creating a Data Dictionary 171


Accessing dictionary data 172


Getting the length of a dictionary 174


Seeing whether a key exists in a dictionary 175


Getting dictionary data with get() 176


Changing the value of a key 177


Adding or changing dictionary data 177


Looping through a Dictionary 179


Data Dictionary Methods 181


Copying a Dictionary 182


Deleting Dictionary Items 182


Using pop() with Data Dictionaries 184


Fun with Multi-Key Dictionaries 186


Using the mysterious fromkeys and setdefault methods 188


Nesting Dictionaries 190


Chapter 5: Wrangling Bigger Chunks of Code 193


Creating a Function 194


Commenting a Function 195


Passing Information to a Function 196


Defining optional parameters with defaults 198


Passing multiple values to a function 199


Using keyword arguments (kwargs) 200


Passing multiple values in a list 202


Passing in an arbitrary number of arguments 204


Returning Values from Functions 205


Unmasking Anonymous Functions 206


Chapter 6: Doing Python with Class 213


Mastering Classes and Objects 213


Creating a Class 216


How a Class Creates an Instance 217


Giving an Object Its Attributes 218


Creating an instance from a class 219


Changing the value of an attribute 222


Defining attributes with default values 222


Giving a Class Methods 224


Passing parameters to methods 226


Calling a class method by class name 227


Using class variables 228


Using class methods 230


Using static methods 232


Understanding Class Inheritance 234


Creating the base (main) class 236


Defining a subclass 237


Overriding a default value from a subclass 239


Adding extra parameters from a subclass 239


Calling a base class method 242


Using the same name twice 243


Chapter 7: Sidestepping Errors 247


Understanding Exceptions 247


Handling Errors Gracefully 251


Being Specific about Exceptions 252


Keeping Your App from Crashing 253


Adding an else to the Mix 255


Using try … … … except else finally 257


Raising Your Own Errors 259


Book 3: Working with Python Libraries 265


Chapter 1: Working with External Files 267


Understanding Text and Binary Files 267


Opening and Closing Files 269


Reading a File’s Contents 276


Looping through a File 277


Looping with readlines() 277


Looping with readline() 279


Appending versus overwriting files 280


Using tell() to determine the pointer location 281


Moving the pointer with seek() 283


Reading and Copying a Binary File 283


Conquering CSV Files 286


Opening a CSV file 288


Converting strings 290


Converting to integers 291


Converting to date 292


Converting to Boolean 293


Converting to floats 293


From CSV to Objects and Dictionaries 295


Importing CSV to Python objects 296


Importing CSV to Python dictionaries 299


Chapter 2: Juggling JSON Data 303


Organizing JSON Data 303


Understanding Serialization 306


Loading Data from JSON Files 307


Converting an Excel date to a JSON date 309


Looping through a keyed JSON file 310


Converting firebase timestamps to Python dates 313


Loading unkeyed JSON from a Python string 314


Loading keyed JSON from a Python string 315


Changing JSON data 316


Removing data from a dictionary 317


Dumping Python Data to JSON 318


Chapter 3: Interacting with the Internet 323


How the Web Works 323


Understanding the mysterious URL 324


Exposing the HTTP headers 325


Opening a URL from Python 327


Posting to the Web with Python 328


Scraping the Web with Python 330


Parsing part of a page 333


Storing the parsed content 333


Saving scraped data to a JSON file 335


Saving scraped data to a CSV file 336


Chapter 4: Libraries, Packages, and Modules 339


Understanding the Python Standard Library 339


Using the dir() function 340


Using the help() function 341


Exploring built-in functions 343


Exploring Python Packages 343


Importing Python Modules 345


Making Your Own Modules 348


Book 4: Using Artificial Intelligence in Python 353


Chapter 1: Exploring Artificial Intelligence 355


AI is a Collection of Techniques 356


Neural networks 356


Machine learning 359


TensorFlow — A framework for deep learning 361


Current Limitations of AI 363


Chapter 2: Building a Neural Network in Python 365


Understanding Neural Networks 366


Layers of neurons 367


Weights and biases 368


The activation function 369


Loss function 369


Building a Simple Neural Network in Python 370


The neural-net Python code 370


Using TensorFlow for the same neural network 381


Installing the TensorFlow Python library 382


Building a Python Neural Network in TensorFlow 383


Loading your data 384


Defining your neural-network model and layers 384


Compiling your model 384


Fitting and training your model 384


Breaking down the code 386


Evaluating the model 388


Changing to a three-layer neural network in TensorFlow/Keras 390


Chapter 3: Doing Machine Learning in Python 393


Learning by Looking for Solutions in All the Wrong Places 394


Classifying Clothes with Machine Learning 395


Training and Learning with TensorFlow 395


Setting Up the Software Environment for this Chapter 396


Creating a Machine-Learning Network for Detecting Clothes Types 397


Getting the data — The Fashion-MNIST dataset 398


Training the network 398


Testing our network 398


Breaking down the code 399


Results of the training and evaluation 402


Testing a single test image 402


Testing on external pictures 403


The results, round 1 405


The CNN model code 406


The results, round 2 409


Visualizing with MatPlotLib 409


Learning More Machine Learning 413


Chapter 4: Exploring More AI in Python 415


Limitations of the Raspberry Pi and AI 415


Adding Hardware AI to the Raspberry Pi 418


AI in the Cloud 420


Google cloud 421


Amazon Web Services 421


IBM cloud 422


Microsoft Azure 422


AI on a Graphics Card 423


Where to Go for More AI Fun in Python 424


Book 5: Doing Data Science with Python 427


Chapter 1: The Five Areas of Data Science 429


Working with Big, Big Data 430


Volume 430


Variety 431


Velocity 431


Managing volume, variety, and velocity 432


Cooking with Gas: The Five Step Process of Data Science 432


Capturing the data 433


Processing the data 433


Analyzing the data 434


Communicating the results 434


Maintaining the data 435


Chapter 2: Exploring Big Data with Python 437


Introducing NumPy, Pandas, and MatPlotLib 438


Doing Your First Data Science Project 440


Diamonds are a data scientist’s best friend 440


Breaking down the code 443


Visualizing the data with MatPlotLib 444


Chapter 3: Using Big Data from the Google Cloud 451


What is Big Data? 451


Understanding the Google Cloud and BigQuery 452


The Google Cloud Platform 452


BigQuery from Google 452


Computer security on the cloud 453


Signing up on Google for BigQuery 454


Reading the Medicare Big Data 454


Setting up your project and authentication 454


The first big-data code 457


Breaking down the code 460


A bit of analysis next 461


Payment percent by state 464


And now some visualization 465


Looking for the Most Polluted City in the World on an Hourly Basis 466


Book 6: Talking to Hardware with Python 469


Chapter 1: Introduction to Physical Computing 471


Physical Computing is Fun 472


What is a Raspberry Pi? 472


Making Your Computer Do Things 474


Using Small Computers to Build Projects That Do and Sense Things 474


The Raspberry Pi: A Perfect Platform for Physical Computing in Python 476


GPIO pins 477


GPIO libraries 477


The hardware for “Hello World” 478


Assembling the hardware 478


Controlling the LED with Python on the Raspberry Pi 482


But Wait, There is More 485


Chapter 2: No Soldering! Grove Connectors for Building Things 487


So What is a Grove Connector? 488


Selecting Grove Base Units 489


For the Arduino 489


Raspberry Pi Base Unit — the Pi2Grover 490


The Four Types of Grove Connectors 492


The Four Types of Grove Signals 493


Grove digital — All about those 1’s and 0’s 493


Grove analog: When 1’s and 0’s aren’t enough 494


Grove UART (or serial) — Bit by bit transmission 495


Grove I2C — Using I2C to make sense of the world 497


Using Grove Cables to Get Connected 499


Grove Patch Cables 499


Chapter 3: Sensing the World with Python: The World of I2C 505


Understanding I2C 506


Exploring I2C on the Raspberry Pi 507


Talking to I2C devices with Python 508


Reading temperature and humidity from an I2C


device using Python 511


Breaking down the program 514


A Fun Experiment for Measuring Oxygen and a Flame 517


Analog-to-digital converters (ADC) 518


The Grove oxygen sensor 519


Hooking up the oxygen experiment 520


Breaking down the code 522


Building a Dashboard on Your Phone Using Blynk and Python 525


HDC1080 temperature and humidity sensor redux 525


How to add the Blynk dashboard 527


The modified temperatureTest.py software for the Blynk app 531


Breaking down the code 533


Where to Go from Here 536


Chapter 4: Making Things Move with Python 537


Exploring Electric Motors 538


Small DC motors 538


Servo motors 539


Stepper motors 539


Controlling Motors with a Computer 540


Python and DC Motors 540


Python and running a servo motor 548


Python and making a stepper motor step 554


Book 7: Building Robots with Python 565


Chapter 1: Introduction to Robotics 567


A Robot is Not Always like a Human 567


Not Every Robot Has Arms or Wheels 568


The Wilkinson Bread-Making Robot 569


Baxter the Coffee-Making Robot 570


The Griffin Bluetooth-enabled toaster 571


Understanding the Main Parts of a Robot 572


Computers 572


Motors and actuators 573


Communications 573


Sensors 573


Programming Robots 574


Chapter 2: Building Your First Python Robot 575


Introducing the Mars Rover PiCar-B 575


What you need for the build 576


Understanding the robot components 577


Assembling the Robot 586


Calibrating your servos 588


Running tests on your rover in Python 591


Installing software for the CarPi-B Python test 591


The PiCar-B Python test code 592


Pi camera video testing 592


Chapter 3: Programming Your Robot Rover in Python 595


Building a Simple High-Level Python Interface 595


The motorForward function 596


The wheelsLeft function 596


The wheelsPercent function 596


Making a Single Move with Python 597


Functions of the RobotInterface Class 598


Front LED functions 598


Pixel strip functions 600


Ultrasonic distance sensor function 601


Main motor functions 602


Servo functions 603


General servo function 606


The Python Robot Interface Test 606


Coordinating Motor Movements with Sensors 610


Making a Python Brain for Our Robot 613


A Better Robot Brain Architecture 620


Overview of the Included Adeept Software 621


Where to Go from Here? 622


Chapter 4: Using Artificial Intelligence in Robotics 623


This Chapter’s Project: Going to the Dogs 624


Setting Up the Project 624


Machine Learning Using TensorFlow 625


The code 627


Examining the code 629


The results 632


Testing the Trained Network 633


The code 634


Explaining the code 636


The results 637


Taking Cats and Dogs to Our Robot 640


The code 640


How it works 643


The results 643


Other Things You Can Do with AI Techniques and the Robot 645


Cat/Not Cat 645


Santa/Not Santa 646


Follow the ball 646


Using Alexa to control your robot 646


AI and the Future of Robotics 646


Index 647