Python All-in-One For Dummies (For Dummies (Computer/Tech))

Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it's used in a variety of applications.;Book 1: Getting started with Python. Chapter 1: Starting with Python ; Chapter 2: Interactive mode, getting help, writing apps ; Chapter 3: Python elements and syntax ; Chapter 4: Building your first Python application -- Book 2: Understanding Python building blocks. Chapter 1: Working with numbers, text, and dates ; Chapter 2: Controlling the action ; Chapter 3: Speeding along with lists and tuples ; Chapter 4: Cruising massive data with dictionaries ; Chapter 5: Wrangling bigger chunks of code ; Chapter 6: Doing Python with class ; Chapter 7: Sidestepping errors -- Book 3: Working with Python libraries. Chapter 1: Working with external files ; Chapter 2: Juggling JSON data ; Chapter 3: Interacting with the internet ; Chapter 4: Libraries, packages, and modules -- Book 4: Using artificial intelligences in Python. Chapter 1: Exploring artificial intelligence ; Chapter 2: Building a neural network in Python ; Chapter 3: Doing machine learning in Python ; Chapter 4: Exploring more AI in Python -- Book 5: Doing data science with Python. Chapter 1: The five areas of data science ; Chapter 2: Exploring big data with Python ; Chapter 3: Using big data from the Google cloud -- Book 6: Talking to hardware with Python. Chapter 1: Introduction to physical computing ; Chapter 2: No soldering! Grove connectors for building things ; Chapter 3: Sensing the world with Python: the world of I2C ; Chapter 4: Making things move with Python -- Book 7: Building robots with Python. Chapter 1: Introduction to robotics ; Chapter 2: Building your first Python robot ; Chapter 3: Programming your robot rover in Python ; Chapter 4: Using artificial intelligence in robotics. Title page 2 Copyright Page 3 Table of Contents 6 Introduction 18 About This Book 18 Foolish Assumptions 19 Icons Used in This Book 19 Beyond the Book 20 Where to Go from Here 20 Book 1 Getting Started with Python 22 Chapter 1 Starting with Python 24 Why Python Is Hot 25 Choosing the Right Python 26 Tools for Success 28 An excellent, free learning environment 29 Installing Anaconda and VS Code 30 Writing Python in VS Code 34 Choosing your Python interpreter 36 Writing some Python code 37 Getting back to VS Code Python 38 Using Jupyter Notebook for Coding 38 Chapter 2 Interactive Mode, Getting Help, Writing Apps 44 Using Python Interactive Mode 44 Opening Terminal 45 Getting your Python version 45 Going into the Python Interpreter 47 Entering commands 47 Using Python’s built-in help 48 Exiting interactive help 50 Searching for specific help topics online 50 Lots of free cheat sheets 51 Creating a Python Development Workspace 51 Creating a Folder for your Python Code 54 Typing, Editing, and Debugging Python Code 56 Writing Python code 57 Saving your code 58 Running Python in VS Code 58 Simple debugging 59 The VS Code Python debugger 60 Writing Code in a Jupyter Notebook 62 Creating a folder for Jupyter Notebook 62 Creating and saving a Jupyter notebook 63 Typing and running code in a notebook 63 Adding some Markdown text 64 Saving and opening notebooks 65 Chapter 3 Python Elements and Syntax 66 The Zen of Python 66 Object-Oriented Programming 70 Indentations Count, Big Time 71 Using Python Modules 73 Syntax for importing modules 75 Using an alias with modules 76 Chapter 4 Building Your First Python Application 78 Open the Python App File 79 Typing and Using Python Comments 80 Understanding Python Data Types 81 Numbers 82 Words (strings) 83 True/false Booleans 85 Doing Work with Python Operators 86 Arithmetic operators 86 Comparison operators 87 Boolean operators 88 Creating and Using Variables 89 Creating valid variable names 90 Creating variables in code 91 Manipulating variables 92 Saving your work 93 Running your Python app in VS Code 93 What Syntax Is and Why It Matters 95 Putting Code Together 99 Book 2 Understanding Python Building Blocks 100 Chapter 1 Working with Numbers, Text, and Dates 102 Calculating Numbers with Functions 103 Still More Math Functions 105 Formatting Numbers 108 Formatting with f-strings 108 Showing dollar amounts 109 Formatting percent numbers 110 Making multiline format strings 112 Formatting width and alignment 113 Grappling with Weirder Numbers 115 Binary, octal, and hexadecimal numbers 115 Complex numbers 116 Manipulating Strings 117 Concatenating strings 118 Getting the length of a string 119 Working with common string operators 119 Manipulating strings with methods 122 Uncovering Dates and Times 124 Working with dates 125 Working with times 129 Calculating timespans 131 Accounting for Time Zones 135 Working with Time Zones 137 Chapter 2 Controlling the Action 142 Main Operators for Controlling the Action 142 Making Decisions with if 143 Adding else to your if login 147 Handling multiple else’s with elif 148 Ternary operations 150 Repeating a Process with for 151 Looping through numbers in a range 151 Looping through a string 153 Looping through a list 154 Bailing out of a loop 155 Looping with continue 157 Nesting loops 157 Looping with while 158 Starting while loops over with continue 160 Breaking while loops with break 161 Chapter 3 Speeding Along with Lists and Tuples 164 Defining and Using Lists 164 Referencing list items by position 165 Looping through a list 167 Seeing whether a list contains an item 167 Getting the length of a list 168 Adding an item to the end of a list 168 Inserting an item into a list 169 Changing an item in a list 170 Combining lists 170 Removing list items 171 Clearing out a list 173 Counting how many times an item appears in a list 174 Finding an list item’s index 175 Alphabetizing and sorting lists 176 Reversing a list 178 Copying a list 179 What’s a Tuple and Who Cares? 180 Working with Sets 182 Chapter 4 Cruising Massive Data with Dictionaries 186 Creating a Data Dictionary 188 Accessing dictionary data 189 Getting the length of a dictionary 191 Seeing whether a key exists in a dictionary 192 Getting dictionary data with get() 193 Changing the value of a key 194 Adding or changing dictionary data 194 Looping through a Dictionary 196 Data Dictionary Methods 198 Copying a Dictionary 199 Deleting Dictionary Items 199 Using pop() with Data Dictionaries 201 Fun with Multi-Key Dictionaries 203 Using the mysterious fromkeys and setdefault methods 205 Nesting Dictionaries 207 Chapter 5 Wrangling Bigger Chunks of Code 210 Creating a Function 211 Commenting a Function 212 Passing Information to a Function 213 Defining optional parameters with defaults 215 Passing multiple values to a function 216 Using keyword arguments (kwargs) 217 Passing multiple values in a list 219 Passing in an arbitrary number of arguments 221 Returning Values from Functions 222 Unmasking Anonymous Functions 223 Chapter 6 Doing Python with Class 230 Mastering Classes and Objects 230 Creating a Class 233 How a Class Creates an Instance 234 Giving an Object Its Attributes 235 Creating an instance from a class 236 Changing the value of an attribute 239 Defining attributes with default values 239 Giving a Class Methods 241 Passing parameters to methods 243 Calling a class method by class name 244 Using class variables 245 Using class methods 247 Using static methods 249 Understanding Class Inheritance 251 Creating the base (main) class 253 Defining a subclass 254 Overriding a default value from a subclass 256 Adding extra parameters from a subclass 256 Calling a base class method 259 Using the same name twice 260 Chapter 7 Sidestepping Errors 264 Understanding Exceptions 264 Handling Errors Gracefully 268 Being Specific about Exceptions 269 Keeping Your App from Crashing 270 Adding an else to the Mix 272 Using try . . . except . . . else . . . finally 274 Raising Your Own Errors 276 Book 3 Working with Python Libraries 282 Chapter 1 Working with External Files 284 Understanding Text and Binary Files 284 Opening and Closing Files 286 Reading a File’s Contents 293 Looping through a File 294 Looping with readlines() 294 Looping with readline() 296 Appending versus overwriting files 297 Using tell() to determine the pointer location 298 Moving the pointer with seek() 300 Reading and Copying a Binary File 300 Conquering CSV Files 303 Opening a CSV file 305 Converting strings 307 Converting to integers 308 Converting to date 309 Converting to Boolean 310 Converting to floats 310 From CSV to Objects and Dictionaries 312 Importing CSV to Python objects 313 Importing CSV to Python dictionaries 316 Chapter 2 Juggling JSON Data 320 Organizing JSON Data 320 Understanding Serialization 323 Loading Data from JSON Files 324 Converting an Excel date to a JSON date 326 Looping through a keyed JSON file 327 Converting firebase timestamps to Python dates 330 Loading unkeyed JSON from a Python string 331 Loading keyed JSON from a Python string 332 Changing JSON data 333 Removing data from a dictionary 334 Dumping Python Data to JSON 335 Chapter 3 Interacting with the Internet 340 How the Web Works 340 Understanding the mysterious URL 341 Exposing the HTTP headers 342 Opening a URL from Python 344 Posting to the Web with Python 346 Scraping the Web with Python 347 Parsing part of a page 350 Storing the parsed content 350 Saving scraped data to a JSON file 353 Saving scraped data to a CSV file 354 Chapter 4 Libraries, Packages, and Modules 356 Understanding the Python Standard Library 356 Using the dir() function 357 Using the help() function 358 Exploring built-in functions 360 Exploring Python Packages 360 Importing Python Modules 362 Making Your Own Modules 365 Book 4 Using Artificial Intelligence in Python 370 Chapter 1 Exploring Artificial Intelligence 372 AI Is a Collection of Techniques 373 Neural networks 373 Machine learning 376 TensorFlow — A framework for deep learning 378 Current Limitations of AI 380 Chapter 2 Building a Neural Network in Python 382 Understanding Neural Networks 383 Layers of neurons 384 Weights and biases 385 The activation function 386 Loss function 386 Building a Simple Neural Network in Python 387 The neural-net Python code 387 Using TensorFlow for the same neural network 398 Installing the TensorFlow Python library 399 Building a Python Neural Network in TensorFlow 400 Loading your data 401 Defining your neural-network model and layers 401 Compiling your model 401 Fitting and training your model 401 Breaking down the code 403 Evaluating the model 405 Changing to a three-layer neural network in TensorFlow/Keras 407 Chapter 3 Doing Machine Learning in Python 410 Learning by Looking for Solutions in All the Wrong Places 411 Classifying Clothes with Machine Learning 412 Training and Learning with TensorFlow 412 Setting Up the Software Environment for this Chapter 413 Creating a Machine-Learning Network for Detecting Clothes Types 414 Getting the data — The Fashion-MNIST dataset 415 Training the network 415 Testing our network 415 Breaking down the code 416 Results of the training and evaluation 419 Testing a single test image 419 Testing on external pictures 420 The results, round 1 422 The CNN model code 423 The results, round 2 426 Visualizing with MatPlotLib 426 Learning More Machine Learning 430 Chapter 4 Exploring More AI in Python 432 Limitations of the Raspberry Pi and AI 432 Adding Hardware AI to the Raspberry Pi 435 AI in the Cloud 437 Google cloud 438 Amazon Web Services 438 IBM cloud 439 Microsoft Azure 439 AI on a Graphics Card 440 Where to Go for More AI Fun in Python 441 Book 5 Doing Data Science with Python 444 Chapter 1 The Five Areas of Data Science 446 Working with Big, Big Data 447 Volume 447 Variety 448 Velocity 448 Managing volume, variety, and velocity 449 Cooking with Gas: The Five Step Process of Data Science 449 Capturing the data 450 Processing the data 450 Analyzing the data 451 Communicating the results 451 Maintaining the data 452 Chapter 2 Exploring Big Data with Python 454 Introducing NumPy, Pandas, and MatPlotLib 455 Doing Your First Data Science Project 457 Diamonds are a data scientist’s best friend 457 Breaking down the code 460 Visualizing the data with MatPlotLib 461 Chapter 3 Using Big Data from the Google Cloud 468 What Is Big Data? 468 Understanding the Google Cloud and BigQuery 469 The Google Cloud Platform 469 BigQuery from Google 469 Computer security on the cloud 470 Signing up on Google for BigQuery 471 Reading the Medicare Big Data 471 Setting up your project and authentication 471 The first big-data code 474 Breaking down the code 477 A bit of analysis next 478 Payment percent by state 481 And now some visualization 482 Looking for the Most Polluted City in the World on an Hourly Basis 483 Book 6 Talking to Hardware with Python 486 Chapter 1 Introduction to Physical Computing 488 Physical Computing Is Fun 489 What Is a Raspberry Pi? 489 Making Your Computer Do Things 491 Using Small Computers to Build Projects That Do and Sense Things 491 The Raspberry Pi: A Perfect Platform for Physical Computing in Python 493 GPIO pins 494 GPIO libraries 494 The hardware for “Hello World” 495 Assembling the hardware 495 Controlling the LED with Python on the Raspberry Pi 499 But Wait, There Is More . . . 502 Chapter 2 No Soldering! Grove Connectors for Building Things 504 So What Is a Grove Connector? 505 Selecting Grove Base Units 506 For the Arduino 506 Raspberry Pi Base Unit — the Pi2Grover 507 The Four Types of Grove Connectors 509 The Four Types of Grove Signals 510 Grove digital — All about those 1’s and 0’s 510 Grove analog: When 1’s and 0’s aren’t enough 511 Grove UART (or serial) — Bit by bit transmission 512 Grove I2C — Using I2C to make sense of the world 514 Using Grove Cables to Get Connected 516 Grove Patch Cables 516 Chapter 3 Sensing the World with Python: The World of I2C 522 Understanding I2C 523 Exploring I2C on the Raspberry Pi 524 Talking to I2C devices with Python 525 Reading temperature and humidity from an I2C device using Python 528 Breaking down the program 531 A Fun Experiment for Measuring Oxygen and a Flame 534 Analog-to-digital converters (ADC) 535 The Grove oxygen sensor 536 Hooking up the oxygen experiment 537 Breaking down the code 539 Building a Dashboard on Your Phone Using Blynk and Python 542 HDC1080 temperature and humidity sensor redux 542 How to add the Blynk dashboard 544 The modified temperatureTest.py software for the Blynk app 548 Breaking down the code 550 Where to Go from Here 553 Chapter 4 Making Things Move with Python 554 Exploring Electric Motors 555 Small DC motors 555 Servo motors 556 Stepper motors 556 Controlling Motors with a Computer 557 Python and DC Motors 557 Python and running a servo motor 565 Python and making a stepper motor step 571 Book 7 Building Robots with Python 582 Chapter 1 Introduction to Robotics 584 A Robot Is Not Always like a Human 584 Not Every Robot Has Arms or Wheels 585 The Wilkinson Bread-Making Robot 586 Baxter the Coffee-Making Robot 587 The Griffin Bluetooth-enabled toaster 588 Understanding the Main Parts of a Robot 589 Computers 589 Motors and actuators 590 Communications 590 Sensors 590 Programming Robots 591 Chapter 2 Building Your First Python Robot 592 Introducing the Mars Rover PiCar-B 592 What you need for the build 593 Understanding the robot components 594 Assembling the Robot 603 Calibrating your servos 605 Running tests on your rover in Python 608 Installing software for the CarPi-B Python test 608 The PiCar-B Python test code 609 Pi camera video testing 609 Chapter 3 Programming Your Robot Rover in Python 612 Building a Simple High-Level Python Interface 612 The motorForward function 613 The wheelsLeft function 613 The wheelsPercent function 613 Making a Single Move with Python 614 Functions of the RobotInterface Class 615 Front LED functions 615 Pixel strip functions 617 Ultrasonic distance sensor function 618 Main motor functions 619 Servo functions 620 General servo function 623 The Python Robot Interface Test 623 Coordinating Motor Movements with Sensors 627 Making a Python Brain for Our Robot 630 A Better Robot Brain Architecture 637 Overview of the Included Adeept Software 638 Where to Go from Here? 639 Chapter 4 Using Artificial Intelligence in Robotics 640 This Chapter’s Project: Going to the Dogs 641 Setting Up the Project 641 Machine Learning Using TensorFlow 642 The code 644 Examining the code 646 The results 649 Testing the Trained Network 650 The code 651 Explaining the code 653 The results 654 Taking Cats and Dogs to Our Robot 657 The code 657 How it works 660 The results 660 Other Things You Can Do with AI Techniques and the Robot 662 Cat/Not Cat 662 Santa/Not Santa 663 Follow the ball 663 Using Alexa to control your robot 663 AI and the Future of Robotics 663 Index 664 EULA -1

Your one-stop resource on all things Python

Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes.

There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it's used in a variety of applications.

• Covers the basics of the language
• Explains its syntax through application in high-profile industries
• Shows how Python can be applied to projects in enterprise
• Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis

This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox.

Powerful and flexible, Python is one of the most popular programming languages in the world. It's got all the right stuff for the software driving the cutting-edge of the development world--machine learning, robotics, artificial intelligence, data science, etc. The good news is that it's also pretty straightforward to learn, with a simplified syntax, natural-language flow, and an amazingly supportive user community. The latest edition of Python All-in-One For Dummies gives you an inside look at the exciting possibilities offered in the Python world and provides a springboard to launch yourself into wherever you want your coding career to take you. These 7 straightforward and friendly mini-books assume the reader is a beginning programmer, and cover everything from the basic elements of Python code to introductions to the specific applications where you'll use it. Intended as a hands-on reference, the focus is on practice over theory, providing you with examples to follow as well as code for you to copy and start modifying in the "real world"--helping you get up and running in your area of interest almost right away. Your one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. • Covers the basics of the language • Explains its syntax through application in high-profile industries • Shows how Python can be applied to projects in enterprise • Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis • This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox.