Python All-in-One For Dummies
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Python All-in-One For Dummies, Wiley
Von John C. Shovic, Alan Simpson, im heise Shop in digitaler Fassung erhältlich
Von John C. Shovic, Alan Simpson, im heise Shop in digitaler Fassung erhältlich
Artikel-Beschreibung
THE ONE-STOP RESOURCE FOR ALL YOUR PYTHON QUERIESPowerful 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. This means you'll be finishing off your first app or building and remote-controlling your own robot much faster than you can believe.
* Get a thorough grounding in the language basics
* Learn how the syntax is applied in high-profile industries
* Apply Python to projects in enterprise
* Find out how Python can get you into hot careers in AI, big data, and more
Whether you're a newbie coder or just want to add Python to your magic box of tricks, this is the perfect, practical introduction—and one you'll return to as you grow your career.
JOHN SHOVIC, PHD, is a computer science faculty member at the University of Idaho specializing in robotics and artificial intelligence.
ALAN SIMPSON is a web development professional who has published more than 100 articles and books on technology.
INTRODUCTION 1
About This Book 1
Foolish Assumptions 2
What to Buy 2
Icons Used in This Book 4
Beyond the Book 4
Where to Go from Here 5
BOOK 1: GETTING STARTED 7
CHAPTER 1: STARTING WITH PYTHON 9
Why Python is Hot 10
Choosing the Right Python 11
Tools for Success 13
Introducing Anaconda and VS Code 14
Installing Anaconda and VS Code 15
Writing Python in VS Code 19
Choosing your Python interpreter 21
Writing some Python code 22
Getting back to VS Code Python 23
Using Jupyter Notebook for Coding 23
CHAPTER 2: INTERACTIVE MODE, GETTING HELP, AND WRITING APPS 29
Using Python’s Interactive Mode 29
Opening Terminal 30
Getting your Python version 32
Going into the Python Interpreter 32
Entering commands 33
Using Python’s built-in help 33
Exiting interactive help 35
Searching for specific help topics online 36
Lots of free cheat sheets 36
Creating a Python Development Workspace 37
Creating a Folder for Your Python Code 39
Typing, Editing, and Debugging Python Code 41
Writing Python code 42
Saving your code 43
Running Python in VS Code 44
Learning simple debugging 45
Using the VS Code Python debugger 46
Writing Code in a Jupyter Notebook 47
Creating a folder for Jupyter Notebook 47
Creating and saving a Jupyter notebook 48
Typing and running code in a notebook 49
Adding Markdown text 49
Saving and opening notebooks 51
CHAPTER 3: PYTHON ELEMENTS AND SYNTAX 53
The Zen of Python 53
Introducing Object-Oriented Programming 56
Discovering Why Indentations Count, Big Time 57
Using Python Modules 59
Understanding the syntax for importing modules 61
Using an alias with modules 62
CHAPTER 4: BUILDING YOUR FIRST PYTHON APPLICATION 63
Opening the Python App File 64
Typing and Using Python Comments 64
Understanding Python Data Types 66
Numbers 67
Words (strings) 68
Booleans 70
Working with Python Operators 71
Arithmetic operators 71
Comparison operators 72
Boolean operators 73
Creating and Using Variables 74
Creating valid variable names 75
Creating variables in code 75
Manipulating variables 76
Saving your work 78
Running your Python app in VS Code 78
Understanding What Syntax is and Why It Matters 79
Putting Code Together 84
BOOK 2: UNDERSTANDING PYTHON BUILDING BLOCKS 85
CHAPTER 1: WORKING WITH NUMBERS, TEXT, AND DATES 87
Calculating Numbers with Functions 87
Still More Math Functions 90
Formatting Numbers 93
Formatting with f-strings 93
Showing dollar amounts 94
Formatting percent numbers 95
Making multiline format strings 97
Formatting width and alignment 98
Grappling with Weirder Numbers 100
Binary, octal, and hexadecimal numbers 100
Complex numbers 101
Manipulating Strings 103
Concatenating strings 103
Getting the length of a string 104
Working with common string operators 105
Manipulating strings with methods 107
Uncovering Dates and Times 110
Working with dates 110
Working with times 114
Calculating timespans 116
Accounting for Time Zones 120
Working with Time Zones 122
CHAPTER 2: CONTROLLING THE ACTION 127
Main Operators for Controlling the Action 127
Making Decisions with if 129
Adding else to your if logic 132
Handling multiple else statements with elif 133
Ternary operations 135
Repeating a Process with for 136
Looping through numbers in a range 136
Looping through a string 138
Looping through a list 139
Bailing out of a loop 140
Looping with continue 141
Nesting loops 142
Looping with while 143
Starting while loops over with continue 145
Breaking while loops with break 146
CHAPTER 3: SPEEDING ALONG WITH LISTS AND TUPLES 149
Defining and Using Lists 149
Referencing list items by position 150
Looping through a list 151
Seeing whether a list contains an item 152
Getting the length of a list 153
Adding an item to the end of a list 153
Inserting an item into a list 154
Changing an item in a list 155
Combining lists 155
Removing list items 156
Clearing out a list 158
Counting how many times an item appears in a list 159
Finding an list item’s index 160
Alphabetizing and sorting lists 161
Reversing a list 164
Copying a list 164
What’s a Tuple and Who Cares? 165
Working with Sets 167
CHAPTER 4: CRUISING MASSIVE DATA WITH DICTIONARIES 171
Understanding Data Dictionaries 172
Creating a Data Dictionary 174
Accessing dictionary data 175
Getting the length of a dictionary 177
Seeing whether a key exists in a dictionary 177
Getting dictionary data with get() 178
Changing the value of a key 179
Adding or changing dictionary data 180
Looping through a Dictionary 182
Data Dictionary Methods 183
Copying a Dictionary 184
Deleting Dictionary Items 185
Having Fun with Multi-Key Dictionaries 188
Using the mysterious fromkeys and setdefault methods 190
Nesting dictionaries 193
CHAPTER 5: WRANGLING BIGGER CHUNKS OF CODE 195
Creating a Function 196
Commenting a Function 197
Passing Information to a Function 198
Defining optional parameters with defaults 200
Passing multiple values to a function 201
Using keyword arguments (kwargs) 203
Passing multiple values in a list 205
Passing in an arbitrary number of arguments 207
Returning Values from Functions 208
Unmasking Anonymous Functions 209
CHAPTER 6: DOING PYTHON WITH CLASS 217
Mastering Classes and Objects 217
Creating a Class 220
Creating an Instance from a Class 221
Giving an Object Its Attributes 222
Creating an instance from a class 223
Changing the value of an attribute 226
Defining attributes with default values 227
Giving a Class Methods 228
Passing parameters to methods 230
Calling a class method by class name 231
Using class variables 232
Using class methods 234
Using static methods 236
Understanding Class Inheritance 238
Creating the base (main) class 240
Defining a subclass 241
Overriding a default value from a subclass 243
Adding extra parameters from a subclass 243
Calling a base class method 246
Using the same name twice 247
CHAPTER 7: SIDESTEPPING ERRORS 251
Understanding Exceptions 252
Handling Errors Gracefully 254
Being Specific about Exceptions 255
Keeping Your App from Crashing 257
Adding an else to the Mix 259
Using try except else finally 261
Raising Your Own Exceptions 263
BOOK 3: WORKING WITH LIBRARIES 269
CHAPTER 1: WORKING WITH EXTERNAL FILES 271
Understanding Text and Binary Files 271
Opening and Closing Files 273
Reading a File’s Contents 279
Looping through a File 281
Looping with readlines() 281
Looping with readline() 283
Appending versus overwriting files 284
Using tell() to determine the pointer location 285
Moving the pointer with seek() 286
Reading and Copying a Binary File 287
Conquering CSV Files 290
Opening a CSV file 292
Converting strings 293
Converting to integers 295
Converting to date 295
Converting to Boolean 297
Converting to floats 297
Converting from CSV to Objects and Dictionaries 299
Importing CSV to Python objects 300
Importing CSV to Python dictionaries 303
CHAPTER 2: JUGGLING JSON DATA 307
Organizing JSON Data 307
Understanding Serialization 310
Loading Data from JSON Files 312
Converting an Excel date to a JSON date 313
Looping through a keyed JSON file 314
Converting Firebase timestamps to Python dates 317
Loading unkeyed JSON from a Python string 318
Loading keyed JSON from a Python string 319
Changing JSON data 320
Removing data from a dictionary 321
Dumping Python Data to JSON 322
CHAPTER 3: INTERACTING WITH THE INTERNET 327
Seeing How the Web Works 327
Understanding the mysterious URL 328
Exposing the HTTP headers 329
Opening a URL from Python 331
Posting to the web with Python 333
Scraping the web with Python 334
Parsing part of a page 337
Storing the parsed content 337
Saving scraped data to a JSON file 340
Saving scraped data to a CSV file 341
CHAPTER 4: LIBRARIES, PACKAGES, AND MODULES 343
Understanding the Python Standard Library 343
Using the dir() function 344
Using the help() function 345
Exploring built-in functions 347
Exploring Python Packages 347
Importing Python Modules 349
Making Your Own Modules 352
BOOK 4: USING ARTIFICIAL INTELLIGENCE 357
CHAPTER 1: EXPLORING ARTIFICIAL INTELLIGENCE 359
AI is a Collection of Techniques 360
Neural networks 360
Machine learning 365
TensorFlow — A framework for deep learning 366
Current Limitations of AI 367
CHAPTER 2: BUILDING A NEURAL NETWORK 369
Understanding Neural Networks 370
Layers of neurons 371
Weights and biases 372
The activation function 373
Loss function 373
Building a Simple Neural Network in Python 374
The neural-net Python code 375
Using TensorFlow for the same neural network 385
Installing the TensorFlow Python library 386
Building a Python Neural Network in TensorFlow 387
Loading your data 388
Defining your neural-network model and layers 388
Compiling your model 388
Fitting and training your model 388
Evaluating the model 388
Breaking down the code 390
Checking the results 392
Changing to a three-layer neural network in TensorFlow and Keras 395
CHAPTER 3: DOING MACHINE LEARNING 399
Learning by Looking for Solutions in All the Wrong Places 400
Creating a Machine-Learning Network for Detecting Clothes Types 401
Setting up the software environment 402
Getting the data from the Fashion-MNIST dataset 403
Training the network 404
Testing our network 404
Breaking down the code 405
Results of the training and evaluation 407
Testing a single test image 408
Testing on external pictures 409
The results, round 1 411
The CNN model code 412
The results, round 2 414
Visualizing with MatPlotLib 415
Learning More Machine Learning 419
CHAPTER 4: EXPLORING AI 421
Limitations of the Raspberry Pi and AI 421
Adding Hardware AI to the Raspberry Pi 423
AI in the Cloud 425
Google Cloud 427
Amazon Web Services 427
IBM Cloud 427
Microsoft Azure 428
AI on a Graphics Card 428
Where to Go for More AI Fun in Python 430
BOOK 5: DOING DATA SCIENCE 433
CHAPTER 1: UNDERSTANDING THE FIVE AREAS OF DATA SCIENCE 435
Working with Big, Big Data 436
Volume 436
Variety 437
Velocity 437
Managing volume, variety, and velocity 437
Cooking with Gas: The Five-Step Process of Data Science 438
Capturing the data 438
Processing the data 438
Analyzing the data 439
Communicating the results 440
Maintaining the data 440
CHAPTER 2: EXPLORING BIG DATA 441
Introducing NumPy, Pandas, and MatPlotLib 442
NumPy 442
Pandas 443
MatPlotLib 444
Doing Your First Data Science Project 444
Diamonds are a data scientist’s best friend 444
Breaking down the code 447
Visualizing the data with MatPlotLib 449
CHAPTER 3: USING BIG DATA FROM GOOGLE CLOUD 457
What is Big Data? 457
Understanding Google Cloud and BigQuery 458
Google Cloud Platform 458
BigQuery from Google 458
Computer security on the cloud 459
Signing up for BigQuery 460
Reading the Medicare Big Data 460
Setting up your project and authentication 460
The first big-data code 463
Breaking down the code 466
Doing a bit of analysis 467
Payment percent by state 470
Now some visualization 471
Looking for the Most Polluted City in the World on an Hourly Basis 473
BOOK 6: TALKING TO HARDWARE 475
CHAPTER 1: INTRODUCING PHYSICAL COMPUTING 477
Physical Computing is Fun 478
What is a Raspberry Pi? 478
Building Projects That Move and Sense the Environment 480
Sensing the Environment with the Raspberry Pi 482
GPIO pins 482
GPIO libraries 482
Buying and assembling the hardware for “Hello World” 483
Controlling an LED with Python 487
But Wait, There’s More 489
CHAPTER 2: NO SOLDERING! USING GROVE CONNECTORS FOR BUILDING 493
Working with the Grove System 494
Selecting a Grove base unit 494
Error-proofing with a Grove connector 496
Grove Connectors 498
Grove digital — All about those 1s and 0s 498
Grove analog: When 1s and 0s aren’t enough 499
Grove UART (or serial) — bit-by-bit transmission 500
Grove I2C — Using I2C to make sense of the world 502
Connecting with Grove Cables 503
An example of the power of the patch! 505
Second example: The Adafruit Ultimate GPS 506
CHAPTER 3: SENSING THE WORLD 509
Understanding I2C 509
Enabling I2C on the Raspberry Pi 511
The hardware for reading temperature and humidity 512
Reading temperature and humidity from an I2C device using Python 515
Breaking down the program 518
Measuring Oxygen and a Flame 521
Analog-to-digital converters (ADC) 522
The Grove oxygen sensor 522
Hooking up the oxygen experiment 524
Breaking down the code 527
Interpreting the results 528
Building a Dashboard on Your Phone with Blynk 530
HDC1080 temperature and humidity sensor redux 530
Adding the Blynk dashboard 531
The modified temperatureTest.py software for the Blynk app 534
Breaking down the code 536
Where to Go from Here 539
CHAPTER 4: MAKING THINGS MOVE 541
Exploring Electric Motors 541
Small DC motors 542
Servo motors 543
Stepper motors 543
Controlling a DC Motor 544
Grove I2C motor driver 545
Python DC motor software 548
Running a Servo Motor 551
Python servo software 555
Breaking down the code 556
Making a Stepper Motor Step 558
Python stepper software 566
Breaking down the code 567
BOOK 7: BUILDING ROBOTS 569
CHAPTER 1: INTRODUCING ROBOTICS 571
A Robot is Not Always Like a Human 571
Not Every Robot Has Arms or Wheels 572
The Wilkinson bread-making robot 573
Baxter, the coffee-making robot 574
The Griffin Bluetooth-enabled toaster 575
Understanding the Main Parts of a Robot 576
Computers 576
Motors and actuators 577
Communications 577
Sensors 577
Programming Robots 578
CHAPTER 2: BUILDING YOUR FIRST PYTHON ROBOT 579
Introducing the Mars Rover PiCar-B 580
What you need for the build 580
Understanding the robot components 581
Assembling the Robot 590
Testing Your Robot 592
Calibrating your servos 592
Preparing for running tests on your rover in Python 595
Installing software for the PiCar-B Python test 595
The PiCar-B Python test code 596
Pi camera video testing 597
CHAPTER 3: PROGRAMMING YOUR ROBOT ROVER 601
Building a Simple, High-Level Python Interface 601
The motorForward() function 602
The wheelsLeft function() 602
The wheelsPercent function() 603
Making a Single Move with Python 603
Functions of the RobotInterface Class 604
Front LED functions 605
Pixel strip functions 606
Ultrasonic distance sensor function 608
Main motor functions 608
Servo functions 609
General servo function 613
The Python Robot Interface Test 613
Coordinating Motor Movements with Sensors 617
Making a Python Brain for Our Robot 621
Overview of the Included Adeept Software 628
Where to Go from Here 629
CHAPTER 4: USING ARTIFICIAL INTELLIGENCE IN ROBOTICS 631
This Chapter’s Projects: Going to the Dogs 632
Setting Up the First Project 632
Machine Learning Using TensorFlow 633
The code 635
How the code works 637
The results 640
Testing the Trained Network 642
The code 642
How the code works 644
The results 646
Taking Cats and Dogs to Our Robot 648
The code 649
How it works 652
The results 652
Setting Up the Second Project 654
The FindAndChaseTheBall.py Python Program 655
The structure of the program 656
The ultrasonic thread 656
The video display thread 657
The OpenCV frame analyzer thread 657
The Main Program 661
The program’s configuration 661
Setting the ball’s color 662
Chasing the ball 664
Program notes 664
AI and the Future of Robotics 666
Index 667
Artikel-Details
Anbieter:
Wiley
Autor:
Alan Simpson, John C. Shovic
Artikelnummer:
9781119787624
Veröffentlicht:
29.03.2021
Seitenanzahl:
720
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