Python All-In-One for Dummies

Python All-In-One for Dummies

Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfec...

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Detalles Bibliográficos
Autor principal: Simpson, Alan (-)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated 2024.
Edición:3rd ed
Colección:--For dummies.
Materias:
Python (Computer program language)
Computer programming.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009811317506719
Tabla de Contenidos:
  • Intro
  • Title Page
  • Copyright Page
  • Table of Contents
  • Introduction
  • About This Book
  • Foolish Assumptions
  • What to Buy to Do the Projects in This Book
  • Icons Used in This Book
  • Beyond the Book
  • Where to Go from Here
  • Book 1 Getting Started
  • Chapter 1 Starting with Python
  • Why Python Is Hot
  • Choosing the Right Python
  • Tools for Success
  • Installing Python and VS Code
  • Installing the Python extension
  • Letting AI write your Python code
  • Using GitHub Copilot
  • Using Jupyter Notebook for Coding
  • Chapter 2 Using Interactive Mode, Getting Help, and Writing Apps
  • Using Python's Interactive Mode
  • Opening Terminal
  • Getting your Python version
  • Going into the Python Interpreter
  • Entering commands
  • Using Python's built-in help
  • Exiting interactive help
  • Searching for specific help topics online
  • Lots of free cheat sheets
  • Creating a Folder for Your Python Code
  • Typing, Editing, and Debugging Python Code
  • Writing Python code
  • Saving your code
  • Running Python in VS Code
  • Learning simple debugging
  • Closing a File
  • Writing Code in a Jupyter Notebook
  • Creating a folder for Jupyter Notebooks
  • Creating and saving a Jupyter notebook
  • Typing and running code in a notebook
  • Chapter 3 Python Elements and Syntax
  • The Zen of Python
  • Introducing Object-Oriented Programming
  • Discovering Why Indentations Count, Big Time
  • Using Python Modules
  • Understanding the syntax for importing modules
  • Using an alias with modules
  • Chapter 4 Building Your First Python Application
  • Opening the Python App File
  • Typing and Using Python Comments
  • Understanding Python Data Types
  • Numbers
  • Integers
  • Floats
  • Complex numbers
  • Words (strings)
  • Booleans
  • Working with Python Operators
  • Arithmetic operators
  • Comparison operators
  • Boolean operators
  • Creating and Using Variables.
  • Creating valid variable names
  • Creating variables in code
  • Manipulating variables
  • Saving your work
  • Running your Python app in VS Code
  • Understanding What Syntax Is and Why It Matters
  • Book 2 Understanding Python Building Blocks
  • Chapter 1 Working with Numbers, Text, and Dates
  • Calculating Numbers with Functions
  • Still More Math Functions
  • Formatting Numbers
  • Formatting with f-strings
  • Showing dollar amounts
  • Formatting percent numbers
  • Making multiline format strings
  • Formatting width and alignment
  • Grappling with Weirder Numbers
  • Binary, octal, and hexadecimal numbers
  • Complex numbers
  • Manipulating Strings
  • Concatenating strings
  • Getting the length of a string
  • Working with common string operators
  • Manipulating strings with methods
  • Uncovering Dates and Times
  • Working with dates
  • Working with times
  • Calculating timespans
  • Accounting for Time Zones
  • Working with Time Zones
  • Chapter 2 Controlling the Action
  • Main Operators for Controlling the Action
  • Making Decisions with if
  • Adding else to your if logic
  • Handling multiple else statements with elif
  • Ternary operations
  • Repeating a Process with for
  • Looping through numbers in a range
  • Looping through a string
  • Looping through a list
  • Bailing out of a loop
  • Looping with continue
  • Nesting loops
  • Looping with while
  • Starting while loops over with continue
  • Breaking while loops with break
  • Chapter 3 Speeding Along with Lists and Tuples
  • Defining and Using Lists
  • Referencing list items by position
  • Looping through a list
  • Seeing whether a list contains an item
  • Getting the length of a list
  • Adding an item to the end of a list
  • Inserting an item into a list
  • Changing an item in a list
  • Combining lists
  • Removing list items
  • Clearing out a list
  • Counting how many times an item appears in a list.
  • Finding a list item's index
  • Alphabetizing and sorting lists
  • Reversing a list
  • Copying a list
  • Using List Comprehension
  • What's a Tuple and Who Cares?
  • Working with Sets
  • Chapter 4 Cruising Massive Data with Dictionaries
  • Understanding Data Dictionaries
  • Creating a Dictionary
  • Accessing dictionary data
  • Getting the length of a dictionary
  • Seeing whether a key exists in a dictionary
  • Getting dictionary data with get()
  • Changing the value of a key
  • Adding or changing dictionary data
  • Looping through a Dictionary
  • Dictionary Methods
  • Copying a Dictionary
  • Deleting Dictionary Items
  • Having Fun with Multi-Key Dictionaries
  • Using the mysterious fromkeys and setdefault methods
  • Nesting dictionaries
  • Creating a dictionary from list comprehension
  • Chapter 5 Wrangling Bigger Chunks of Code
  • Creating a Function
  • Commenting a Function
  • Passing Information to a Function
  • Defining optional parameters with defaults
  • Passing multiple values to a function
  • Using keyword arguments (kwargs)
  • Passing multiple values in a list
  • Passing in an arbitrary number of arguments
  • Returning Values from Functions
  • Unmasking Anonymous Functions
  • Chapter 6 Doing Python with Class
  • Mastering Classes and Objects
  • Creating a Class
  • Creating an Instance from a Class
  • Giving an Object Its Attributes
  • Creating an instance from a class
  • Changing the value of an attribute
  • Defining attributes with default values
  • Giving a Class Methods
  • Passing parameters to methods
  • Calling a class method by class name
  • Using class variables
  • Using class methods
  • Using static methods
  • Understanding Class Inheritance
  • Creating the base (main) class
  • Defining a subclass
  • Overriding a default value from a subclass
  • Adding extra parameters from a subclass
  • Calling a base class method.
  • Using the same name twice
  • Chapter 7 Sidestepping Errors
  • Understanding Exceptions
  • Handling Errors Gracefully
  • Being Specific about Exceptions
  • Keeping Your App from Crashing
  • Adding an else to the Mix
  • Using try . . . except . . . else . . . finally
  • Raising Your Own Exceptions
  • Book 3 Working with Libraries
  • Chapter 1 Working with External Files
  • Understanding Text and Binary Files
  • Opening and Closing Files
  • Reading a File's Contents
  • Looping through a File
  • Looping with readlines()
  • Looping with readline()
  • Appending versus overwriting files
  • Using tell() to determine the pointer location
  • Moving the pointer with seek()
  • Reading and Copying a Binary File
  • Conquering CSV Files
  • Opening a CSV file
  • Converting strings
  • Converting to integers
  • Converting to date
  • Converting to Boolean
  • Converting to floats
  • Converting from CSV to Objects and Dictionaries
  • Importing CSV to Python objects
  • Importing CSV to Python dictionaries
  • Chapter 2 Juggling JSON Data
  • Organizing JSON Data
  • Understanding Serialization
  • Loading Data from JSON Files
  • Converting an Excel date to a JSON date
  • Looping through a keyed JSON file
  • Converting Firebase timestamps to Python dates
  • Loading unkeyed JSON from a Python string
  • Loading keyed JSON data from a Python string
  • Changing JSON data
  • Removing data from a dictionary
  • Dumping Python Data to JSON
  • Chapter 3 Interacting with the Internet
  • Seeing How the Web Works
  • Understanding the mysterious URL
  • Exposing the HTTP headers
  • Opening a URL from Python
  • Posting to the web with Python
  • Scraping the web with Python
  • Parsing part of a page
  • Storing the parsed content
  • Saving scraped data to a JSON file
  • Saving scraped data to a CSV file
  • Chapter 4 Libraries, Packages, and Modules
  • Understanding the Python Standard Library.
  • Using the dir() function
  • Using the help() function
  • Exploring built-in functions
  • Exploring Python Packages
  • Importing Python Modules
  • Making Your Own Modules
  • Managing Virtual Environments
  • Creating a virtual environment
  • Activating a virtual environment
  • Creating a requirements.txt file
  • Deactivating a virtual environment
  • Book 4 Using Artificial Intelligence
  • Chapter 1 Demystifying Artificial Intelligence
  • AI Is a Collection of Techniques
  • Neural networks
  • Machine learning
  • TensorFlow - A framework for deep learning
  • Current Limitations of AI
  • Chapter 2 Building a Neural Network
  • Understanding Neural Networks
  • Layers of neurons
  • Weights and biases
  • The activation function
  • Loss function
  • Building a Simple Neural Network in Python
  • The neural-net Python code
  • Breaking down the code
  • Running the neural-network code
  • Using TensorFlow for the same neural network
  • Installing the TensorFlow Python library
  • Building a Python Neural Network in TensorFlow
  • Loading your data
  • Defining your neural-network model and layers
  • Compiling your model
  • Fitting and training your model
  • Evaluating the model
  • Breaking down the code
  • Step 1: Load and format your data
  • Step 2: Define your neural network model and layers
  • Step 3: Compile your model
  • Step 4: Fit and train your model
  • Step 5: Evaluate the model
  • Checking the results
  • Changing to a three-layer neural network in TensorFlow and Keras
  • Chapter 3 Doing Machine Learning
  • Learning by Looking for Solutions in All the Wrong Places
  • Creating a Machine-Learning Network for Detecting Clothes Types
  • Setting up the software environment
  • Getting the data from the Fashion-MNIST dataset
  • Training the network
  • Testing the network
  • Breaking down the code
  • Step 1: Load and format the data.
  • Step 2: Define the neural network model and layers.

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