ENGLISH

Super Pythonista: The Ultimate Guide to Python Programming from Beginner to Advanced, and Far Beyond

Book information

Publisher
Independently published
Year
2022
Language
english
Format
PDF
Filesize
18 MB (18425361 bytes)
Pages
324\324
Time added
2023-02-07 11:37:55

Description

nside these pages, you'll find a comprehensive step-by-step guide to the Python programming language, with clear explanations and simple code examples to help you fully understand each concept. We'll start with the basics, covering topics like data types, variables, and control structures, and then move on to more advanced concepts like object-oriented programming, data manipulation, and working with external libraries, as well as many other advanced concepts. But that’s not all. We then go on to get applying your newfound advanced Python skills to solve some of the worlds greatest programming challenges, including: Image processing Sound processing Video processing Desktop application development Web Development Web Scraping Data Analysis Big data processing Cloud computing Machine learning Natural language processing Game development Excel integration Automation Robotics IoT Virtual reality These aren’t areas we will simply skip over. You will get the clear instruction and code examples you need to truly get started programming in these specialist applications of the Python language showing you’re the true power and diversity of the language itself. Throughout the book, you'll also find practical examples and project ideas to help you re-enforce your newfound knowledge and build real-world enterprise-grade code. By the time you finish this book, you'll have advanced skills in Python programming and be well on your way to becoming a "Super Pythonista"! Table of Contents Introduction Chapter 1: Introduction to programming and Python What is programming? What is Python? Why learn Python? Chapter 2: Setting up a development environment Why do you need a development environment? How to set up a development environment How to set up a development environment in PyCharm How to set up a development environment in VS Code Chapter 3: Basic concepts and syntax of Python Variables Data types Operators Control statements Chapter 4: Working with lists, tuples, and dictionaries Lists and list comprehensions Indexing and slicing lists Modifying lists Sorting lists Tuples and tuple manipulation Dictionaries and dictionary manipulation Chapter 5: Working with data types in Python Working with variables Working with numbers Working with strings Working with lists Chapter 6: Control structures in Python Using if statements Using for loops Using while loops Using try and except statements Using with statements Chapter 7: Working with files and data input/output Reading and writing text files Working with file paths and modes Reading and writing files line by line Working with CSV and JSON data What is CSV data? Working with CSV data in Python (using the csv module) What is JSON data? Working with JSON data in Python Database connectivity (SQLite, MySQL, etc.) What is a database? Connecting to and querying a database in Python Chapter 8: Writing and using functions in Python Defining a function Calling a function Returning a value Scope Argument default values Variable number of arguments How to call a function in Python Using keyword arguments in Python Using lambda functions in Python Chapter 9: Working with modules in Python What are modules? Importing specific names from a module Renaming imported names Importing all names from a module Creating and using your own modules Chapter 10: Object orientated programming (OOP) What is object-oriented programming? Defining and using classes Creating and using objects Inheritance and polymorphism Chapter 11: Python libraries and frameworks Introduction to libraries and frameworks What are libraries and frameworks? How to find and install libraries and frameworks NumPy and Pandas for scientific computing and data analysis What is NumPy? What is Pandas? Using NumPy and Pandas for data manipulation and analysis Django for web development What is Django? Setting up a Django project Creating a web application with Django Other popular libraries and frameworks What is TensorFlow? What is Pygame? Using TensorFlow and Pygame in Python Chapter 12: Debugging and error handling in Python Common error types and how to handle them Using the built-in debugger (pdb) Debugging with third-party tools such as PyCharm and pdb++ Handling exceptions with try-except blocks Raising and handling custom exceptions Debugging and error handling best practices Chapter 13: Development Tools and Techniques Virtual Environments for Managing Packages and Dependencies Working with the Python Package Index (PyPI) Creating and Distributing Python Packages Using Continuous Integration and Deployment Tools Performance Optimization and Profiling Techniques Chapter 14: The Python Inspect Library Inspecting Modules and Classes Tips for Using the Inspect Library Chapter 15: Python and Optimization Linear Programming with Pulp and Pyomo Nonlinear Optimization with Scipy Global Optimization with DEAP and PyGMO Constraint Programming with Gurobi and Pyomo Advanced Optimization Techniques with Python Chapter 16: Advanced Python concepts and techniques Decorators and metaprogramming Generators and iterators Working Asynchronous programming with asyncio Working with sets, queues, and stacks Processing and manipulating data with Pandas Working with databases and SQL Web development with Flask Building and deploying web applications Regular expressions Chapter 17: Python and Image Processing Loading and Manipulating Images with Pillow and OpenCV Filtering and Enhancing Images with Scikit-image Extracting Features from Images with Scikit-image and OpenCV Advanced Image Processing Techniques with Python Chapter 18: Python and Audio Processing Loading and Manipulating Audio Files with Librosa and PyAudio Filtering and Enhancing Audio with Scikit-sound Extracting Features from Audio with Librosa and Scikit-sound Advanced Audio Processing Techniques with Python Chapter 19: Python and Video Processing Introduction to Video Processing with Python Loading and Manipulating Video Files with OpenCV and MoviePy Filtering and Enhancing Video with OpenCV and Scikit-video Extracting Features from Video with OpenCV and Scikit-video Advanced Video Processing Techniques with Python Chapter 20: Python and Desktop Applications Creating GUI Applications with PyGTK and PyQt Integrating with External Libraries and APIs Storing and Accessing Data in a Database Packaging and Distributing a Desktop Application Advanced Desktop Application Development Chapter 21: Python and Web Development Introduction to Web Development with Python Building a Web Server with Flask Working with Templates and Forms Integrating a Database with a Web Application Deploying a Web Application to a Hosting Provider Advanced Web Development Techniques with Django Building and Deploying a RESTful API with Flask-RESTful Chapter 22: Python and web scraping Introduction to web scraping with Python Using Beautiful Soup to parse HTML and XML Scraping dynamic websites with Selenium Handling cookies, headers, and authentication Scraping data from APIs and data streams Storing and processing scraped data Advanced web scraping techniques and best practices Chapter 23: Python and Data Analysis Working with Data Structures and Data Types in Python Loading and Cleaning Data Using Pandas Exploring and Visualizing Data with Matplotlib and Seaborn Performing Statistical Analysis with SciPy Working with Time Series Data Predictive Modeling and Machine Learning with scikit-learn Advanced Data Analysis Techniques with NumPy and Pandas Chapter 24: Python and big data processing Processing large datasets with Pandas and Dask Distributed computing with PySpark Integrating with Hadoop and other big data technologies Advanced big data processing techniques with PySpark and Dask Chapter 25: Python and Cloud Computing Deploying Python Applications to the Cloud Working with Cloud-Based Storage and Databases Scaling and Optimizing Applications in the Cloud Advanced Cloud Computing Techniques with Python Chapter 26: Python and Machine Learning Supervised Learning Algorithms Linear Regression Support Vector Machines (SVMs) Decision Trees Unsupervised Learning Algorithms Clustering Dimensionality Reduction Deep Learning with TensorFlow and Keras Evaluating and Optimizing Machine Learning Models Working with Real-World Data Sets and Projects Chapter 27: Python and natural language processing Preprocessing and cleaning text data Extracting features and creating a feature matrix Classification and clustering of text data Topic modeling and document summarization Advanced natural language processing Chapter 28: Python and game development Creating simple games with Pygame Handling user input and collision detection Animating and rendering graphics Creating levels and game mechanics Integrating sound and music Advanced game development techniques with Pygame Chapter 29: Python and Excel integration Reading and writing Excel files with Pandas and openpyxl Accessing and manipulating Excel data with xlwings Creating custom Excel functions (PyXLL) Advanced Excel integration techniques with Python Chapter 30: Python and automation Automating tasks with the subprocess module Controlling the mouse and keyboard with PyAutoGUI Automating web browsing with Selenium Integrating with external tools and platforms Advanced automation techniques with Python Chapter 31: Python and Robotics Robot Hardware Robot Software Robot Applications Advanced Robotics Techniques with Python Machine Learning and Artificial Intelligence Motion Planning and Control Perception Tasks Chapter 32: Python and IoT Connecting to and interacting with IoT devices Collecting and processing sensor data with Pandas and Dask Visualizing and reporting on IoT data with Matplotlib and Plotly Building and deploying IoT applications with Flask and AWS IoT Advanced IoT techniques with Python Chapter 33: Python and Virtual Reality Creating Virtual Environments with PyOpenGL and PyVR Rendering 3D Graphics with PyOpenGL and PyVR Creating Interactive Experiences with PyVR and PyOpenVR Integrating with VR Hardware and Platforms Advanced Virtual Reality Techniques with Python About the Author Index

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