Python Unit Test Automation, 2nd Edition
Learn how to automate unit tests of Python 3 with automation libraries, such as doctest, unittest, nose, nose2, pytest, and selenium. This book explores important concepts in software test automation and demonstrates how to automate, organize, and execute unit tests with Python. It also introduces readers to the concepts of web browser automation and logging. This new edition starts with an introduction to Python 3. Next, it covers doctest and pydoc. This is followed by a discussion on unittest, a framework that comes packaged with Python 3 itself. There is a dedicated section on creating test suites, followed by an explanation of how nose2 provides automatic test module discovery. Moving forward, you will learn about pytest, the most popular third-party library and testrunner for Python. You will see how to write and execute tests with pytest. You'll also learn to discover tests automatically with pytest. This edition features two brand new chapters, the first of which focuses o ...
Learn how to automate unit tests of Python 3 with automation libraries, such as doctest, unittest, nose, nose2, pytest, and selenium. This book explores important concepts in software test automation and demonstrates how to automate, organize, and execute unit tests with Python. It also introduces readers to the concepts of web browser automation and logging. This new edition starts with an introduction to Python 3. Next, it covers doctest and pydoc. This is followed by a discussion on unittest, a framework that comes packaged with Python 3 itself. There is a dedicated section on creating test suites, followed by an explanation of how nose2 provides automatic test module discovery. Moving forward, you will learn about pytest, the most popular third-party library and testrunner for Python. You will see how to write and execute tests with pytest. You'll also learn to discover tests automatically with pytest. This edition features two brand new chapters, the first of which focuses o ...
Human-Computer Interaction in Game Development with Python
Deepen your understanding of human-computer interaction (HCI) in game development and learn how to develop video games that grab players and don't let them go. This book explores HCI design in computer games to maximize collaborative and interactive functions. You'll first gain a basic introduction to fundamental concepts and practices of HCI before diving into the fundamental concepts of game interface design and technology. You'll learn how to design a gaming interface through practical examples using Python. This is followed by a brief look at how HCI can offer immersive gaming experiences for players and a review of key elements such as interface, usability, user-centered design, and user interface in terms of efficacy. You will also learn how to implement usability aspects in gaming interfaces with examples using Python. Additionally, the book discusses major challenges that game publishers and developers face, and how they can be resolved using HCI techniques. The questio ...
Deepen your understanding of human-computer interaction (HCI) in game development and learn how to develop video games that grab players and don't let them go. This book explores HCI design in computer games to maximize collaborative and interactive functions. You'll first gain a basic introduction to fundamental concepts and practices of HCI before diving into the fundamental concepts of game interface design and technology. You'll learn how to design a gaming interface through practical examples using Python. This is followed by a brief look at how HCI can offer immersive gaming experiences for players and a review of key elements such as interface, usability, user-centered design, and user interface in terms of efficacy. You will also learn how to implement usability aspects in gaming interfaces with examples using Python. Additionally, the book discusses major challenges that game publishers and developers face, and how they can be resolved using HCI techniques. The questio ...
Introduction to Scientific Programming with Python
This open book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies. ...
This open book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies. ...
3D Deep Learning with Python
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
With this hands-on guide to 3D deep learning, developers working with 3D computer vision will be able to put their knowledge to work and get up and running in no time. Complete with step-by-step explanations of essential concepts and practical examples, this book lets you explore and gain a thorough understanding of state-of-the-art 3D deep learning. You'll see how to use PyTorch3D for basic 3D mesh and point cloud data processing, including loading and saving ply and obj files, projecting 3D points into camera coordination using perspective camera models or orthographic camera models, rendering point clouds and meshes to images, and much more. As you implement some of the latest 3D deep learning algorithms, such as differential rendering, Nerf, synsin, and mesh RCNN, you'll realize how coding for these deep learning models becomes easier using the PyTorch3D library. By the end of this deep learning book, you'll be ready to implement your own 3D deep learning models confidently. ...
Mastering Financial Pattern Recognition
Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and back-test the profitability of candlestick patterns. Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on book, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before. ...
Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers, quants, strategists, and analysts how to use Python to recognize, scan, trade, and back-test the profitability of candlestick patterns. Financial author, trading consultant, and institutional market strategist Sofien Kaabar shows you how to create a candlestick scanner and indicator so you can compare the profitability of these patterns. With this hands-on book, you'll also explore a new type of charting system similar to candlesticks, as well as new patterns that have never been presented before. ...
Create Graphical User Interfaces with Python
Add buttons, boxes, pictures and colours and more to your Python programs using the guizero library, which is quick, accessible, and understandable for all. This 156-page book is suitable for everyone, from beginners to experienced Python programmers who want to explore graphical user interfaces (GUIs). There are ten fun projects for you to create, including a painting program, an emoji match game, and a stop-motion animation creator. - Create games and fun Python programs; - Learn how to create your own graphical user interfaces; - Use windows, text boxes, buttons, images, and more; - Learn about event-based programming; - Explore good (and bad) user interface design. ...
Add buttons, boxes, pictures and colours and more to your Python programs using the guizero library, which is quick, accessible, and understandable for all. This 156-page book is suitable for everyone, from beginners to experienced Python programmers who want to explore graphical user interfaces (GUIs). There are ten fun projects for you to create, including a painting program, an emoji match game, and a stop-motion animation creator. - Create games and fun Python programs; - Learn how to create your own graphical user interfaces; - Use windows, text boxes, buttons, images, and more; - Learn about event-based programming; - Explore good (and bad) user interface design. ...
Advanced Data Analytics Using Python, 2nd Edition
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Understand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment. Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpa ...
Think Python
If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language one step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. Through exercises in each chapter, you'll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. ...
If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language one step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. Through exercises in each chapter, you'll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. ...
Bioinformatics Programming Using Python
Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics - researchers, support staff, students, and software developers interested in writing bioinformatics applications. ...
Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you'll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming. Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics - researchers, support staff, students, and software developers interested in writing bioinformatics applications. ...
Think Bayes
If you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. ...
If you know how to program with Python and also know a little about probability, you're ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you'll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. ...