Products related to Python:
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Electrodynamics Tutorials with Python Simulations
This book provides an accessible introduction to intermediate-level electrodynamics with computa- tional approaches to complement a traditional mathematical treatment of the subject.It covers key topics in electrodynamics, such as electromagnetic fields, forces, potentials, and waves as well as Special Theory of Relativity. Through intuition-building examples and visualizations in the Python programming language, it helps readers to develop technical computing skills in numerical and symbolic calculations, modeling and simulations, and visualizations.Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience. This book can serve as an electrodynamics textbook for undergraduate physics and engineering students in their second or third years, who are studying intermediate- or advanced-level electrodynamics and who want to learn techniques for scientific computing at the same time.This book will also appeal to computer science students who want to see how their computer programming skills may be applied to science, particularly to physics, without needing too much background physics knowledge. Key featuresMajor concepts in classical electrodynamics are introduced cohesively through computational and mathematical treatmentsComputational examples in Python programming language guide students on how to simulate and visualize electrodynamic principles and phenomena for themselves
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Thermal Physics Tutorials with Python Simulations
This book provides an accessible introduction to thermal physics with computational approaches that complement the traditional mathematical treatments of classical thermodynamics and statistical mechanics.It guides readers through visualizations and simulations in the Python programming language, helping them to develop their own technical computing skills (including numerical and symbolic calculations, optimizations, recursive operations, and visualizations).Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience. This book may serve as a thermal physics textbook for a semester-long undergraduate thermal physics course or may be used as a tutorial on scientific computing with focused examples from thermal physics.This book will also appeal to engineering students studying intermediate-level thermodynamics as well as computer science students looking to understand how to apply their computer programming skills to science. Key features Major concepts in thermal physics are introduced cohesively through computational and mathematical treatments. Computational examples in Python programming language guide students on how to simulate and visualize thermodynamic principles and processes for themselves.
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An Introduction to Scientific Computing with MATLAB® and Python Tutorials
This textbook is written for the first introductory course on scientific computing.It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems.It includes short Matlab and Python tutorials to quickly get students started on programming.It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing. This textbook gives a comprehensive and in-depth treatment of elementary numerical methods.It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions. •Where is the method applied?•How is the method developed?•How is the method implemented?•How well does the method work?The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks.The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.
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DevOps in Python : Infrastructure as Python
Take advantage of Python to automate complex systems with readable code.This new edition will help you move from operations/system administration into easy-to-learn coding. You'll start by writing command-line scripts and automating simple DevOps-style tasks followed by creating reliable and fast unit tests designed to avoid incidents caused by buggy automation.You’ll then move on to more advanced cases, like using Jupyter as an auditable remote-control panel and writing Ansible and Salt extensions. The updated information in this book covers best practices for deploying and updating Python applications.This includes Docker, modern Python packaging, and internal Python package repositories.You'll also see how to use the AWS API, and the Kubernetes API, and how to automate Docker container image building and running.Finally, you'll work with Terraform from Python to allow more flexible templating and customization of environments. What You'll LearnUnderstand operating system automation with PythonPackage Python applicationsUse Python as a DevOps consoleReview Cloud automation with PythonWho This Book Is ForDevOps engineer.Site Reliability Engineer, or similar (including Platform, Production, and Systems), and whose organization uses Python.
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What are some good book tutorials for Python?
Some good book tutorials for Python include "Python Crash Course" by Eric Matthes, which is great for beginners and covers the basics of Python programming. "Automate the Boring Stuff with Python" by Al Sweigart is another popular choice that focuses on practical projects and automating tasks. For more advanced users, "Fluent Python" by Luciano Ramalho provides in-depth coverage of Python's features and best practices. These books offer a comprehensive and hands-on approach to learning Python programming.
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Is there free hosting for Python websites?
Yes, there are several free hosting options available for Python websites. Platforms like Heroku, PythonAnywhere, and Google App Engine offer free hosting plans with certain limitations on resources and features. These free hosting options are a great way for developers to test and deploy their Python applications without incurring any costs. However, it's important to note that free hosting plans may have limitations and it's advisable to upgrade to a paid plan as the website grows in traffic and complexity.
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How can one control other Python programs with Python?
One can control other Python programs with Python by using the subprocess module, which allows you to spawn new processes, connect to their input/output/error pipes, and obtain their return codes. You can use the subprocess module to run other Python scripts or any other command line programs from within your Python program. Additionally, you can use libraries like os and sys to interact with the file system, environment variables, and command line arguments of other Python programs. Lastly, you can also use inter-process communication mechanisms like sockets, pipes, or shared memory to establish communication between different Python programs.
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'Python or Kotlin?'
Both Python and Kotlin are popular programming languages with their own strengths. Python is known for its simplicity and readability, making it a great choice for beginners and for tasks like data analysis, machine learning, and web development. On the other hand, Kotlin is a modern language that is fully interoperable with Java, making it a good choice for Android app development and backend services. Ultimately, the choice between Python and Kotlin depends on the specific requirements of the project and the developer's familiarity with the language.
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Python Swallowed Whole : Core Developers Define Python
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Python Distilled
Expert insight for modern Python (3.6+) coding from the author of Python Essential ReferencePython educator Dave Beazley’s concise handbook focuses on the essential core of the Python programming language, with code examples to illuminate how Python works and how to structure programs that can be more easily explained, tested, and debugged.Rather than trying to cover every possible feature and quirk of a 30-year-old language, this pragmatic guide provides a concise narrative related to fundamental programming topics that form the foundation for Python projects of any size includingData abstractionControl flowProgram structureFunctions: master functions and functional programming idiomsObjects: control objects and master the "protocols" that define their behaviorModules: plan for project growth by understanding modules and packagesGeneratorsClasses: understand classes from both high-level and technical perspectivesI/O handling: proper techniques and abstractionsDicts"This is a pragmatic book that presents some of the most important topics about the Python programming language in a concise form, designed to make it easier to find out the most relevant information bits in a context where resources abound and frequently are just too overwhelming."—Victor Domingos, Software Developer, Slim Business Solutions, The No Title® Tech Blog
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Python Challenge
Learn to program fast in 155 challenges, 53 examples and 85 pages.There's no substitute for practice when it comes to learning a new skill!Python syntax is simple to learn, but becoming an expert in writing programs to solve different kinds of problems takes a bit longer.That's why this book has a short explanation of each new statement or technique, followed by one or more examples and then loads of practice challenges.Some of the challenges will take you only a minute or two, using the Python Interactive window to try out new statements and get immediate results.As you get further into the book, you will be challenged to write programs to perform different kinds of tasks - for example to find the results of a calculation, write a program for a simplified cash machine, sort a list of items into alphabetical order, or to record data in a text file to be read, formatted, and printed.The programming solutions to some challenges have been helpfully simplified for an inexperienced programmer to modify rather than to write from scratch.This builds your confidence in problem-solving. That's why 35 challenges consist of partially written programs for you to complete.
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Python Playground
Python is a powerful programming language that s easy to learn and fun to play with.But once you ve gotten a handle on the basics, what do you do next?Python Playground is a collection of imaginative programming projects that will inspire you to use Python to make art and music, build simulations of real-world phenomena, and interact with hardware like the Arduino and Raspberry Pi.You ll learn to use common Python tools and libraries like numpy, matplotlib, and pygame to do things like: Generate Spirograph-like patterns using parametric equations and the turtle module Create music on your computer by simulating frequency overtones Translate graphical images into ASCII art Write an autostereogram program that produces 3D images hidden beneath random patterns Make realistic animations with OpenGL shaders by exploring particle systems, transparency, and billboarding techniques Construct 3D visualizations using data from CT and MRI scans Build a laser show that responds to music by hooking up your computer to an Arduino Programming shouldn t be a chore.Have some solid, geeky fun with Python Playground. The projects in this book are compatible with both Python 2 and 3.
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Is Python difficult?
Python is generally considered to be one of the easier programming languages to learn due to its simple and readable syntax. It is often recommended as a good language for beginners. However, like any programming language, mastering Python can still be challenging, especially when working on more complex projects or diving into advanced topics. With practice and dedication, Python can be a very rewarding language to learn.
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Python or Kotlin?
The choice between Python and Kotlin depends on the specific use case and requirements. Python is a versatile language known for its simplicity and readability, making it a popular choice for tasks like data analysis, machine learning, and web development. On the other hand, Kotlin is a modern language that is fully interoperable with Java and is often used for Android app development due to its conciseness and safety features. Ultimately, the decision between Python and Kotlin should be based on the specific project needs and the developer's familiarity with the language.
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'Kotlin or Python?'
Both Kotlin and Python are popular programming languages with their own strengths. Kotlin is known for its strong type system, interoperability with Java, and modern language features, making it a good choice for Android development and backend services. On the other hand, Python is known for its simplicity, readability, and extensive libraries, making it a great choice for web development, data analysis, and artificial intelligence. The choice between Kotlin and Python ultimately depends on the specific requirements of the project and the developer's familiarity with the language.
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Is Python funny?
Python can be considered funny in the sense that it has a playful and whimsical approach to programming. Its syntax is often described as clean and easy to read, which can lead to a more enjoyable coding experience. Additionally, Python's community and culture often incorporate humor and lightheartedness, with memes, jokes, and puns related to Python programming being common. Overall, while humor is subjective, many people find Python to have a fun and amusing aspect to it.
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