Search results for "introduction to python programming"
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Learning Concurrency in Python
Practically and deeply understand concurrency in Python to write efficient programsAbout This Book• Build highly efficient, robust, and concurrent applications• Work through practical examples that will help you address the challenges of writing concurrent code• Improve the overall speed of execution in multiprocessor and multicore systems and keep them highly availableWho This Book Is ForThis book is for Python developers who would like to get started with concurrent programming. Readers are expected to have a working knowledge of the Python language, as this book will build on these fundamentals concepts.What You Will Learn• Explore the concept of threading and multiprocessing in Python• Understand concurrency with threads• Manage exceptions in child threads• Handle the hardest part in a concurrent system — shared resources• Build concurrent systems with Communicating Sequential Processes (CSP)• Maintain all concurrent systems and master them• Apply reactive programming to build concurrent systems• Use GPU to solve specific problemsIn DetailPython is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create.This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python.The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems.By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices.Style and approachThis easy-to-follow guide teaches you new practices and techniques to optimize your code, and then moves toward more advanced ways to effectively write efficient Python code. Small and simple practical examples will help you test the concepts yourself, and you will be able to easily adapt them for any application.
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Python for SAS Users
Business users familiar with Base SAS programming can now learn Python by example. You will learn via examples that map SAS programming constructs and coding patterns into their Python equivalents. Your primary focus will be on pandas and data management issues related to analysis of data.It is estimated that there are three million or more SAS users worldwide today. As the data science landscape shifts from using SAS to open source software such as Python, many users will feel the need to update their skills. Most users are not formally trained in computer science and have likely acquired their skills programming SAS as part of their job.As a result, the current documentation and plethora of books and websites for learning Python are technical and not geared for most SAS users. Python for SAS Users provides the most comprehensive set of examples currently available. It contains over 200 Python scripts and approximately 75 SAS programs that are analogs to the Python scripts. The first chapters are more Python-centric, while the remaining chapters illustrate SAS and corresponding Python examples to solve common data analysis tasks such as reading multiple input sources, missing value detection, imputation, merging/combining data, and producing output. This book is an indispensable guide for integrating SAS and Python workflows.What You’ll LearnQuickly master Python for data analysis without using a trial-and-error approachUnderstand the similarities and differences between Base SAS and PythonBetter determine which language to use, depending on your needsObtain quick resultsWho This Book Is ForSAS users, SAS programmers, data scientists, data scientist leaders, and Python users who need to work with SAS
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Maya Programming with Python Cookbook
Master complex workflows and conquer the world with Python and MayaAbout This Book• Improve your modelling skills and reduce your scripting problems using Python in Maya• Learn to communicate with web applications using Python for easier team development• A quick and practical answer to every problem you can have whilst scripting in Maya with PythonWho This Book Is ForThis book is for Python developers who have just started scripting with Maya.What You Will Learn• Find out how to use Python scripting to automate tedious tasks• Create functional user interfaces to make scripts easy to share with others• Add new functionality to Maya via the power of scripting• Import and export arbitrary data into and out of Maya• Improve your workflow, and that of your team• Create custom create custom controls to make rigs that are easy to work with• Implement a system to render 3D assets for isometric games• Use script jobs to trigger actions automatically in response to user interaction• Open a command port to allow other applications to communicate with MayaIn DetailMaya is a 3D graphics and animation software, used to develop interactive 3D applications and games with stupendous visual effects. The Maya Programming with Python Cookbook is all about creating fast, powerful automation systems with minimum coding using Maya Python. With the help of insightful and essential recipes, this book will help you improve your modelling skills. Expand your development options and overcome scripting problems encountered whilst developing code in Maya. Right from the beginning, get solutions to complex development concerns faced when implementing as parts of build.Style and approachThis book is comprised of a set of practical recipes, grouped under specific topics, which can be referred to independently or in sequence. These recipes provide quick solutions to common problems, and cover most of the real-world scenarios that developers are likely to face when working with Maya.
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Learning Python for Forensics
Learn the art of designing, developing, and deploying innovative forensic solutions through PythonAbout This Book• This practical guide will help you solve forensic dilemmas through the development of Python scripts• Analyze Python scripts to extract metadata and investigate forensic artifacts• Master the skills of parsing complex data structures by taking advantage of Python librariesWho This Book Is ForIf you are a forensics student, hobbyist, or professional that is seeking to increase your understanding in forensics through the use of a programming language, then this book is for you.You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding of examiners who wish to learn programmingWhat You Will Learn• Discover how to perform Python script development• Update yourself by learning the best practices in forensic programming• Build scripts through an iterative design• Explore the rapid development of specialized scripts• Understand how to leverage forensic libraries developed by the community• Design flexibly to accommodate present and future hurdles• Conduct effective and efficient investigations through programmatic pre-analysis• Discover how to transform raw data into customized reports and visualizationsIn DetailThis book will illustrate how and why you should learn Python to strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. The tutorials use an interactive design, giving you experience of the development process so you gain a better understanding of what it means to be a forensic developer.Each chapter walks you through a forensic artifact and one or more methods to analyze the evidence. It also provides reasons why one method may be advantageous over another. We cover common digital forensics and incident response scenarios, with scripts that can be used to tackle case work in the field. Using built-in and community-sourced libraries, you will improve your problem solving skills with the addition of the Python scripting language. In addition, we provide resources for further exploration of each script so you can understand what further purposes Python can serve. With this knowledge, you can rapidly develop and deploy solutions to identify critical information and fine-tune your skill set as an examiner.Style and approachThe book begins by instructing you on the basics of Python, followed by chapters that include scripts targeted for forensic casework. Each script is described step by step at an introductory level, providing gradual growth to demonstrate the available functionalities of Python.
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Python GUI Programming Cookbook
Over 80 object-oriented recipes to help you create mind-blowing GUIs in PythonAbout This Book• Use object-oriented programming to develop amazing GUIs in Python• Create a working GUI project as a central resource for developing your Python GUIs• Packed with easy-to-follow recipes to help you develop code using the latest released version of PythonWho This Book Is ForIf you are a Python programmer with intermediate level knowledge of GUI programming and want to learn how to create beautiful, effective, and responsive GUIs using the freely available Python GUI frameworks, this book is for you.What You Will Learn• Create amazing GUIs with Python's built-in Tkinter module• Customize the GUIs by using layout managers to arrange the GUI widgets• Advance to an object-oriented programming style using Python• Develop beautiful charts using the free Matplotlib Python module• Use threading in a networked environment to make the GUIs responsive• Discover ways to connect the GUIs to a database• Understand how unit tests can be created and internationalize the GUI• Extend the GUIs with free Python frameworks using best practices In DetailPython is a multi-domain, interpreted programming language. It is a widely used general-purpose, high-level programming language. It is often used as a scripting language because of its forgiving syntax and compatibility with a wide variety of different eco-systems. Its flexible syntax enables developers to write short scripts while at the same time, they can use object-oriented concepts to develop very large projects.Python GUI Programming Cookbook follows a task-based approach to help you create beautiful and very effective GUIs with the least amount of code necessary. This book uses the simplest programming style, using the fewest lines of code to create a GUI in Python, and then advances to using object-oriented programming in later chapters. If you are new to object-oriented programming (OOP), this book will teach you how to take advantage of the OOP coding style in the context of creating GUIs written in Python.Throughout the book, you will develop an entire GUI application, building recipe upon recipe, connecting the GUI to a database. In the later chapters, you will explore additional Python GUI frameworks, using best practices. You will also learn how to use threading to ensure your GUI doesn't go unresponsive.By the end of the book, you will be an expert in Python GUI programming to develop a common set of GUI applications.Style and approachEvery recipe in this programming cookbook solves a problem you might encounter in your programming career. At the same time, most of the recipes build on each other to create an entire, real-life GUI application.
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Getting Started with Python Data Analysis
Learn to use powerful Python libraries for effective data processing and analysisAbout This Book• Learn the basic processing steps in data analysis and how to use Python in this area through supported packages, especially Numpy, Pandas, and Matplotlib• Create, manipulate, and analyze your data to extract useful information to optimize your system• A hands-on guide to help you learn data analysis using PythonWho This Book Is ForIf you are a Python developer who wants to get started with data analysis and you need a quick introductory guide to the python data analysis libraries, then this book is for you.What You Will Learn• Understand the importance of data analysis and get familiar with its processing steps• Get acquainted with Numpy to use with arrays and array-oriented computing in data analysis• Create effective visualizations to present your data using Matplotlib• Process and analyze data using the time series capabilities of Pandas• Interact with different kind of database systems, such as file, disk format, Mongo, and Redis• Apply the supported Python package to data analysis applications through examples• Explore predictive analytics and machine learning algorithms using Scikit-learn, a Python libraryIn DetailData analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It's often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis.With this book, we will get you started with Python data analysis and show you what its advantages are.The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems.Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples.Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn. Style and approachThis is an easy-to-follow, step-by-step guide to get you familiar with data analysis and the libraries supported by Python. Topics are explained with real-world examples wherever required.
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