Effective Pycharm
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Effective Pycharm
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Author : Michael Kennedy
language : en
Publisher: Independently Published
Release Date : 2019-04-19
Effective Pycharm written by Michael Kennedy and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-19 with categories.
Hello and welcome to Effective PyCharm. In this book, we're going to look at all the different features of one of the very best environments for interacting and creating Python code, PyCharm. PyCharm is an IDE (integrated development environment) and this book will teach you how you can make the most of this super powerful editor.The first thing we are going to talk about is why do we want to use an IDE in the first place? What value does a relatively heavyweight application like PyCharm bring and why would we want to use it? There are many features that make PyCharm valuable. However, let's begin by talking about the various types of editors we can use and what the trade-offs are there.We're going to start by focusing on creating new projects and working with all the files in them. You'll see there's a bunch of configuration switcheswe can set to be more effective. Then we're going to jump right intowhat I would say is the star of the show--the editor.If you're writing code, you need an editor. You will be writing a lot of code. This includes typing new text and manipulating existing text. The editor has to be awesome and aid you in these tasks. We're going to focus on all the cool features that the PyCharm editor offers. We'll see that source control in particular, Git and Subversion are deeply integrated into PyCharm. There are all sorts of powerful things we can do beyond git, including actual GitHub integration. We are going to focus on source control and the features right inside the IDE.PyCharm is great at *refactoring*. Refactoring code is changing our code to restructure it in a different way, to use a slightly different algorithm, while not actually changing the behavior of the code. There are many powerful techniques in PyCharm that you can use to do this. Because it understands all of your files at once, it can safely refactor. It will even refactor doc strings and other items that could be overlooked without a deep understanding of code structures.There is powerful database tooling in PyCharm. You can interact with most databases including SQLite, MySQL, and Postgres. You can edit the data, edit the schemes, run queries and more. Because PyCharm has a deep understanding of your code, there is even integration between your database schema and the Python text editor. Note that PyCharm has a free version and a professional version. The database features are only available in the professional version.PyCharm is excellent at building web applications using libraries like Django, Pyramid, or Flask. It also has a full JavaScript editor and environment so you can use TypeScript or CoffeeScript. We'll look into both server-side and client-side features.PyCharm has a great visual debugger, and we are going to look at all the different features of it. You can use it to debug and understand your application. It has powerful breakpoint operations and data visualization that typically editors don't have.Profiling is a common task if you want to understand how your code is running. If your application is slow and you want it to go faster, you shouldn't guess where it is slow. PyCharm makes it easy to look at the code determine what it fast and slow, rather than relying on our intuition which may be flawed. PyCharm has some tremendous built-in visual types of tools for us to fundamentally understand the performance of our app.PyCharm has built-in test runners for pytest, unittest, and a number of Python testing frameworks. If you are doing any unit testing or integration testing, PyCharm will come to your aid. For example, one feature you can turn on is auto test execution. If you are changing certain parts of your code, PyCharm will automatically re-run the tests. There are a couple of additional tools that don't really land in any of the above categories. There is a chapter with the additional tools at the end.
Effective Machine Learning Teams
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Author : David Tan
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-02-29
Effective Machine Learning Teams written by David Tan and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-29 with Computers categories.
Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products. Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help your team avoid common traps in the ML world, so you can iterate and scale more quickly and reliably. You'll learn how to overcome friction and experience flow when delivering ML solutions. You'll also learn how to: Write automated tests for ML systems, containerize development environments, and refactor problematic codebases Apply MLOps and CI/CD practices to accelerate experimentation cycles and improve reliability of ML solutions Apply Lean delivery and product practices to improve your odds of building the right product for your users Identify suitable team structures and intra- and inter-team collaboration techniques to enable fast flow, reduce cognitive load, and scale ML within your organization
Thinking In Pandas
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Author : Hannah Stepanek
language : en
Publisher: Apress
Release Date : 2020-06-05
Thinking In Pandas written by Hannah Stepanek and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-05 with Computers categories.
Understand and implement big data analysis solutions in pandas with an emphasis on performance. This book strengthens your intuition for working with pandas, the Python data analysis library, by exploring its underlying implementation and data structures. Thinking in Pandas introduces the topic of big data and demonstrates concepts by looking at exciting and impactful projects that pandas helped to solve. From there, you will learn to assess your own projects by size and type to see if pandas is the appropriate library for your needs. Author Hannah Stepanek explains how to load and normalize data in pandas efficiently, and reviews some of the most commonly used loaders and several of their most powerful options. You will then learn how to access and transform data efficiently, what methods to avoid, and when to employ more advanced performance techniques. You will also go over basic data access and munging in pandas and the intuitive dictionary syntax. Choosing the right DataFrame format, working with multi-level DataFrames, and how pandas might be improved upon in the future are also covered. By the end of the book, you will have a solid understanding of how the pandas library works under the hood. Get ready to make confident decisions in your own projects by utilizing pandas—the right way. What You Will Learn Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance Choose the right DataFrame so that the data analysis is simple and efficient. Improve performance of pandas operations with other Python libraries Who This Book Is ForSoftware engineers with basic programming skills in Python keen on using pandas for a big data analysis project. Python software developers interested in big data.
Hands On Application Development With Pycharm
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Author : Quan Nguyen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-09-27
Hands On Application Development With Pycharm written by Quan Nguyen and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.
A definitive guide to PyCharm to help you build business-oriented Python applications ranging from modern web development to data science Key FeaturesLearn basic to advanced PyCharm concepts to improve efficiency of your Python projectsWork through practical examples that focus on efficient application development with PyCharmExplore advanced features in PyCharm such as code automation, version control, and GUI debuggingBook Description JetBrain’s PyCharm is the most popular Integrated Development Environment (IDE) used by the Python community thanks to its numerous features that facilitate faster, more accurate, and more productive programming practices. However, the abundance of options and customizations can make PyCharm seem quite intimidating. Hands-on Application Development with PyCharm starts with PyCharm’s installation and configuration process, and systematically takes you through a number of its powerful features that can greatly improve your productivity. You’ll explore code automation, version control, graphical debugging/testing, management of virtual environments, and much more. Finally, you’ll delve into specific PyCharm features that support web development and data science, two of the fastest growing applications in Python programming. These include the integration of the Django framework as well as the extensive support for IPython and Jupyter Notebook. By the end of this PyCharm book, you will have gained extensive knowledge of the tool and be able to implement its features and make the most of its support for your projects. What you will learnExplore PyCharm functionalities and what makes it stand out from other Python IDEsSet up, configure, and customize your Python projects in PyCharmUnderstand how PyCharm integrates with Django for web developmentDiscover PyCharm's capabilities in database management and data visualizationPerform code automation, GUI testing, and version control in PyCharmIntegrate interactive Python tools such as Jupyter Notebooks for building virtual environmentsWho this book is for If you’re a beginner or an expert Python user looking to improve your productivity using one of the best Python IDEs, this book is for you. Basic knowledge of Python programming language is expected.
The Big Book Of Small Python Projects
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Author : Al Sweigart
language : en
Publisher: No Starch Press
Release Date : 2021-06-25
The Big Book Of Small Python Projects written by Al Sweigart and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Computers categories.
Best-selling author Al Sweigart shows you how to easily build over 80 fun programs with minimal code and maximum creativity. If you’ve mastered basic Python syntax and you’re ready to start writing programs, you’ll find The Big Book of Small Python Projects both enlightening and fun. This collection of 81 Python projects will have you making digital art, games, animations, counting pro- grams, and more right away. Once you see how the code works, you’ll practice re-creating the programs and experiment by adding your own custom touches. These simple, text-based programs are 256 lines of code or less. And whether it’s a vintage screensaver, a snail-racing game, a clickbait headline generator, or animated strands of DNA, each project is designed to be self-contained so you can easily share it online. You’ll create: • Hangman, Blackjack, and other games to play against your friends or the computer • Simulations of a forest fire, a million dice rolls, and a Japanese abacus • Animations like a virtual fish tank, a rotating cube, and a bouncing DVD logo screensaver • A first-person 3D maze game • Encryption programs that use ciphers like ROT13 and Vigenère to conceal text If you’re tired of standard step-by-step tutorials, you’ll love the learn-by-doing approach of The Big Book of Small Python Projects. It’s proof that good things come in small programs!
Effective Data Science Infrastructure
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Author : Ville Tuulos
language : en
Publisher: Simon and Schuster
Release Date : 2022-08-16
Effective Data Science Infrastructure written by Ville Tuulos and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-16 with Computers categories.
Effective Data Science Infrastructure teaches you to build data pipelines and project workflows that will supercharge data scientists and their projects. Based on state-of-the-art tools and concepts that power data operations of Netflix, this book introduces a customizable cloud-based approach to model development and MLOps that you can easily adapt to your company's specific needs. As you roll out these practical processes, your teams will produce better and faster results when applying data science and machine learning to a wide array of business problems.
Effective Python
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Author : Brett Slatkin
language : en
Publisher:
Release Date : 2015
Effective Python written by Brett Slatkin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
5+ Hours of Video Instruction Effective Python LiveLessons Video Training offers developers insight into the Pythonic way of writing programs, building on the viewer's fundamental understanding of Python to help him or her write programs more effectively. Description Effective Python LiveLessons Video Training is based on the book Effective Python written by Google software engineer Brett Slatkin for the Effective Software Development Series. Each lesson contains a broad but related set of items. Each item is designed to provide concise and specific guidance on what to do and what to avoid when writing programs using Python. Hands-on demonstration helps the viewer understand how to put each item into action. Each of the video's six lessons includes items focused on a key topic. The video starts with items focused on how to make more efficient use of expressions and statements before moving on to lessons that teach viewers how to better use comprehensions and generators, functions, and classes. Next, the training teaches viewers how to solve problems associated with concurrency and parallelism. Finally, the focus switches to how to make Python programs more robust. After watching this video, Python programmers will have the knowledge necessary to really master the language and apply the advice, tips, and tricks learned from the video to the Python programs they're writing, immediately improving the quality of their code. The source code repository for this LiveLesson is located at https://github.com/bslatkin/effectivepython/blob/master/VIDEO.md . About the Instructor Brett Slatkin is a Senior Staff Software Engineer at Google and the engineering lead and co-founder of Google Consumer Surveys. Slatkin formerly worked on Google App Engine's Python infrastructure. He is the co-creator of the PubSubHubbub protocol. Nine years ago, he cut his teeth using Python to manage Google's enormous fleet of servers. Outside of his day job, he works on open source tools and writes about software, bicycles, and other topics on his personal website. He earned his B.S. in Computer Engineering from Columbia University in the City of New York. He lives in San Francisco. Skill Level Intermediate to Advanced What You Will Learn Methods for using expressions and statements more efficiently How to make better use of comprehensions and generators How to make better use of functions and classes Methods for working with concurrency and parallelism How to make your program...
Python Testing With Pytest
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Author : Brian Okken
language : en
Publisher:
Release Date : 2017-09-25
Python Testing With Pytest written by Brian Okken and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-25 with Computers categories.
Do less work when testing your Python code, but be just as expressive, just as elegant, and just as readable. The pytest testing framework helps you write tests quickly and keep them readable and maintainable - with no boilerplate code. Using a robust yet simple fixture model, it's just as easy to write small tests with pytest as it is to scale up to complex functional testing for applications, packages, and libraries. This book shows you how. For Python-based projects, pytest is the undeniable choice to test your code if you're looking for a full-featured, API-independent, flexible, and extensible testing framework. With a full-bodied fixture model that is unmatched in any other tool, the pytest framework gives you powerful features such as assert rewriting and plug-in capability - with no boilerplate code. With simple step-by-step instructions and sample code, this book gets you up to speed quickly on this easy-to-learn and robust tool. Write short, maintainable tests that elegantly express what you're testing. Add powerful testing features and still speed up test times by distributing tests across multiple processors and running tests in parallel. Use the built-in assert statements to reduce false test failures by separating setup and test failures. Test error conditions and corner cases with expected exception testing, and use one test to run many test cases with parameterized testing. Extend pytest with plugins, connect it to continuous integration systems, and use it in tandem with tox, mock, coverage, unittest, and doctest. Write simple, maintainable tests that elegantly express what you're testing and why. What You Need: The examples in this book are written using Python 3.6 and pytest 3.0. However, pytest 3.0 supports Python 2.6, 2.7, and Python 3.3-3.6.
Coding With Chatgpt And Other Llms
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Author : Dr. Vincent Austin Hall
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-11-29
Coding With Chatgpt And Other Llms written by Dr. Vincent Austin Hall and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Computers categories.
Leverage LLM (large language models) for developing unmatched coding skills, solving complex problems faster, and implementing AI responsibly Key Features Understand the strengths and weaknesses of LLM-powered software for enhancing performance while minimizing potential issues Grasp the ethical considerations, biases, and legal aspects of LLM-generated code for responsible AI usage Boost your coding speed and improve quality with IDE integration Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionKeeping up with the AI revolution and its application in coding can be challenging, but with guidance from AI and ML expert Dr. Vincent Hall—who holds a PhD in machine learning and has extensive experience in licensed software development—this book helps both new and experienced coders to quickly adopt best practices and stay relevant in the field. You’ll learn how to use LLMs such as ChatGPT and Bard to produce efficient, explainable, and shareable code and discover techniques to maximize the potential of LLMs. The book focuses on integrated development environments (IDEs) and provides tips to avoid pitfalls, such as bias and unexplainable code, to accelerate your coding speed. You’ll master advanced coding applications with LLMs, including refactoring, debugging, and optimization, while examining ethical considerations, biases, and legal implications. You’ll also use cutting-edge tools for code generation, architecting, description, and testing to avoid legal hassles while advancing your career. By the end of this book, you’ll be well-prepared for future innovations in AI-driven software development, with the ability to anticipate emerging LLM technologies and generate ideas that shape the future of development.What you will learn Utilize LLMs for advanced coding tasks, such as refactoring and optimization Understand how IDEs and LLM tools help coding productivity Master advanced debugging to resolve complex coding issues Identify and avoid common pitfalls in LLM-generated code Explore advanced strategies for code generation, testing, and description Develop practical skills to advance your coding career with LLMs Who this book is for This book is for experienced coders and new developers aiming to master LLMs, data scientists and machine learning engineers looking for advanced techniques for coding with LLMs, and AI enthusiasts exploring ethical and legal implications. Tech professionals will find practical insights for innovation and career growth in this book, while AI consultants and tech hobbyists will discover new methods for training and personal projects.