Use PyCharm with fluid efficiency to write idiomatic python code About This Book Understand how PyCharm works and how you can leverage its strength to develop applications quickly Master PyCharm's editor to get a fast workflow Full of examples and illustrations that focus on the practical aspects of using PyCharm Who This Book Is For If you know PyCharm but want to understand it better and leverage its more powerful but less obvious tool set, this is the book for you. Serving as a launch pad for those who want to master PyCharm and completely harness its best features, it would be helpful if you were familiar with some of Python's most prominent tools such as virtualenv and Python's popular docstring formats such as reStructuredText and EpyType. What You Will Learn Understand the internal workings of the IntelliJ Platform Leverage PyCharm's powerful search tools, and learn which ones are the best for you and your workflow Customize PyCharm's enhanced Python interpreter and its inbuilt terminal Develop web applications quickly and easily with different frameworks such as Flask and Django Understand how code completion works in PyCharm for Python and JavaScript In Detail PyCharm is addictive, with powerful and configurable code completion, superb editing tools, top-notch support, diverse plugins, and a vibrant ecosystem to boot. Learning how PyCharm works and maximising the synergy of its powerful tools will help you to rapidly develop applications. From leveraging the power of the editor to understanding PyCharm's internals, this book will give you a comprehensive view of PyCharm and allow you to make your own choices about which workflow and tools are best for you. You will start by getting comfortable with PyCharm and making it look exactly like you want. You can customize the tools and taskbars to suit individual developers' coding styles. You also learn how to assign keyboard shortcuts. You will master debugging by inserting breakpoints, collecting runtime data, and debugging from the console. You will understand how PyCharm works underneath and how plugins such as Codemap, Vim, Bitbucket, Assets compressor, markdown, bash file, shortcut translator, and .gitignore leverage the power of the IntelliJ platform. You will become comfortable using the VCS interface in PyCharm and see the benefits of using it for some simple tasks as well as some more complex tasks such as partial commits using changelists. You will take an in-depth look at the various tools in PyCharm, improving your workflow drastically. Finally, you will deploy powerful PyCharm tools for Django, Flask, GAE, and Pyramid Development, becoming well acquainted with PyCharm's toolset for web development with popular platforms. Packed with insider tricks, this book will help you boost productivity with PyCharm. Style and approach An easy-to-follow guide with plenty of examples and screenshots. Each topic starts off with the goal of enhancing or changing a part of PyCharm to make it suit your needs.

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.

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.

Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key FeaturesUnderstand how large-scale state-of-the-art RL algorithms and approaches workApply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and moreExplore tips and best practices from experts that will enable you to overcome real-world RL challengesBook Description Reinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL. Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. After that, you will learn about deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning. Then, you'll be introduced to some of the key approaches behind the most successful RL implementations, such as domain randomization and curiosity-driven learning. As you advance, you’ll explore many novel algorithms with advanced implementations using modern Python libraries such as TensorFlow and Ray’s RLlib package. You’ll also find out how to implement RL in areas such as robotics, supply chain management, marketing, finance, smart cities, and cybersecurity while assessing the trade-offs between different approaches and avoiding common pitfalls. By the end of this book, you’ll have mastered how to train and deploy your own RL agents for solving RL problems. What you will learnModel and solve complex sequential decision-making problems using RLDevelop a solid understanding of how state-of-the-art RL methods workUse Python and TensorFlow to code RL algorithms from scratchParallelize and scale up your RL implementations using Ray's RLlib packageGet in-depth knowledge of a wide variety of RL topicsUnderstand the trade-offs between different RL approachesDiscover and address the challenges of implementing RL in the real worldWho this book is for This book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required.

Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key FeaturesDevelop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and PythonApply machine learning and deep learning techniques with TensorFlow and KerasDiscover the modern design patterns you should avoid when developing efficient computer vision applicationsBook Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learnHandle files and images, and explore various image processing techniquesExplore image transformations, including translation, resizing, and croppingGain insights into building histogramsBrush up on contour detection, filtering, and drawingWork with Augmented Reality to build marker-based and markerless applicationsWork with the main machine learning algorithms in OpenCVExplore the deep learning Python libraries and OpenCV deep learning capabilitiesCreate computer vision and deep learning web applicationsWho this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.

Master Ansible and Automate Your IT Infrastructure! Conquer IT Infrastructure Challenges with Ansible, the powerful automation tool for configuration management and deployment. This comprehensive guide equips you with the skills to: - Automate repetitive tasks and streamline your workflow (say goodbye to manual configurations!). - Ensure consistent configurations across your entire infrastructure (no more inconsistencies or errors!). - Deploy applications quickly and reliably (get those applications up and running faster!). Whether you're a system administrator, developer, or DevOps engineer, this book is your one-stop shop for mastering Ansible. Learn in-depth: - Installation & Configuration (get Ansible up and running smoothly) - Writing & Organizing Playbooks (define your infrastructure as code) - Ansible Modules, Plugins & Roles (leverage pre-built functionality for complex tasks) - Variables, Templates & Conditionals (make your playbooks dynamic and adaptable) - Dynamic Inventory Management (manage large and diverse IT environments) - Security & Troubleshooting (keep your automation secure and efficient) Master Every Step: - Step-by-step guidance through each Ansible topic (learn at your own pace). - Clear explanations and code examples (understand the concepts and see them in action). - Real-world scenarios for practical application (learn by doing!). - Best practices to optimize your automation (write efficient and maintainable playbooks). Take control of your IT infrastructure, become an Ansible expert, and boost your automation efficiency today! Keywords: Ansible, Configuration Management, IT Automation, Infrastructure Automation, DevOps, System Administration, Application Deployment

"Mastering Data Structures with Python: A Practical Guide" offers a comprehensive journey through the essential concepts of data structures, all within the practical framework of Python. Designed for both beginners and experienced programmers, this book provides a thorough understanding of the data structures that are critical to writing efficient, high-performance algorithms. The book begins with a solid introduction to fundamental data structures like arrays, linked lists, stacks, and queues, before moving on to more complex structures such as trees, graphs, and heaps. Each data structure is broken down with easy-to-understand explanations, step-by-step walkthroughs, and Python code examples that bring theory to life. The clear, practical approach ensures that readers can apply what they've learned in real-world programming situations. In addition to covering these essential structures, the book also focuses on the efficiency and performance of algorithms, teaching you how to analyze time and space complexity using Big O notation. This understanding is crucial for writing code that scales and performs well under pressure, a skill that's highly sought after in technical interviews and real-world development. The book goes beyond theory, showcasing real-world applications of data structures in Python, such as how to use them to optimize search algorithms, build complex networks, and manage large datasets. With a focus on practical problem-solving, you'll also learn tips and tricks for optimizing code, managing memory efficiently, and implementing the right data structures for various tasks. Whether you’re a student preparing for coding interviews, a developer wanting to sharpen your skills, or simply curious about data structures, "Mastering Data Structures with Python" serves as a valuable guide. It’s not just about learning Python—it’s about mastering the art of programming itself.