What is Python? Executive Summary Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn't catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python's introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective. What is Python? Python is a popular programming language. It was created by Guido van Rossum, and released in 1991. It is used for: web development (server-side), software development, mathematics, system scripting. What can Python do? Python can be used on a server to create web applications. Python can be used alongside software to create workflows. Python can connect to database systems. It can also read and modify files. Python can be used to handle big data and perform complex mathematics. Python can be used for rapid prototyping, or for production-ready software development. Why Python? Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc). Python has a simple syntax similar to the English language. Python has syntax that allows developers to write programs with fewer lines than some other programming languages. Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick. Python can be treated in a procedural way, an object-oriented way or a functional way. Good to know The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular. In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files. Python Syntax compared to other programming languages Python was designed for readability, and has some similarities to the English language with influence from mathematics. Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses. Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose. Applications for Python Python is used in many application domains. Here's a sampling. The Python Package Index lists thousands of third party modules for Python. Web and Internet Development Python offers many choices for web development: Frameworks such as Django and Pyramid. Micro-frameworks such as Flask and Bottle. Advanced content management systems such as Plone and django CMS. Python's standard library supports many Internet protocols: HTML and XML JSON E-mail processing. Support for FTP, IMAP, and other Internet protocols. Easy-to-use socket interface. And the Package Index has yet more libraries: Requests, a powerful HTTP client library. Beautiful Soup, an HTML parser that can handle all sorts of oddball HTML. Feedparser for parsing RSS/Atom feeds. Paramiko, implementing the SSH2 protocol. Twisted Python, a framework for asynchronous network programming. Scientific and Numeric Python is widely used in scientific and numeric computing: SciPy is a collection of packages for mathematics, science, and engineering. Pandas is a data analysis and modeling library. IPython is a powerful interactive shell that features easy editing and recording of a work session, and supports visualizations and parallel computing. The Software Carpentry Course teaches basic skills for scientific computing, running bootcamps and providing open-access teaching materials. Education Python is a superb language for teaching programming, both at the introductory level and in more advanced courses. Books such as How to Think Like a Computer Scientist, Python Programming: An Introduction to Computer Science, and Practical Programming. The Education Special Interest Group is a good place to discuss teaching issues. Desktop GUIs The Tk GUI library is included with most binary distributions of Python. Some toolkits that are usable on several platforms are available separately: wxWidgets Kivy, for writing multitouch applications. Qt via pyqt or pyside Platform-specific toolkits are also available: GTK+ Microsoft Foundation Classes through the win32 extensions Software Development Python is often used as a support language for software developers, for build control and management, testing, and in many other ways. SCons for build control. Buildbot and Apache Gump for automated continuous compilation and testing. Roundup or Trac for bug tracking and project management. Business Applications Python is also used to build ERP and e-commerce systems: Odoo is an all-in-one management software that offers a range of business applications that form a complete suite of enterprise management applications. Try ton is a three-tier high-level general purpose application platform.

The UNICORN Binance Suite is a comprehensive collection of open-source Python packages designed for building sophisticated automated trading systems. Tailored for Python developers, this suite offers seamless integration with the Binance API, enabling the creation of advanced and professional trading bots for streamlined and efficient trading.

Anime Pahe is an advanced Telegram bot built to fully automate the anime downloading and uploading pipeline. Designed for speed and reliability, it features smart queue processing, batch uploads, per-anime channel routing, and automated file cleanups. Built with Python and Pyrogram, it is highly scalable and optimized for VPS and local deployments

A Devops pipeline is set of automated processes and tools that the development (Dev) and operations (Ops) teams implement to build, test, and deploy software faster and easier. In this course you will complete DevOps pipeline generally consists of a set of tools which are normally broken down into the following categories: Plan Code Integrate Test Release Deploy Operate This learning path will cover: Git is an open-source and distributed version control system. Github is git repository hosting service used for code sharing, bug tracking, feature request and much more. PyCharm is an integrated development environment (IDE) for python programing language. Flask is a python web framework. HTML is the standard markup language for Web pages. CSS is a style sheet language use to style a HTML document. SQLAlchemy is an open-source SQL toolkit and object-relational mapper which gives full power and flexibility of SQL. Selenium is used to automate web browser interaction. Pytest is unit testing framework that allows users to write test codes. Ngrok allows to expose a web server running on your local machine to the internet. Github Action enables you to include Continues Integration (CI) and continuous deployment (CD) capabilities and many other features directly in your repository. Docker is an open source containerization platform enables developers to package applications into containers. Docker Hub is a cloud-based repository for finding and sharing container images with your team. Kubernetes is an open-source container orchestration for automating deployment, scaling, and management of containerized applications. This course is one stop shop where you will learn web development, continuous integration, continuous deployment, containerization, writing neat and quality code, devops concepts and much more with python programing language. What you’ll learn Learn to build Continuous Integration Continuous Deployment pipeline Build CI CD tool to update docker image after any update Learn to create dockerfile Learn the fundamental concepts of Docker Learn the fundamental concepts of Kubernetes Learn to create Kubernetes YAML files Learn to deploy high availability, fault tolerance, scalable application Learn all the basic and advanced git commands Learn different types of branches like master, developer, feature, release and hotfix branch Learn fundamental concepts of Version Control System Learn to use Github actions for CI CD pipeline Learn to build python flask web application Learn to use SQL Alchemy Lean to create HTML pages using HTML, CSS and bootstrap Are there any course requirements or prerequisites? Git installed Docker installed Kubernetes installed Any IDE Github account Docker hub account Who this course is for: Anyone who wants to Enhance their skills in DevOps domain Developers and IT Pros Instructor User photo Pranjal Srivastava Docker | Kubernetes | AWS | Azure | ML | Linux | Python I am an Instructor, Devops engineer, machine learning enthusiast, cloud expert and passionate developer. I have authored 60+ courses with over 50,000+ students worldwide across 175+ countries on wide array of technologies like containerization, machine learning, Linux, programming languages and cloud computing platforms like Microsoft Azure, Amazon Web Service and IBM Cloud.

BibexPy is a Python-based software designed to streamline bibliometric data integration, deduplication, metadata enrichment, and format conversion. It simplifies the preparation of high-quality datasets for advanced analyses by automating traditionally manual and error-prone tasks.