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https://github.com/alprojects1/python

Collection of practices, written apps, automation testing
https://github.com/alprojects1/python

pip pycharm pycharm-ide python python3 vscode-extension

Last synced: 12 days ago
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Collection of practices, written apps, automation testing

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README 

        
## Python Wiki:



**Python is an open-source, high-level programming language known for its simplicity and versatility. Designed by Guido van Rossum in 1991, in Haarlem, the Netherlands. Of course, Guido van Rossum did not develop and evolve all the Python components himself**. It has a massive standard library, making it adaptable to countless applications. 



**Python's community-driven nature ensures ongoing development and support, with popular frameworks like Django and Flask accelerating web development projects**. Python is often praised for its dynamic typing, interpreted nature, and ease of use for beginners while maintaining power and scalability for more advanced projects. It can be run on all major platforms like (`Windows`), (`macOS`), and (`Linux`).



Python emphasizes code readability and supports multiple programming paradigms, including procedural, object-oriented, and functional programming**. Python is widely used in web development, automation, data analysis, artificial intelligence, and more. **Major websites and services like (`Dropbox`), (`Uber`), (`Spotify`), (`Pintrest`), (`BuzzFee`)** were all written, to a greater or lesser extent, in Python.



**Do you remember (`Battlefield 2`), (`Battlefield 2142`) and (`Battlefield Heroes`) - strategy and first person shooter games from (`EA`) (`DICE`)? All the games use Python for logic and server controls**. **Python is frequently used for creating open-source, free games, like (`OpenRTS`), (`PySol`), (`Metin 2`), or (`Frets On Fire`) and (`Guitar Hero`)-like games written in pygame**. 



**while you may know the python as a large snake, the name of the Python programming language comes from an old BBC television comedy sketch series called Monty Python's Flying Circus**. At the height of its success, the Monty Python team were performing their sketches to live audiences across the world, including at the Hollywood Bowl. **Since Monty Python is considered one of the two fundamental nutrients to a programmer** (`the other being pizza`), Python's creator named the language in honor of the TV show.



## PyCharm Wiki:



**PyCharm is a powerful integrated development environment (IDE) specifically designed for Python programming**. Developed by (`JetBrains`) and released in 2010, PyCharm offers extensive code analysis, support for web frameworks (`like Django`), and a vast array of tools that help streamline Python development. PyCharm's features include intelligent code completion, on-the-fly error checking, and seamless integration with version control systems like Git.



PyCharm comes in two versions: Community Edition (`open-source`) and Professional Edition (`commercial`), with the latter offering additional support for web development, scientific computing, and remote development.



## Python Rivals:



- **Python has two direct competitors, with comparable properties and predispositions. The former is more traditional and more conservative than Python**, and resembles some of the old languages derived from the classic C programming language. 



    - ***Perl*** – a scripting language originally authored by Larry Wall.

    - ***Ruby*** – a scripting language originally authored by Yukihiro Matsumoto.

 

- **In contrast, the latter is more innovative and more full of fresh ideas than Python. Python itself lies somewhere between these two creations**.

    

## Security & Compliance:



- ***Python Security*** - Python supports a range of security-focused libraries (`PyCryptodome, Secure-SMTPLib`) that can be used to ensure encrypted communications, secure data storage, and safe web interactions.

- ***PyCharm Security*** - PyCharm provides secure coding tools that help developers identify and mitigate vulnerabilities in their code, such as (`SQL`) injection or insecure deserialization.

- ***Compliance*** - Python and PyCharm can be used in developing secure, compliant applications that meet industry standards like (`GDPR`), (`PCI DSS`), and (`HIPAA`), with auditing, logging, and encryption features.



## Important Note:

- (`Do NOT`) ignore Python's version compatibility. While Python 2.7 is still in use, Python 3 is the current and recommended version. Migrating older code to Python 3 is essential for security, performance, and long-term support.



## Key Features:



- ***Python***

  - ***Cross-platform*** - Works across Windows, macOS, and Linux.

  - ***Extensive Standard Library*** - Offers modules for everything from file I/O to networking.

  - ***Diverse Use Cases*** - Powers web development, machine learning, AI, automation, and data analysis. 

  - ***Community Support*** A large, active community continually contributes packages and tutorials.



- ***PyCharm***

  - ***Code Intelligence*** - Features intelligent code completion and on-the-fly syntax and error checking.

  - ***Debugger*** - Powerful built-in debugger with visual stepping through code.

  - ***Integration*** - Seamlessly integrates with (`Git`), (`GitHub`), and other version control tools.

  - ***Testing Frameworks*** - Built-in support for unit testing, with integration for pytest and unittest.



## Best Practices:



  - ***Use Virtual Environments*** - Isolate project dependencies using venv or Conda to avoid conflicts between libraries.

  - ***Code Style*** - Adhere to the PEP 8 style guide to maintain readability and consistency across Python codebases.

  - ***Leverage PyCharm’s Refactoring Tools*** - Use PyCharm's refactoring features to improve code structure, reduce duplication, and enhance maintainability.

  - ***Test Early, Test Often*** - Automate testing through PyCharm’s built-in testing framework integration to catch errors before deployment.



##

> One Cool Thing About Python and PyCharm: Python's versatility is what makes it unique. From simple automation scripts to large-scale machine learning projects, Python can do it all. Combined with PyCharm, you get an all-in-one IDE that enhances productivity, whether you're building a web app, processing large datasets, or testing new machine learning algorithms. With Jupyter Notebook integration in PyCharm Professional, scientific and data-driven tasks are even more accessible, making it a top choice for data scientists and developers alike.