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Python Programming

What Is Python?

Python is an open-source, object-oriented programming language.

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According to Python.org, its simple, easy-to-learn syntax emphasizes readability and therefore reduces the cost of program maintenance.

In short, Python is an open-source, object-oriented interactive programming language that is interpreted line by line.

With simple and easy to learn syntax, as well as advanced readability and support for a number of modules and libraries, Python is well-loved due to the increased productivity it provides.

As a testament to this, Python is used by some of the biggest organizations in the world to power their platforms, perform data analysis, and run their machine learning models. Companies including Google, YouTube, Netflix, NASA, Spotify, and IBM have publicly stated Python has been an important part of their growth, due to its simplicity, speed, and scalability. In fact, Google’s first web-crawler was actually written in Python and it remains one of their official server-side languages.

How to Run Python

You can run Python scripts in a number of ways, depending on what works best for you.

Most systems come with Python already installed, although it’s worth noting that this will more than likely be Python 2, which will be officially deprecated in 2020 now that Python 3 is deemed stable.

You can run Python from your terminal or command line IDE (Integrated Development Environment) or use cloud-based alternatives including:

These provide an easier experience for beginners to learn and test elements of code line by line.

Python Libraries

The main power of Python is in its libraries, which enable a number of add-ons including:

  • Data extraction.
  • Analysis and preparation.
  • Scientific computing.
  • Natural language processing.
  • Machine learning.

Some useful libraries for tasks involving data analysis and automation include:

  • TensorFlow: An open-source machine learning library.
  • NumPy: Useful for scientific computing.
  • SciPy: Used for scientific and technical computing.
  • SciKit Lear: Machine learning for data mining and analysis.
  • Pandas: Used for data manipulation and analysis.
  • SpaCy: A great natural language processing library.
  • Requests: A library for making HTTP requests.

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