Python is one of the most popular programming languages. It is a general purpose high- level language, created by Guido van Rossum, and publicly released in 1991. It is an interpreted language. The philosophy of the language is about the code readability. For example, you use white spaces to delimit code blocks instead of special characters such as semicolons or curly brackets.

Python supports automatic memory management. It has a dynamic type system. You can use multiple program paradigms in Python, including procedural, object-oriented, and functional programming. You can find Python interpreters for all major operating systems. The reference implementation of Python, namely CPython, is open source software, managed by the non-profit Python Software Foundation. Of course, it being open source also means that there is a rich set of libraries available. Even the standard library is impressive and comprehensive.

Like SQL Server 2016 started to support R, SQL Server 2017 supports Python. Now you can select your preferred language for data science and even other tasks. R has even more statistical, data mining, and machine learning libraries, because it is more widely used in the data science community; however, Python has a broader purpose than just data science, and is more readable and therefore might be simpler to learn. This chapter introduces Python for SQL Server developers and business intelligence (BI) specialists. This means that the chapter is more focused on Python basics and data science, and less on general programming with Python.

This chapter will cover the following points:

• Python basics and concepts
• Python data structures
• Basic data management and visualizations
• Introductory statistics with Python
• Data science with Python
• Creating and using scalable Python solutions in SQL Server