![[Assets/python_logo.svg|100]] [Python](https://www.python.org/) is a high-level general-purpose programming language. It's main philosophy revolves around code readability and object-oriented design to help programmers write and read clear, logical code. In Data Engineering, it's commonly used to transform data and incorporate business logic in [[Data Pipeline|data pipelines]]. ## Official Documentation https://docs.python.org/ ## Advantages - Easy to learn, read and write - Requires less code to complete a task compared to most other languages - Can run on any platform with the same code (portable) - Extensive 3rd party libraries - Large active community ## Disadvantages - Code is not compiled so it's slower than compiled languages - Increased probability of runtime errors due to dynamic typing - Memory intensive - Database access is weaker compared to JDBC and ODBC ![[Learning Resources#Python Learning Resources]] ## [Recent Python Posts in the Community](https://www.reddit.com/r/dataengineering/search/?q=python&restrict_sr=1&sort=relevance&t=year) %% wiki footer: Please don't edit anything below this line %% ## This note in GitHub <span class="git-footer">[Edit In GitHub](https://github.dev/data-engineering-community/data-engineering-wiki/blob/main/Tools/Programming%20Languages/Python.md "git-hub-edit-note") | [Copy this note](https://raw.githubusercontent.com/data-engineering-community/data-engineering-wiki/main/Tools/Programming%20Languages/Python.md "git-hub-copy-note")</span> <span class="git-footer">Was this page helpful? [👍](https://tally.so/r/mOaxjk?rating=Yes&url=https://dataengineering.wiki/Tools/Programming%20Languages/Python) or [👎](https://tally.so/r/mOaxjk?rating=No&url=https://dataengineering.wiki/Tools/Programming%20Languages/Python)</span>