> For the complete documentation index, see [llms.txt](https://fall2019.fullstackdeeplearning.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://fall2019.fullstackdeeplearning.com/course-content/infrastructure-and-tooling/software-engineering.md). # Software Engineering {% embed url="" %} Software Engineering - Infrastructure and Tooling {% endembed %} ## Summary * **Python** is the clear programming language of choice. * **Visual Studio Code** makes for a very nice Python experience, with features such as built-in git staging and diffing, peek documentation, and linter code hints. * **PyCharm** is a popular choice for Python developers. * **Jupyter Notebooks** is the standard tool for quick prototyping and exploratory analysis, but it is not suitable to build machine learning products. * **Streamlit** is a new tool that fulfills a common need - an interactive applet to communicate the modeling results. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://fall2019.fullstackdeeplearning.com/course-content/infrastructure-and-tooling/software-engineering.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.