With an extensive and high-quality ecosystem of libraries, scientific Python has emerged as the leading platform for data analysis. This ecosystem is sustained largely by volunteers working on independent projects with separate mailing lists, websites, roadmaps, documentation, engineering and packaging solutions, and governance structures.
The Scientific Python project aims to better coordinate the ecosystem and prepare the software projects in this ecosystem for the next decade of data science.
There is no shortage of blog posts around the web about how to use and explore different packages in the scientific Python ecosystem. However, some of it is outdated or incomplete, and many times doesn’t follow the best practices that would be advocated for by the maintainers of these packages.
In addition, we would like to create a central, community-driven location where Scientific Python projects can make announcements and share information.
Our project aims to be the definitive community blog—for people looking to make use of these libraries in education, research and industry, contribute to them, or maintain them—written, reviewed, and approved by the community of developers and users.
While our core projects (NumPy, SciPy, Matplotlib, scikit-image, NetworkX, etc.) will be regularly contributing content, we also would like to increase the number of contributors by providing support to newer members to generate high-quality, peer-reviewed blog posts.
Our goal is to populate the https://blog.scientific-python.org/ website with high-quality content, reviewed and approved by the maintainers of the libraries in the ecosystem. The main goal of these documents is to centralize information relevant to all (or most) projects in the ecosystem, at the reduced cost of being maintained in one place.
This project aims to:
To ensure this project is successful, it is recommended that the technical writer has some familiarity with at least a few of Scientific Python’s core projects.
We would consider the project successful if:
We anticipate the project to be developed over six months including onboarding five technical writers, reviewing existing material, developing blog post ideas with the project mentors and blog editorial board, writing and revising the blog posts, as well as providing feedback on the submission and review process.
| Dates | Action Items |
|---|---|
| May | Onboarding |
| June | Review existing documentation |
| July | Update contributor guide |
| August–October | Create and edit content |
| November | Project completion |
| Budget item | Amount | Running Total | Notes/justifications |
|---|---|---|---|
| Technical writers (5) | $15,000.00 | $15,000.00 | $3,000 / writer |
| TOTAL | $15,000.00 |
The Scientific Python project is a new initiative, and this is our first time participating in Google Season of Docs. However, both Jarrod Millman and Ross Barnowski are established members of the Python community, with a vast collective experience in mentoring, managing and maintaining large open source projects.
Jarrod cofounded the Neuroimaging in Python project. He was the NumPy and SciPy release manager from 2007 to 2009. He cofounded NumFOCUS and served on its board from 2011 to 2015. Currently, he is the release manager of NetworkX and cofounder of the Scientific Python project.
Both mentors Jarrod and Ross have mentored many new contributors on multiple projects including NumPy, SciPy, and NetworkX. Ross has served as a co-mentor for three former GSoD students on the NumPy project, largely related to generating new content for tutorials, as well as refactoring existing user documentation.
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