In November 2022, the Chan Zuckerberg Initiative (CZI) awarded the Scientific Python project with a grant to improve communications infrastructure and accessibility. This proposal involves several key areas to improve sustainability, inclusivity and accessibility of the Scientific Python ecosystem. One of these areas is making software documentation and user interfaces available in multiple languages. We are happy to announce that we have organized the necessary infrastructure and processes to allow volunteers to start translating multiple project websites.

In this blog post, we will discuss how we set up manage translations for Scientific Python projects, and how you can participate in the translation and localization effort. The work described here was done by Quansight Labs.

Why translations are important#

Accessibility and inclusion are important aspects of building a healthy community around open source software development. By providing translations of our websites, documentation and user interfaces in multiple languages, we can reach a wider global audience, thereby making our projects more inclusive and increasing the diversity of contributions and ideas. This is especially important for scientific software projects, which are used by researchers and scientists from around the world with a wide range of language proficiencies and backgrounds.

Recently, machine translation tools have made it easier to translate content into multiple languages. While such tools are improving, they often fall short in the context of technical documentation. In addition, without a human in the loop, maintainers can never be sure if translated content is correct for languages they are not familiar with. For this reason, we chose to work with a group of volunteers to help us translate selective subsets of project websites and documentation.

Setting up translations workflow#

You may have seen that translations into some languages are already available for numpy.org, with a version switcher in the top right corner.

A number of core projects have also joined this effort and are set up to start with translations. At the moment, we are targeting NumPy, SciPy, NetworkX, Xarray, and pandas. We’re offering to help other core projects integrate something similar into their websites, and we aim to accomplish this in a way that requires minimal effort from the core project maintainers, using Crowdin.

For the moment, our scope is to translate only the projects’ websites—the landing pages you see when you check out the links above—and not full documentation. We are intentionally starting small with the goal of completing this first phase and then potentially expanding once the translations team is established.

Translations team#

For new contributors who are looking to get involved in the projects they already use and depend on, joining the translations team can be a great way to get started. Because of how the translations infrastructure is set up in Crowdin, this workflow is particularly well-suited for new contributors who are not yet familiar with GitHub or other development tools—they can work entirely on the Crowdin web platform.

One advantage of setting this up at the Scientific Python level, and not on a per-project basis, is that the translations team can work on multiple projects, and knowledge and experience can be shared. This also helps to ensure that translations are consistent across projects.

The translations team will be responsible for:

• Translating (and reviewing) content into multiple languages;
• Ensuring that translations are accurate and up-to-date;
• Engaging with the community to help maintain and improve translations.

Once the translations are complete and reviewed, a maintainer for each project can merge the translations and publish them to the project website. After the initial setup, the translations team will be able to manage the translations workflow independently, with minimal input from the project maintainers.

For more information on the infrastructure and team working on the translations, and how to join as a translator, see https://scientific-python-translations.github.io/. You can also join the #translation channel at the Scientific Python Discord server.

We are delighted to announce a two-year grant from the Chan Zuckerberg Initiative (CZI) in support of the Scientific Python project. This grant will support work on common web themes, joint infrastructure and practices, accessibility, and interactivity of core library documentation. We are particularly excited that, through this work, we may expand global participation of scientific communities in using and contributing to Python tools. It is, to the best of our knowledge, the first time that a scientific open source community has received significant support for accessibility and internationalization efforts.

CZI & Scientific Python#

CZI continues to support many impactful and innovative projects in the scientific Python community through its Essential Open Source Software for Science (EOSS) program. Today, they announced the 5th funding cycle of that program. This grant to Scientific Python, while outside the EOSS program, complements it well. Among other things, the Scientific Python project aims to support, document, and make accessible common practices & infrastructure. Such infrastructure will benefit not only the projects at the core of the ecosystem, but also those well beyond it.

“We are thrilled to partner with the Scientific Python project, an effort to harmonize a critical set of open source research software projects widely used across all the areas of biomedical research that CZI supports. The distributed nature of the scientific open source ecosystem will greatly benefit from their efforts to standardize best practices and focus on ecosystem-level initiatives,” said Dario Taraborelli, Science Program Officer at the Chan Zuckerberg Initiative.

What will we be working on?#

This grant will support core scientific Python projects by doing release management, writing documentation, building and supporting joint infrastructure, and by measuring and publishing metrics on community involvement and project health. In addition, here are some specific deliverables:

Common web themes#

There are two web themes commonly deployed on community sites: the Scientific Python Hugo Theme—for project websites, and the pydata-sphinx-theme—for documentation. We will improve these themes, effectively upgrading several project websites simultaneously. By fostering theme adoption, we will help the ecosystem present a more unified front to users, while reducing the web maintenance burden on developers. Other theme work includes better responsive layouts (important for use on mobile and tables), blogging facilities, increased usability, and accessibility compliance.

Adopting and promoting access-centered practices#

Better accessibility of online resources increases usability for everyone, while fostering community participation and inclusion. The Scientific Python Hugo Theme and pydata-sphinx-theme are natural conduits for introducing accessibility standards and best practices to the broader ecosystem. We will develop access-centered best practices and contribution guidelines, organize online workshops, and work with other maintainers to improve their projects’ documentation and homepage accessibility. A set of access-centered practices will be written up as a Scientific Python Ecosystem Coordination document (or SPEC, for short), to provide guidance to those projects we cannot support directly.

A key aim of this work is to have web and documentation themes, as well as core scientific Python project websites, meet the applicable Web Content Accessibility Guidelines.

Interactive documentation & translations#

Documentation is key to a project’s success, and good documentation is approachable to end users with a wide range of backgrounds and skills. While most scientific Python projects value documentation and work hard at it, there is still much room for improvement.

One such improvement is translation and localization. Development takes place in English, as reflected by project websites and documentation. While many contributors are comfortable with English as a first, second, or even third language, the language barrier excludes especially users that are very young, are new to the community, have learning disabilities, or are from the Global South—all potential future contributors and leaders in the scientific Python community! We will therefore translate key pages of core project websites, and provide translation infrastructure for the web themes.

A second area of improvement is interactivity. Interactive project documentation has the potential to engage less experienced users, making it easier to experiment with and teach ecosystem libraries. We will work on documentation interactivity by providing seamless, in-browser execution of code via JupyterLite, a WebAssembly Jupyter distribution.

Who will be involved#

The four PI’s for this grant are Stéfan van der Walt (UC Berkeley; NumPy, scikit-image, SciPy; Scientific Python Hugo Theme), Tania Allard (Quansight Labs; JupyterHub, NumFOCUS DISC, Jupyter accessibility), Jarrod Millman (Scientific Python; NetworkX; scikit-image; Scientific Python Hugo Theme, pydata-sphinx-theme), and Ralf Gommers (Quansight Labs; SciPy, NumPy, data-apis.org). Melissa Weber Mendonça (Quansight Labs; NumPy, SciPy) and Chris Holdgraf (2i2c; Project Jupyter, MyST, pydata-sphinx-theme) will participate as key personnel, providing expertise in documentation and Sphinx themes in particular. Jarrod and Stéfan are co-creators of the Scientific Python project, and everyone on the grant has been involved in the larger scientific Python ecosystem and community for many years.

Next steps#

Today was announcement day, but the real work starts in December. Some topics we’ll be able to dive straight into; others will require hiring—and we’re excited to involve new web designers, accessibility experts, and engineers in this journey. Stay tuned—there’s a lot more to come!

To connect with the team, and to follow job posts, please join us at https://discuss.scientific-python.org.