The Labs team shares their news, updates, and knowledge

Posts, articles and tutorials

blog

header

Quansight Labs is delighted to welcome its second cohort of 6 interns, who will work on a variety of open source projects and tasks

Introducing the 2022 Interns Cohort

Announcing the SciPy 2022 Accessibility Awareness Efforts

SciPy 2022 Accessibility Awareness Programs

A non-exhaustive but totally honest checklist for accessibility review

Checking for accessibility: thoughts and a checklist!

The development story of a developer command-line interface (CLI) for the SciPy project, with exmaples

The evolution of the SciPy developer CLI

In our weekly show and tell we got real about "why can writing blog  posts be so hard?" and collaboratively wrote up this blog post about what we learned  from the discussion.

Why is writing blog posts hard?

How we can use the Python Array API Standard with the fundamental libraries in the PyData ecosystem along with CuPy for making GPUs accessible to the users of these libraries

Making GPUs accessible to the PyData Ecosystem via the Array API Standard.

The Chan Zuckerberg Initiative has funded efforts to make the Jupyter ecosystem, starting with JupyterLab, more accessible. As a part of these increased efforts, the team will be providing a periodically updated list of what is currently being worked on and what is coming soon.

Jupyter accessibility efforts have a roadmap!

Grayskull is an automatic conda recipe generator, with a focus on conda-forge.

Conda and Grayskull, the Masters of Software Packaging

This is a companion post from the Official release of IPython 8.0. We hope it will help you apply best practices, and have an easier time maintaining your projects, or helping other.

IPython 8.0, Lessons learned maintaining software

A lot of us showed up for the code, but hung around for the community. We'll continue this post talking about the monthly Jupyter community calls, and how they help all jovyans, Project Jupyter's pet name for their developers and users, stay connected.

A year of Jupyter community calls

In this post, we aim to articulate that vision and suggest a path to making it concrete, focusing on three libraries at the core of the PyData ecosystem: SciPy, scikit-learn and scikit-image. 

A vision for extensibility to GPU & distributed support for SciPy, scikit-learn, scikit-image and beyond

My work was majorly focused on providing performance benchmarks to NumPy in realistic situations. The target was to show the world that NumPy is efficient in handling quasi real-life situations too.

NumPy Benchmarking

In the next lines, I"ll try to capture my experience at Quansight Labs as an intern working on the cuDF implementation of the dataframe interchange protocol. cuDF is a dataframe library very much like pandas which operates on the GPU in order to benefit from its computing power.

Dataframe interchange protocol: cuDF implementation

An exploration of a method to call C++ libarary function from Numba compiled functions, i.e. python function that are decorated with "numba.jit(nopython=True)"

An efficient method of calling C++ functions from numba using clang++/ctypes/rbc

We are thrilled to announce that the team at Quansight Labs has been awarded five EOSS Cycle 4 grants to work on several projects within the PyData ecosystem. This post will introduce the successful grantees and their objectives for these two-year long grants.

CZI EOSS4 Grants at Quansight Labs

Instead of going through all the complications involved in renting or acquiring dedicated hardware, setting up credentials and monitoring costs of a benchmarkin suite, we hoped we could use the same free cloud resources normally used for CI tests. Ideally, GitHub Actions.

Is GitHub Actions suitable for running benchmarks?

SciPy now builds with Meson on Linux, and the full test suite passes! This is a pretty exciting milestone, and good news for SciPy maintainers and contributors - they can look forward to much faster builds and a more pleasant development experience.

Moving SciPy to the Meson build system

In this blogpost we present pyflyby, a project and an extension to IPython and JupyterLab, that, among many things, automatically inserts imports and tidies Python files and notebooks.

Pyflyby: Improving Efficiency of Jupyter Interactive Sessions

Today I want to look into a topic that has not evolved much since, and I believe could use an upgrade. Accessing interactive Documentation when in a Jupyter session, and what it could become. At the end I"ll link to my current prototype if you are adventurous.

Rethinking Jupyter Interactive Documentation

Starting from Numba 0.53, Numba will ship with an enhanced version of the @guvectorize decorator. Similar to the @vectorize decorator, @guvectorize now has two modes of operation: Eager, or decoration-time compilation and Lazy, or call-time compilation

Enhancements to Numba's guvectorize decorator

In this blog post we will focus specifically on recent improvements that have been made to SciPy's interpolation functions. A recent NumFOCUS small development grant awarded to the SciPy developers allowed a dedicated effort to fix existing bugs in boundary handling and improve the documentation of the behavior of these modes.

Making SciPy's Image Interpolation Consistent and Well Documented

In the following blog post, we will show you step-by-step how you can develop a custom theme for JupyterLab, distribute it, and take the example of the jupyterlab-theme-winter theme we release today to celebrate the end of 2020.

Develop a JupyterLab Winter Theme

This new grant totaling $140,000 will fund part of our efforts to improve usability and sustainability in both projects and is excellent news for the scientific computing community, which will certainly benefit from this work downstream.

A second CZI grant for NumPy and OpenBLAS

We'll highlight the ability of Ibis to generically prescribe query expressions across different data storage systems.

Querying multiple backends with Ibis

The basic installation format for users who install packages via pip is the wheel format. But what about Linux? The first manylinux standard, manylinux1, was based on CentOS5 which has been obsolete since March 2017. So what is next for manylinux, and what manylinux should users and package maintainers use?

Manylinux1 is obsolete, manylinux2010 is almost EOL, what is next?

You have probably seen Traitlets in applications, you likely even use it. The package has nearly 5 million downloads on conda-forge alone. But, what is Traitlets? In this post we'll answer this question along with where Traitlets came from, its applications, and a bit of history.

Traitlets - an introduction & use in Jupyter configuration management

I recently moved, and my new place has a relatively small footprint. (Yes, I moved during the COVID-19 pandemic. And yes, it was crazy.) I quickly realized that was going to need a wireless router of some sort, or more formally, a wireless access point (WAP).

Learn NixOS by turning a Raspberry Pi into a Wireless Router

A demonstration of a method to create a copy an exact dev environment on
one machine, and transfering it to a another machine.


Creating a Portable Python Environment from Imports

This post is a deep dive into how TensorIterator works, and is an essential part of learning to contribute to the PyTorch codebase since iterations over tensors in the C++ codebase are extremely commonplace. This post is aimed at someone who wants to contribute to PyTorch

PyTorch TensorIterator Internals

Having official high-level documentation written using up-to-date content and techniques will certainly mean more users (and developers/contributors) are involved in the NumPy community. So, if everybody agrees on its importance, why is it so hard to write good documentation?

Documentation as a way to build Community

TDK-Micronas is sponsoring Spyder development efforts through Quansight Labs. This will enable the development of some features that have been requested by our users, as well as new features that will help TDK develop custom Spyder plugins in order to complement their Automatic Test Equipment (ATE’s) in the development of their Application Specific Integrated Circuits (ASIC’s).