That's interesting! I didn't realize there had been prior dataframe libraries in Python!
Out of curiosity, what was/were the previous libraries?
281 karma · joined February 1, 2022
Out of curiosity, what was/were the previous libraries?
I'm so sorry.
One could also argue that dataframes are basically in-memory database tables. And in that case, S and SQL probably tie in terms of the creation timeline.
I've always heard that they're currently mostly using C++ (and sometimes Java). But I'm not sure how dogmatic or change-averse they are on average.
--Dutch proverb
For anyone working with GIS data, it's absolutely worth investigating what PostGIS provides and the ease of integration to your existing application!
JavaScript is a really interesting case; initially, I don't think it was really taken very seriously. It was mostly tolerated because of its privileged status as part of the web platform. But since so much has moved from desktop application to the browser, that privileged status has proven all the more valuable!
They have poured an enormous amount of time and effort into CUDA and its related libraries. All of that work—in addition to the hardware—is what makes their moat deep and wide. If AMD and/or others invest similarly in ROCm, that will be very telling. Oh, and the work that the Mojo folks are doing is also very interesting; I could also see that as a looming threat for NVIDIA!
Josh’s teaching style is exceptional, and the courses’ exercises challenge you to work just at the edge of your abilities. I cannot recommend these courses enough!!
I'm curiously watching Intel and their OneAPI platform; but it just feels like they're starting from so far behind. And Intel hasn't exactly had a stellar few years on top of that.
Suppose we have a big HPC cluster, and suppose also that this is a fairly heterogeneous cluster in terms of CPU architectures. We might have, for example, 3 different generations of Intel chips. We would also have several different compilers, and several versions of MPI (e.g., OpenMPI, MVAPICH, etc.).
Using Spack, it is trivially simple to build a piece of software with all possible combinations of compiler-architecture-MPI.
Spack also integrates very nicely with LMOD, so managing Spack installs using the LMOD module system is extremely convenient.
I would also argue that the user experience with Spack is phenomenal, but that's just a personal preference.
https://directory.brown.edu/uuid/0525f19f-d156-4c47-a2e1-8b4...
The Brown University Center for Computation and Visualization (CCV) is a research computing center with a team of data scientists, research software engineers, system administrators, and other technologists. We partner with researchers across the Brown University community, as well as the associated hospital partners. We work on problems that span a huge continuum of subject matter areas. We currently have several long-running collaborations with researchers across many disciplines (e.g., neuroscience, computational biology, computer vision, psychiatry, sociology, engineering, environmental science, public health).
Our data scientists and research software engineers partner with researchers to solve hugely diverse problems. The nature of our work varies considerably depending on the projects, but we consistently have research projects that involve machine learning, web app development, mobile apps, high-performance computing (HPC), genomics data, VR/AR.
Our general tech stack includes: Python, R, Julia, Rust, Node, Vue, React, MySQL, Postgres, Docker, and GCP. In addition, on the HPC side of the house we add to that: C, C++, Fortran, and CUDA.
We have a few roles open now, and plan to have more in the coming months. We especially encourage folks from historically under-represented groups to apply. The postings are listed at the link below. Check us out; we'd love to hear from you!!
The Brown University Center for Computation and Visualization (CCV) is a research computing center with a team of data scientists, research software engineers, system administrators, and other technologists. We partner with researchers across the Brown University community, as well as the associated hospital partners. We work on problems that span a huge continuum of subject matter areas. We currently have several long-running collaborations with researchers across many disciplines (e.g., neuroscience, computational biology, computer vision, psychiatry, sociology, engineering, environmental science, public health).
Our data scientists and research software engineers partner with researchers to solve hugely diverse problems. The nature of our work varies considerably depending on the projects, but we consistently have research projects that involve machine learning, web app development, mobile apps, high-performance computing (HPC), genomics data, VR/AR.
Our general tech stack includes: Python, R, Julia, Rust, Node, Vue, MySQL, Postgres, Docker, and GCP. In addition, on the HPC side of the house we add to that: C, C++, and CUDA.
We have a few roles open now, and plan to have more in the coming months. We especially encourage folks from historically under-represented groups to apply. The postings are listed at the link below. Check us out; we'd love to hear from you!!
I'd also be curious what others recommend!
https://cjolowicz.github.io/posts/hypermodern-python-01-setu...
Ecolumix is a pre-seed environmental technology startup. We are a mission-driven organization aiming to transform the evaluation of companies’ environmental impact. Our approach differs from legacy competitors (e.g., MSCI, Sustainalytics, etc.) in that we rely only on actual data—not platitudes and euphemisms found in corporate sustainability reports and letters to shareholders.
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We are looking for generalist software engineers and data engineers. In terms of technology, we use mostly Rust, Vue, Julia, Python, PostgreSQL, and GCP.
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