CoCalc News
I developed a brand new Python api for using CoCalc!
https://pypi.org/project/cocalc-api/
and you should be able to pip or uv install it as normal.
The docs are at
https://cocalc.com/api/python/
You might want to try a few basic things like:
create an api key in account prefs on cocalc (refresh your browser if you get an error setting the expire date, since I just fixed an issue)
use the api to list your projects,
create a project,
copy files between two projects
Organizations
CoCalc now has a notion of organizations with admins, who can manage users of an organization. This is currently only accessible via this Python API right now. It is designed to make it much easier to build things like asynchronous courses involving Jupyter notebooks, where you want to easily build your own custom workflow and user management instead of using CoCalc's course management UI.
For managing users we will need to create a new "organization" for you and make you an admin of that organization. You can then create users in your org, provide a URL so they can use cocalc (without having to worry about creating accounts themselves), etc. Can you also make projects for them, add them as collaborators to those projects, copy files to their projects (from your own template project), list all members of your org, etc. It's also easy to broadcast a message to all org members.
It's also fairly easy to add new functionality to this API. What is missing that you want? An obvious gap is compute servers, right now.
-- William
Starting today, our default software environment for new projects is based on Ubuntu 24.04. You can still select the previous default, Ubuntu 22.04 (available until June 2025), when creating new projects. While we plan to support Ubuntu 22.04 for a while longer, our main focus going forward will be on Ubuntu 24.04.
Existing projects are unaffected. If you want to switch, you can do this any time via Project Settings → Project Control → Software Environment.
To see what’s included, check out our software inventory.
Programming Languages and Features
Python: There is now a new "CoCalc Python" environment, featuring a curated set of popular packages. This replaces the previously called "system-wide" environment. Terminals now run inside this environment by default. The main benefit is, that this allows to manage Python packages without depending on system-wide packages, installed for system utilities. As before, you can also use the Anaconda-based environment via
anaconda2025
, and we continue to offer a Colab-compatible environment.R: We now provide a broader selection of R packages, powered by r2u, making it easier and more convenient to get started.
SageMath: The latest version of SageMath is available in the new environment. For earlier SageMath releases, please switch to the "Ubuntu 22.04" environment.
LaTeX: This is now running a full and up-to-date Texlive distribution. We plan to update its packages with each new software environment update.
This week, NVIDIA highlighted CoCalc as a key platform for teaching with its CUDA-Q academic materials. In their technical blog post, NVIDIA mentions how CoCalc can provide a seamless learning environment for the next wave of quantum computing specialists.
This might also be a good time to add that we were officially accepted as an NVIDIA Inception Program Member a while back!
Our Chief Sales Officer, Blaec Bejarano, has had the pleasure of meeting Monica Van Dieren, a Senior Technical Marketing Engineer at NVIDIA, at the Joint Mathematics Meeting in Seattle this past January. Their discussions continued at the NVIDIA GTC conference in San Jose in March, solidifying our shared vision for accessible and powerful quantum computing education.
NVIDIA's CUDA-Q Academic program is a comprehensive suite of Jupyter notebooks designed to bridge the gap between theoretical quantum mechanics and practical application. These resources are now readily available via CoCalc, allowing students and instructors to dive into complex topics like quantum machine learning and variational algorithms without the hassle of a complex setup.
The synergy between CoCalc's collaborative platform and NVIDIA's cutting-edge educational content creates an unparalleled learning experience. Students can work through CUDA-Q modules, leveraging CoCalc's powerful computational resources and real-time collaboration features. This integration is particularly highlighted in NVIDIA's post, which notes the ease of getting started on platforms like CoCalc.
For those eager to explore these resources, the CUDA-Q Academic GitHub repository is the perfect starting point: https://github.com/NVIDIA/cuda-q-academic/tree/main?tab=readme-ov-file
We are thrilled to be at the forefront of education, providing the tools necessary to train the quantum workforce of the future. The journey with NVIDIA is just beginning, and we look forward to empowering more learners around the globe.
The software environments "Ubuntu 22.04 (Default)" and "Ubuntu 24.04 (Testing)" now contain the most recent version of SageMath 10.6. You can select the software environment in Project Settings → Project Control → Software Environment. If you're already on the default Ubuntu 22.04 line, then you might have to restart your project to get the latest version.
Apart from that, don't forget to update the Sage Jupyter Kernel to run the latest version 😉
You can now use compute servers very easily with CoCalc's course management system. This video shows how to create a compute server associated to an assignment in a CoCalc course, then make private copies of that compute server available to all students in the class. You can easily set idle timeout, spend limits and a shutdown time for all student compute servers. You can also very easily control some or all servers in a class or install custom software on all servers.
This new functionality is the result of extensive discussions with many teachers who are already using CoCalc in the courses, and want to expand their classes to gives students real experience involving AI, deep learning and more using state of the art GPU's.
https://youtu.be/ikktaiw14Tw?si=_a6HxTRgDeN2NrVg
There are now four new compute server automatic shutdown and health check strategies: idle timeout, shutdown time, spending limit, and generic health check. Each can give you better insight into how your compute servers are used and save you substantial money. This video describes each in detail:
https://youtu.be/Kx_47fs_xcI?si=99Ex4yNQ14IVzkmD
Bridging Theory and Computation in Physics
Transforming Physics Understanding Through Computation
Physics—the study of matter, energy, and their interactions—has always been deeply mathematical. Today, computational methods have become essential tools for understanding complex physical phenomena that resist analytical solutions. CoCalc provides an ideal environment for learning physics through the powerful combination of theoretical understanding and computational exploration.
For information about available scientific computing tools and environments, see the CoCalc documentation.
Whether you're modeling planetary motion, analyzing quantum systems, or exploring electromagnetic fields, CoCalc's integrated tools help you visualize, simulate, and understand the physical world in ways that traditional methods alone cannot achieve.
Your Computational Physics Toolkit
Python for Physics: The Foundation
Python has become the lingua franca of computational physics, offering powerful libraries and intuitive syntax:
Mechanics: Motion and Forces
Start your physics journey with classical mechanics:
Oscillations and Waves
Explore periodic motion and wave phenomena:
Electromagnetism: Fields and Forces
Explore electric and magnetic phenomena:
Thermodynamics and Statistical Mechanics
Explore thermal phenomena and statistical behavior:
Building Physics Intuition
Dimensional Analysis and Scaling
Physics understanding begins with dimensional analysis:
Error Analysis and Uncertainty
Understanding measurement uncertainty is crucial in physics:
Next Steps in Your Physics Journey
Immediate Explorations
Planetary Motion: Simulate orbital mechanics and Kepler's laws
Wave Interference: Explore wave superposition and interference patterns
Quantum Basics: Introduction to wave-particle duality
Thermal Equilibrium: Statistical mechanics fundamentals
Building Toward Advanced Physics
Classical Field Theory: Maxwell's equations and electromagnetic waves
Quantum Mechanics: Schrödinger equation and quantum systems
Statistical Physics: Phase transitions and critical phenomena
Relativity: Special and general relativistic effects
Research Skills Development
Experimental Design: Planning and analyzing physics experiments
Data Analysis: Statistical methods for physics data
Modeling: Creating and validating physical models
Communication: Presenting physics results effectively
Computational physics in CoCalc opens new ways to understand the physical world. Start with fundamental concepts, build your computational skills, and gradually explore more sophisticated phenomena. The combination of theory, computation, and visualization makes complex physics accessible and engaging.
Begin your computational physics journey. Access physics simulations and start exploring at cocalc.com
Join Us at JMM for an Exclusive Meet & Greet and Live Demo with William Stein!
We are thrilled to announce a special opportunity to meet William Stein, the CEO and Founder of CoCalc, at the JMM meeting in Seattle, WA.
Don't miss this chance to engage with William as he presents a live demo of CoCalc! With numerous publications under his belt, William previously served as a tenured professor at the University of Washington until 2019, at which point he committed full-time to growing the CoCalc Platform.
William has made significant contributions to the field of Computational Algebraic Number Theory and is the creator of the Computer Algebra System Sage.
Come find us at booth 507 in the Exhibit Hall during the Grand Opening Reception.