A Jupyter kernel for the Maxima computer algebra system, enabling interactive notebooks for symbolic mathematics.
A Maxima kernel for Jupyter, based on CL-Jupyter (Common Lisp kernel)
Leverages Maxima's full capabilities for algebra, calculus, and equation solving, as shown in examples like MaximaJupyterExample.ipynb, providing robust symbolic computation within notebooks.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Enables rich, cell-based workflows with input/output history and embedded plots, transforming Maxima into a modern notebook environment for exploratory analysis.
Supports local installation, Docker images, and repo2docker, catering to diverse setups from personal machines to cloud deployments, as detailed in the README's installation sections.
Offers specific instructions for Windows and Unix-like systems, including Arch Linux via AUR, making it accessible across major operating systems despite setup complexities.
Requires a Maxima build with specific Lisp implementations (e.g., SBCL or CCL), Quicklisp setup, and manual steps, especially on Windows where PATH editing and conda installations are needed, as admitted in the README.
The README notes that CodeMirror mode and Pygments lexer support are pending, leading to poor syntax highlighting in notebooks and HTML exports until future updates.
Only works with Maxima compiled on Lisp implementations supporting Bordeaux Threads, excluding GCL and ECL, which limits usability with pre-existing Maxima installations.
Relies on Quicklisp to automatically download dependencies during first load, which the README warns might fail unpredictably, adding risk to the setup process.