This repository is forked from cantaro86/Financial-Models-Numerical-Methods, a project by Nicola Cantarutti and contributors. Their extensive and well-documented work on quantitative finance models forms the foundation for this repo-many thanks to the original authors for making their research and code available under open source terms.
See the original README for the full project description.
This fork is being used as a test case for evaluating Marimo (marimo.io), a next-generation Python notebook environment, as an alternative to Jupyter notebooks. The primary goals are:
- Porting and running selected notebooks (starting with “1.1 Black-Scholes numerical methods”) in Marimo.
- Documenting the migration process and any usability differences.
- Comparing features, workflows, and limitations of Marimo and Jupyter for quantitative finance and data science use cases.
- Collecting and sharing pros and cons as discovered through practical use.
Marimo and Jupyter serve somewhat different audiences and use cases. Jupyter is deeply embedded in data science and education, with a huge ecosystem and broad tool support. Marimo, by contrast, is designed for reproducibility, interactivity, and maintainability, with features like:
- Notebooks as pure Python
.pyfiles (easy to version and execute as scripts)6. - Built-in UI elements and reactive execution, eliminating hidden state6.
- Git-friendly, reproducible, and easily shareable as web apps57.
- Automatic dependency tracking and sandboxed execution.
https://marimo-team.github.io/quarto-marimo/
For a detailed technical comparison, see:
- Jupyter vs Marimo: side-by-side (Deepnote) 1
- JupyterLab vs Marimo: side-by-side (Deepnote) 2
- Marimo FAQ: How is Marimo different from Jupyter? 6
- Marimo migration guide for Jupyter users 8
- EuroPython 2025: Meet Marimo, the next-gen Notebook5
- Reddit: Community discussion on Marimo vs Jupyter7
- YouTube: Marimo vs Jupyter walkthrough3
- LinkedIn: Reuven Lerner’s video on Marimo vs Jupyter9
As I progress through the migration and evaluation, I will:
- Update this README (or a dedicated document) with findings, pain points, and advantages discovered.
- Share code examples and workflow notes for both Marimo and Jupyter.
- Highlight any unique Marimo features or limitations relevant to financial modeling and reproducible research.
If you have thoughts, suggestions, or experience with Marimo or Jupyter in quantitative finance, feel free to open an issue or discussion!
Original repo: cantaro86/Financial-Models-Numerical-Methods Marimo: marimo.io