# Matlab/Scilab/Python/Julia cheatsheet **URL:** \ **Category:** General usage\ **Created:** [October 22, 2025, 3:49pm UTC](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066 "2025-10-22T15:49:57Z")\ **Posts on this page:** 5\ **Page:** 1
**Author:** ![mottelet](https://yyz2.discourse-cdn.com/free1/user_avatar/scilab.discourse.group/mottelet/32/13_2.png) [@mottelet](https://scilab.discourse.group/u/mottelet)\ **Post date:** [October 22, 2025, 3:49pm UTC](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066/1 "2025-10-22T15:49:57Z")
Hello, Chris Rackauckas released this excellent cheatsheet ([Scientific Modeling Cheatsheet – MATLAB – Python – Julia Quick Reference](https://sciml.github.io/Scientific_Modeling_Cheatsheet/scientific_modeling_cheatsheet)) which shows, for those who are not already convinced, that Julia not only brings the better of two worlds in terms of user accessibility and syntax (Matlab, Python) but also provides (among others) seamless and advanced automatic differentiation features. I thought that this cheatsheet diserved a new column, as Scilab and Matlab share more features and language idioms than one could think, hence I made an upgraded version with a “Scilab” column which can be found there: [Scientific Modeling Cheatsheet – MATLAB – Scilab - Python – Julia Quick Reference](https://www.utc.fr/~mottelet/scilab/Scientific_Modeling_Quick_Reference.html). Compared to the original version of the sheet you can easily hide/show columns if you want to compare e.g. only two softwares. As a teaser, here is a screenshot of a section of the sheet: ![Screenshot 2025-10-22 at 18.02.37](https://global.discourse-cdn.com/free1/uploads/utc/original/1X/3ff2aa98433ca9c91a6cd844a1e023c08e954ffc.png) S. ---
**Author:** ![mottelet](https://yyz2.discourse-cdn.com/free1/user_avatar/scilab.discourse.group/mottelet/32/13_2.png) [@mottelet](https://scilab.discourse.group/u/mottelet)\ **Post date:** [October 24, 2025, 7:20am UTC](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066/2 "2025-10-24T07:20:24Z")
In fact Chris merged the Scilab update in the original cheatsheet > **[Scientific Modeling Cheatsheet – MATLAB – Scilab – Python – Julia Quick...](https://sciml.github.io/Scientific_Modeling_Cheatsheet/scientific_modeling_cheatsheet)** and contributions to it can be made at > **[GitHub - SciML/Scientific\_Modeling\_Cheatsheet: Scientific Modeling Cheatsheet MATLAB – Python –...](https://github.com/SciML/Scientific_Modeling_Cheatsheet)** > > Scientific Modeling Cheatsheet MATLAB – Python – Julia Quick Reference: MATLAB – Python – Julia Quick Reference ---
**Author:** ![davcheze](https://avatars.discourse-cdn.com/v4/letter/d/90db22/32.png) [@davcheze](https://scilab.discourse.group/u/davcheze)\ **Post date:** [November 7, 2025, 4:08pm UTC](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066/3 "2025-11-07T16:08:02Z")
Hello Stephane, it seems some blanks left during the merge of [reference](https://www.utc.fr/~mottelet/scilab/Scientific_Modeling_Quick_Reference.html) with Chris Rackauckas’s reference, around `sort` and `eigenvalues ,`missing gsort and eigs for Scilab ? David ---
**Author:** ![mottelet](https://yyz2.discourse-cdn.com/free1/user_avatar/scilab.discourse.group/mottelet/32/13_2.png) [@mottelet](https://scilab.discourse.group/u/mottelet)\ **Post date:** [November 12, 2025, 8:27am UTC](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066/4 "2025-11-12T08:27:40Z")
Thanks for signaling, I have made a PR to fix it: > > > \## Checklist > > \- \[\] Appropriate tests were added > \- \[\] Any code changes were …done in a way that does not break public API > \- \[\] All documentation related to code changes were updated > \- \[\] The new code follows the > \[contributor guidelines\](https://github.com/SciML/.github/blob/master/CONTRIBUTING.md), in particular the \[SciML Style Guide\](https://github.com/SciML/SciMLStyle) and > \[COLPRAC\](https://github.com/SciML/COLPRAC). > \- \[\] Any new documentation only uses public API > > \## Additional context > > Add any other context about the problem here. ---
**Author:** ![davcheze](https://avatars.discourse-cdn.com/v4/letter/d/90db22/32.png) [@davcheze](https://scilab.discourse.group/u/davcheze)\ **Post date:** [November 14, 2025, 10:02am UTC](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066/5 "2025-11-14T10:02:28Z")
Hello, I’m happy as well and grateful to Scilab developers for the development of the extension of [objects features in Scilab](https://scilab.discourse.group/t/objects-in-scilab/1058) ! At the moment the question arises in my job to translate in Scilab existing Matlab or Python interfaces/gateways to experimental databases and these gateways are using objects features extensively, in Matlab and Python respectively. Then, in order to choose the most straight approach, I’m wondering which from Matlab or Python gateway is likely to deploy the objects features concepts the closest to Scilab ones, and highlighting the differences. And it comes to my minf that it could be more or less an interesting extension to languages’ objects features of the current [Matlab/Scilab/Python/Julia cheatsheet](https://scilab.discourse.group/t/matlab-scilab-python-julia-cheatsheet/1066) : I’m not familiar with Matlab objects philosophy nor Python ones, do someone already have answers about that ? Part of the the information would also suit well in the Scilab documentation at the `Code Matlab => Scilab` entry, also to be extended with the new Objects in Scilab features. Thank you for the discussion, David