Take a look at SageMath <https://www.sagemath.org/> (https://www.sagemath.org/), which does pulls together lots of disparate packages. I have used it and even contributed to it. I recommend it for people doing pure math or sophisticated niche work. However, It has historically been too heavy-weight and difficult to use correctly for the applications I have in the physical sciences and teaching. They are working towards making installable with pip, which may help with some of my issues.
Jonathan On Thursday, August 31, 2023 at 8:57:57 PM UTC-5 syle...@gmail.com wrote: > Thanks for the blog post. > > Unfortunately, I'm outside from using SymPy recently because > I'm now mainly involved in projects that use React and Typescript heavily, > > However, I particularly find things like mathjs > josdejong/mathjs: An extensive math library for JavaScript and Node.js > (github.com) <https://github.com/josdejong/mathjs> > cortex-js/compute-engine: An engine for symbolic manipulation and numeric > evaluation of math formulas expressed with MathJSON (github.com) > <https://github.com/cortex-js/compute-engine> > to be interesting, and had got me the impression that > small symbolic expression system, without automatic evaluation, is still > very useful by itself. > > And although SymPy, being fully featured CAS, with many features, easy to > use, > had not got a good reputation that it is best at something, or it is best > at anything at all. > It seemed like having having CAS not being best at performance or > having it too opinionated and limits about what kind of math it can do, > pushed me away from using general computer algebra systems, > to more dedicated matrix, algebra, polynomial libraries. > > However, I just want to tackle that this problems may come from monolithic > software designs of computer algebra systems. > Although `arb`, `flint` or `gmpy` achieves best performance at one > specific math, > However, they don't really seem like restricting what you can build on top > of it. > I have got a similar opinion, that CAS should be minimal like basic > operating system that only connects the modules, > and start to have the boundary of what should be inside it or what should > be built on top of it. > > On Monday, August 21, 2023 at 3:35:01 PM UTC-5 da...@dbailey.co.uk wrote: > >> On 21/08/2023 21:01, Aaron Meurer wrote: >> >> Thanks Aaron for your amazingly fast response! >> >> > The main reason Oscar benchmarked matrices is that that's the part of >> > SymPy that he's focused on making faster so far. Actually, matrices >> > are more important than you'd think. They end up being used internally >> > in many calculations, in places like the solvers or integrals, so >> > making matrices faster will also make other parts of SymPy faster. >> > >> > But actually, matrix inverse and your series example are very similar. >> > They both produce unwieldy expressions when computed naively. But >> > these expressions are much simpler if they are simplified: >> >> If Oscar had mentioned that, I would never have written that reply - >> perhaps he forgot that he was not talking to a SymPy developer! >> >> Is there a readable account explaining how the internals of SymPy >> perform their algebraic/calculus manipulations? >> >> David >> >> -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sympy+unsubscr...@googlegroups.com. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/f8994e03-6215-4872-a8ac-28ae31837984n%40googlegroups.com.
