" Hi Peter, thank you for the question! , by 'solver' I meant the
high-level sympy.solve() function. Specifically, I’ve been investigating
performance bottlenecks when equations contain floating-point exponents.
I recently opened an issue (*#29180*) regarding solve() hanging on
expressions like $x^{5.43}$. I found that the 'hang' occurs because SymPy
converts these to very high-degree rationals and attempts expensive
symbolic factorization (Zassenhaus/Hensel lifting).
While my issue was noted as a duplicate of *#11493*, seeing this bottleneck
firsthand is what motivates my interest in 'Efficient Equations of Motion
Generation.' In multibody mechanics, empirical force models often use such
exponents, and I want to ensure the Mechanics package can handle or bypass
these core symbolic limitations to remain performant."
On Sunday, February 22, 2026 at 12:09:00 PM UTC+6 [email protected]
wrote:
> I am a user of sympy.physics.mechanics, Kane's method only.
> Just curiosity: you say, you have been experimenting with the solver.
> What do you mean by solver?
> Thanks1
>
> shuvro bhattacharjee schrieb am Samstag, 21. Februar 2026 um 21:57:40
> UTC+1:
>
>> My name is Shuvro Bhattacharjee. I’m a 4th-year Computer Science and
>> Engineering student from Bangladesh, and I’m very interested in
>> contributing to SymPy for GSoC 2026.
>>
>> I’ve been exploring the project ideas and the one that stands out to me
>> is *"Classical Mechanics: Efficient Equations of Motion Generation."*
>> I’m particularly interested in this because it combines my background in
>> Python with my interest in performance optimization.
>> I’ve been experimenting with the solver and noticed that some
>> expressions (like those with high-degree float exponents) can take a long
>> time to process. It made me curious about how we can use profiling to find
>> bottlenecks in the Mechanics package, especially when generating Kane's or
>> Lagrange's equations.
>> Also I’ve been looking into the sympy.physics.mechanics module and how it
>> handles Kane’s and Lagrange’s methods.
>>
>> I would appreciate your guidance on how best to get started.
>>
>> Thank you for your time . I look forward to contributing to Sympy.
>>
>> Best regards,
>>
>> Shuvro Bhattacharjee
>>
>> 1.
>>
>> Best regards,
>> Shuvro Bhattacharjee
>> 2.
>>
>>
>>
>> 1.
>>
>> Best regards,
>> Shuvro Bhattacharjee
>> 2.
>>
>>
>>
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