I made a little extension to my Python-based LaTeX math renderer so it can be used to draw equations and Sympy expressions directly in the terminal as sixel graphics. Install with `pip install sixelmath` and give it a try! (in a sixel-supported terminal, of course).

Source: https://github.com/cdelker/sixelmath

#sixel #python #sympy #TeXLaTeX #terminal #equations #ziamath #konsole

#Python : Malicious #PyPI Package called 'sympy-dev' Impersonates #SymPy, Deploys XMRig Miner on Linux Hosts:

#SoftwareSupplyChainSecurity
👇
https://thehackernews.com/2026/01/malicious-pypi-package-impersonates.html

Malicious PyPI Package Impersonates SymPy, Deploys XMRig Miner on Linux Hosts

A fake sympy-dev package on PyPI impersonates the SymPy library to download and run XMRig cryptominers on Linux using in-memory execution.

The Hacker News

I don't know why I haven't used sympy before. I think I looked into it around 10 years ago, and I didn't appreciate the potential at the time. From playing around with it today, it's a capable symbolic math library. The documentation is rich as well. I really like it!
https://www.sympy.org/en/index.html

#sympy
#python
#symbolicMath

1/n

SymPy

The hermite function f(x)=3x²-2x³ (basis of smoothstep) is a mix of the in and out easing of x²:

>>> a,b,x = symbols('a b x', real=True)
>>> mix = a*(1-x)+b*x
>>> f_in = x**2
>>> f_out = 1-f_in.subs({x:1-x})
>>> f_in_out = mix.subs({a:f_in, b:f_out, x:x}).simplify()
>>> f_out_in = mix.subs({a:f_out, b:f_in, x:x}).simplify()
>>> hermite = 3*x**2-2*x**3
>>> hermite.simplify() == f_in_out
True

#sympy #math #animation

I just went mental for an hour with #sympy because I declared two symbols like that: n,t=symbols('t n')

I ended up with the most surprising #math identities ever...

Still writing my #AdventOfCode explainer #blog . To make it easier to explain the #algebra of one puzzle, I'm using #SymPy in as succinct and limited a way I can.

#AdventOfCode2023 #programming #Python #code

Hello Mathstodon community.

I'm an independent researcher from a systems design background, and I'm exploring the geometry of a specific golden disphenoid I call 'ANNA'.

It's a Tetrahedron composed of 4 congruent 36-72-72 Golden Triangles.

My key finding is that it possesses a pair of opposite edges that are perfectly orthogonal.

To verify this beyond numerical approximation, I wrote a `sympy` script that defines the vertices symbolically using φ. The script computes the dot product of the opposite edge vectors, and `sympy.simplify()` reduces it to exactly 0.

My question: Is this orthogonality a known property of this solid? I'm posting the (short) symbolic script in the reply.

#math #geometry #goldenratio #sympy #python

I was hoping to do a talk on computer assisted algebra with Python's Sympy at PyCon Ireland.

But this year it seems they can't cover the costs of tickets for speakers, or help with travel/accommodation.

That's a shame and I will have to forgo this opportunity :(

#python #maths #sympy

@hisold Citing a plain website or GitHub repo is kinda unprofessional. Many widespead software packages have a publication that is well citable, e.g. #sympy has this one with a proper DOI: https://doi.org/10.7717/peerj-cs.103, same for #numpy, #scipy, #matplotlib, etc. Some have at least a #Zenodo entry (with a DOI) to be properly citable. #PlatformIO apparently has none of those.
SymPy: symbolic computing in Python

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

PeerJ Computer Science

Earn money working on open source software #oss! New project just posted: help make wrappers to connect Symbolics.jl to SymPy. $300 bounty. Information for signing up for the #SciML small grants program are contained in the link:

https://sciml.ai/small_grants/#create_wrapper_functions_to_sympy_for_symbolicsjl_300

#julialang #python #symbolics #sympy #ode