latex2sympy parses LaTeX and generates SymPy symbolic CAS Python code (w/ ANTLR) and is now merged in SymPy core but you must install ANTLR before because it's an optional dependency. Then, sympy.lambdify will compile a symbolic expression for use with TODO JAX, TensorFlow, PyTorch,.
"Ask HN: Did studying proof based math topics make you a better programmer?" Re: lean mathlib https://news.ycombinator.com/item?id=36463580
[Mathematics in mathlib > A mathlib overview]( https://leanprover-community.github.io/mathlib-overview.html )
From https://news.ycombinator.com/item?id=36159017 :
> sympy.utilities.lambdify.lambdify() https://github.com/sympy/sympy/blob/a76b02fcd3a8b7f79b3a88df... :
>> """Convert a SymPy expression into a function that allows for fast numeric evaluation [with the CPython math module, mpmath, NumPy, SciPy, CuPy, JAX, TensorFlow, SymPy, numexpr,]*
From https://westurner.github.io/hnlog/#comment-19084622 :
> "latex2sympy parses LaTeX math expressions and converts it into the equivalent SymPy form" and is now merged into SymPy master and callable with sympy.parsing.latex.parse_latex(). It requires antlr-python-runtime to be installed. https://github.com/augustt198/latex2sympy https://github.com/sympy/sympy/pull/13706
ENH: 'generate a Jupyter notebook' (nbformat .ipynb JSON) function from this stem formula
ENH: Store/export Stem formula attributes as JSON-LD Linked Data and/or RDFa (RDF in HTML Attributes) .
JSON-LD Playground has examples of JSON-LD, as does https://schema.org/CreativeWork : https://json-ld.org/playground/