lambdify

I would like to lambdify the function Integral(t**t,(t,0,x)) . It works, but my new function, which was returned by lambdify , doesn't return a number but only sympy.integrals.integrals.Integral class. But I don't want that, I want it to return a float number. Here is my code: import sympy as sp import numpy as np f = sp.lambdify(x,sp.integrate(t**t,(t,0,x))) print(f(2)) #return Integral(t**t, (t, 0, 2)) #but i want 2.83387674524687 lambdify doesn't support scipy.integrate.quad directly yet , but it's not difficult to add the appropiate definition. One simply needs to tell lambdify how to

My website runs this Python script that would be way more optimized if Cython is used. Recently I needed to add Sympy with Lambdify , and this is not going well with Cython. So I stripped the problem to a minimum working example. In the code, I have a dictionary with string keys with values that are lists. I would like to use these keys as variables. In the following simplified example, there's only 1 variable, but generally I need more. Please check the following example: import numpy as np from sympy.parsing.sympy_parser import parse_expr from sympy.utilities.lambdify import lambdify,

I am trying to do partial derivatives using sympy and I want to convert it to a function so that I can substitute values and estimate the derivatives at some values of t_1, t_2. The code I am using is as follows: import sympy as sp import numpy as np from sympy import init_printing init_printing() t_1,t_2,X_1,X_2,Y_1,Y_2,X_c1,X_c2,Y_c1,Y_c2,a_1,a_2,psi_1,psi_2,b_1,b_2= sp.symbols('t_1 t_2 X_1 X_2 Y_1 Y_2 X_c1 X_c2 Y_c1 Y_c2 a_1 a_2 psi_1 psi_2 b_1 b_2') X_1=X_c1 + (a_1 * sp.cos(t_1) * sp.cos(psi_1)) - ((b_1) * sp.sin(t_1)* sp.sin(psi_1)) X_2=X_c2 + (a_2 * sp.cos(t_2) * sp.cos(psi_2)) - ((b_2)