1 | initial version |

As I understand, the slowness is not related to the conversion to Sympy. The point is that your expressions become huge, and that's why Sage becomes slow to perform operations (be it conversion or anything else). The solution is to simplify your expression while doing the computations. Below is an example of such simplifications you can add (the complete computation takes 1.27s on my laptop). Note that there may be better strategies (apply `simplify_rational`

to more, or on the contrary less, expressions to optimize computation time). At least, I obtain reasonable computation times:

```
C = matrix(SR, 3, 3, var('C11, C12, C13, C21, C22, C23, C31, C32, C33'))
F = matrix(SR, 3, 3, var('F11, F12, F13, F21, F22, F23, F31, F32, F33'))
Cg = matrix(SR, 3, 3, var('Cg11, Cg12, Cg13, Cg21, Cg22, Cg23, Cg31, Cg32, Cg33'))
Fg = matrix(SR, 3, 3, var('Fg11, Fg12, Fg13, Fg21, Fg22, Fg23, Fg31, Fg32, Fg33'))
Fg_inv = Fg.inverse().simplify_rational()
Ce = (Fg_inv.T*C*Fg_inv).simplify_rational()
Fe = (F*Fg_inv).simplify_rational()
Cedet = Ce.det().simplify_rational()
Je = sqrt(Cedet)
W = ((Je-1)^2).expand().simplify_rational()
S_PK = matrix(SR, 3,3, jacobian(W, C.list()).list()).simplify_rational()
S = Fe*S_PK*Fe.T*Je**(-1)
CF = F.T*F
S00 = S[0,0].substitute([(C.list())[i]==(CF.list())[i] for i in xrange(9)])
out1 = S00._sympy_()
```

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