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A possibly cleaner solution (avoiding to define a truckload of unused symbolic variables and scratch needlessly predefined Sage identifiers such as e, I and i...), expressed as a two-liner :

sage: R1.<A,B,C,D,E>=QQbar[]
sage: [u[C] for u in R1.ideal(A - E, A*E - B, B*E - C, C*E - D - 10, D*E + 2).variety()]
[-6.079524581813865?,
 0.00800384369086252?,
 5.126764595989604?,
 0.4723780710666998? + 5.643167572788120?*I,
 0.4723780710666998? - 5.643167572788120?*I]

Of course, it would be preferable to explicitly compute the idealJ1=R1.ideal(A - E, A*E - B, B*E - C, C*E - D - 10, D*E + 2) and check that its .dimension() is indeed 0 vbefore asking for its .variety()...

A possibly cleaner solution (avoiding to define a truckload of unused symbolic variables and needlessly scratch needlessly predefined Sage identifiers such as e, I and i...), expressed as a two-liner :

sage: R1.<A,B,C,D,E>=QQbar[]
sage: [u[C] for u in R1.ideal(A - E, A*E - B, B*E - C, C*E - D - 10, D*E + 2).variety()]
[-6.079524581813865?,
 0.00800384369086252?,
 5.126764595989604?,
 0.4723780710666998? + 5.643167572788120?*I,
 0.4723780710666998? - 5.643167572788120?*I]

Of course, it would be preferable to explicitly compute the idealJ1=R1.ideal(A - E, A*E - B, B*E - C, C*E - D - 10, D*E + 2) and check that its .dimension() is indeed 0 vbefore asking for its .variety()...