code: def get_results_with_scipy(objective, constraints, variables):
      if scipy is not None and np is not None:
          from sympy.solvers.inequalities import _np
  
          nonpos, rep, xx = _np(constraints, [])
          assert not rep  # only testing nonneg variables
          C, _D = linear_eq_to_matrix(objective, *variables)
          A, B = linear_eq_to_matrix(nonpos, *variables)
          assert _D[0] == 0  # scipy only deals with D = 0
  
          A_sci = Matrix([[A], [-eye(len(variables))]])
          B_sci = Matrix([[B], [Matrix([0] * len(variables))]])
          C_sci = C
          A_sci = np.array(A_sci.tolist())
          B_sci = np.array(B_sci.tolist())
          C_sci = np.array(C_sci.tolist())
          res = scipy.optimize.linprog(C_sci, A_ub=A_sci, b_ub=B_sci)
          return res
  
file_path: sympy/sympy/solvers/tests/test_simplex.py
imports: from sympy.core.numbers import Rational
  from sympy.core.relational import Relational, Eq, Ne
  from sympy.core.symbol import symbols
  from sympy.core.sympify import sympify
  from sympy.core.singleton import S
  from sympy.core.random import random, choice
  from sympy.functions.elementary.miscellaneous import sqrt
  from sympy.ntheory.generate import randprime
  from sympy.matrices.dense import Matrix, eye
  from sympy.solvers.solveset import linear_eq_to_matrix
  from sympy.solvers.simplex import _lp, _primal_dual, UnboundedLPError, InfeasibleLPError, lpmin, lpmax, _m, _abcd, _simplex, linprog
  from sympy.external.importtools import import_module
  from sympy.testing.pytest import raises
  from sympy.abc import x, y, z
label_desc: Use image node_id 1 for calling a global function with example usage: get_results_with_scipy(objective, constraints, variables) and returns: res