The Python(x, cgopts) calling sequence translates Maple code to Python code.

- If the parameter x is an algebraic expression, then a Python statement assigning the expression to a variable is generated.

- If x is a list, Maple Array, or rtable of algebraic expressions, then a sequence of Python statements assigning the elements to a Python array is produced.  Only the initialized elements of the rtable or Maple Array are translated.

- If x is a list of equations $\mathrm{nm}=\mathrm{expr}$, where $\mathrm{nm}$ is a name and $\mathrm{expr}$ is an algebraic expression, then this is understood as a sequence of assignment statements.  In this case, the equivalent sequence of Python assignment statements is generated.

- If x is a procedure, then a Python class is generated containing a function equivalent to the procedure, along with any necessary import statements.

- If x is a module, then a Python class is generated, as described on the PythonDetails help page.

The parameter cgopts may include one or more CodeGeneration options, as described in CodeGenerationOptions.

For more information about how the CodeGeneration package translates Maple code to other languages, see Translation Details. For more information about translation to Python in particular, see PythonDetails.

$\mathrm{with}\left(\mathrm{CodeGeneration}\right)\:$

$\mathrm{Python}\left(x+yz-2xz\,\mathrm{resultname}=''w''\right)$

w = -2 * x * z + y * z + x

$\mathrm{Python}\left(\left[\left[x\,2y\right]\,\left[5\,z\right]\right]\,\mathrm{resultname}=''w''\right)$

w = [[x,2 * y],[5,z]]

$\mathrm{cs}≔\left[s=1.0+x\,t=\ln \left(s\right)\exp \left(-x\right)\,r=\exp \left(-x\right)+xt\right]\:$

$\mathrm{Python}\left(\mathrm{cs}\,\mathrm{optimize}\right)$

s = 0.10e1 + x
t1 = math.log(s)
t2 = math.exp(-x)
t = t2 * t1
r = x * t + t2

$s≔\mathrm{Python}\left(x+y+1\,\mathrm{declare}=\left[x::\mathrm{float}\,y::\'\mathrm{integer}\'\right]\,\mathrm{output}=\mathrm{string}\right)$

$s≔''cg\; =\; x\; +\; y\; +\; 1''$

f := proc(x, y, z) return x*y-y*z+x*z; end proc:

$\mathrm{Python}\left(f\,\mathrm{defaulttype}=\mathrm{integer}\right)$

def f (x, y, z):
    return(y * x - y * z + x * z)

f := proc(n)
  local x, i;
  x := 0.0;
  for i to n do
    x := x + i;
  end do;
end proc:

$\mathrm{Python}\left(f\right)$

def f (n):
    x = 0.0e0
    for i in range(1, n + 1):
        x = x + i
        cgret = x
    return(cgret)

$\mathrm{Python}\left(2\cosh \left(x\right)-7\tanh \left(x\right)\right)$

cg0 = 2 * math.cosh(x) - 7 * math.tanh(x)

f := proc(a::integer, p::integer)
  printf("The integer remainder of %d divided by %d is: %d\n", a, p, irem(a, p));
end proc:

$\mathrm{Python}\left(f\right)$

def f (a, p):
    printf("The integer remainder of %d divided by %d is: %d\n", a, p, a % p)

detHilbert := proc(M, n :: posint) uses LinearAlgebra;
   return Determinant( HilbertMatrix( n ) );
end proc:

$\mathrm{Python}\left(\mathrm{detHilbert}\right)$

import numpy.linalg
import scipy.linalg

def detHilbert (M, n):
    return(numpy.linalg.det(scipy.linalg.hilbert(n)))

$\mathrm{Python}\left(\mathrm{detHilbert}\,\mathrm{libraryorder}=\left[''scipy.linalg''\,''numpy.linalg''\right]\right)$

import scipy.linalg

def detHilbert (M, n):
    return(scipy.linalg.det(scipy.linalg.hilbert(n)))

The CodeGeneration[Python] command was introduced in Maple 18.

For more information on Maple 18 changes, see Updates in Maple 18.