Module inlining

This is a short wrapper around the build_module function in instant.

It creates a module given that the input is a valid C function. It is only possible to inline one C function each time.

Usage:

>>> from instant import inline
>>> add_func = inline("double add(double a, double b){ return a+b; }")
>>> print "The sum of 3 and 4.5 is ", add_func(3, 4.5)

This is a short wrapper around the build_module function in instant.

It creates a module given that the input is a valid C function. It is only possible to inline one C function each time.

Usage:

>>> from instant import inline
>>> add_func = inline("double add(double a, double b){ return a+b; }")
>>> print "The sum of 3 and 4.5 is ", add_func(3, 4.5)

This is a short wrapper around the build_module function in instant.

It creates a module given that the input is a valid C function. It is only possible to inline one C function each time. The difference between this function and the inline function is that C-arrays can be used. The following example illustrates that.

Usage:

>>> import numpy
>>> import time
>>> from instant import inline_with_numpy
>>> c_code = """
    double sum (int n1, double* array1){
        double tmp = 0.0; 
        for (int i=0; i<n1; i++) {  
            tmp += array1[i]; 
        }
        return tmp; 
    }
    """
>>> sum_func = inline_with_numpy(c_code,  arrays = [['n1', 'array1']])
>>> a = numpy.arange(10000000); a = numpy.sin(a)
>>> sum_func(a)

This is a short wrapper around the build_module function in instant.

It creates a module given that the input is a valid C function. It is only possible to inline one C function each time. The difference between this function and the inline function is that C-arrays can be used. The following example illustrates that.

Usage:

>>> import numpy
>>> import time
>>> from instant import inline_with_numpy
>>> c_code = """
    double sum (int n1, double* array1){
        double tmp = 0.0; 
        for (int i=0; i<n1; i++) {  
            tmp += array1[i]; 
        }
        return tmp; 
    }
    """
>>> sum_func = inline_with_numpy(c_code,  arrays = [['n1', 'array1']])
>>> a = numpy.arange(10000000); a = numpy.sin(a)
>>> sum_func(a)