create_extension(**args)

This is a small wrapper around the create_extension function in Instant.

Arguments:

• code:
  • A Python string containing C or C++ function, class, ....
• module:
  • The name you want for the module (Default is 'instant_swig_module'.). String.
• swigopts:
  • Options to swig, for instance -lpointers.i to include the SWIG pointers.i library. String.
• init_code:
  • Code that should be executed when the Instant extension is imported. String.
• system_headers:
  • A list of system header files required by the Instant code.
• local_headers:
  • A list of local header files required by the Instant code.
• wrap_headers:
  • A list of local header files that will be wrapped by SWIG.
• include_dirs:
  • A list of directories to search for header files.
• sources:
  • A list of source files to compile and link with the extension.
• cppargs:
  • Flags like -D, -U, etc. String.
• libraries:
  • A list of libraries needed by the Instant extension.
• library_dirs:
  • A list of directories to search for libraries (-l).
• object_files:
  • If you want to compile the files yourself. NOT YET SUPPORTED.
• arrays:
  • A list of the C arrays to be made from NumPy arrays.

header_and_libs_from_pkgconfig(*packages)

inline(c_code)

This is a short wrapper around the create_extention function in Instant.

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

>>> 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)

inline_with_numarray(c_code, **args_dict)

This is a short wrapper around the create_extention function in Instant.

It creates an extension 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.

>>> import numarray 
>>> import time
>>> from Instant import inline_with_numarray
>>> 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_numarray(c_code,  arrays = [['n1', 'array1']])
>>> a = numarray.arange(10000000); a = numarray.sin(a)
>>> sum_func(a)

inline_with_numeric(c_code, **args_dict)

This is a short wrapper around the create_extention function in Instant.

It creates an extension 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.

>>> import numpy 
>>> import time
>>> from Instant import inline_with_numeric
>>> 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_numeric(c_code,  arrays = [['n1', 'array1']])
>>> a = numpy.arange(10000000); a = numpy.sin(a)
>>> sum_func(a)

inline_with_numpy(c_code, **args_dict)

This is a short wrapper around the create_extention function in Instant.

It creates an extension 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.

>>> 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)