The standard array can have 21 different data types (and has some support for adding your own types). These data types all have an enumerated type, an enumerated type-character, and a corresponding array scalar Python type object (placed in a hierarchy). There are also standard C typedefs to make it easier to manipulate elements of the given data type. For the numeric types, there are also bit-width equivalent C typedefs and named typenumbers that make it easier to select the precision desired.
Warning
The names for the types in c code follows c naming conventions more closely. The Python names for these types follow Python conventions. Thus, NPY_FLOAT picks up a 32-bit float in C, but numpy.float_ in Python corresponds to a 64-bit double. The bit-width names can be used in both Python and C for clarity.
There is a list of enumerated types defined providing the basic 21 data types plus some useful generic names. Whenever the code requires a type number, one of these enumerated types is requested. The types are all called NPY_{NAME} where {NAME} can be
BOOL, BYTE, UBYTE, SHORT, USHORT, INT, UINT, LONG, ULONG, LONGLONG, ULONGLONG, FLOAT, DOUBLE, LONGDOUBLE, CFLOAT, CDOUBLE, CLONGDOUBLE, OBJECT, STRING, UNICODE, VOID
NTYPES, NOTYPE, USERDEF, DEFAULT_TYPE
The various character codes indicating certain types are also part of an enumerated list. References to type characters (should they be needed at all) should always use these enumerations. The form of them is NPY_{NAME}LTR where {NAME} can be
BOOL, BYTE, UBYTE, SHORT, USHORT, INT, UINT, LONG, ULONG, LONGLONG, ULONGLONG, FLOAT, DOUBLE, LONGDOUBLE, CFLOAT, CDOUBLE, CLONGDOUBLE, OBJECT, STRING, VOID
INTP, UINTP
GENBOOL, SIGNED, UNSIGNED, FLOATING, COMPLEX
The latter group of {NAME}s corresponds to letters used in the array interface typestring specification.
All NPY_SIZEOF_{CTYPE} constants have corresponding NPY_BITSOF_{CTYPE} constants defined. The NPY_BITSOF_{CTYPE} constants provide the number of bits in the data type. Specifically, the available {CTYPE}s are
BOOL, CHAR, SHORT, INT, LONG, LONGLONG, FLOAT, DOUBLE, LONGDOUBLE
All of the numeric data types (integer, floating point, and complex) have constants that are defined to be a specific enumerated type number. Exactly which enumerated type a bit-width type refers to is platform dependent. In particular, the constants available are PyArray_{NAME}{BITS} where {NAME} is INT, UINT, FLOAT, COMPLEX and {BITS} can be 8, 16, 32, 64, 80, 96, 128, 160, 192, 256, and 512. Obviously not all bit-widths are available on all platforms for all the kinds of numeric types. Commonly 8-, 16-, 32-, 64-bit integers; 32-, 64-bit floats; and 64-, 128-bit complex types are available.
The constants PyArray_INTP and PyArray_UINTP refer to an enumerated integer type that is large enough to hold a pointer on the platform. Index arrays should always be converted to PyArray_INTP , because the dimension of the array is of type npy_intp.
There are standard variable types for each of the numeric data types and the bool data type. Some of these are already available in the C-specification. You can create variables in extension code with these types.
Unsigned versions of the integers can be defined by pre-pending a ‘u’ to the front of the integer name.
complex types are structures with .real and .imag members (in that order).
There are also typedefs for signed integers, unsigned integers, floating point, and complex floating point types of specific bit- widths. The available type names are
npy_int{bits}, npy_uint{bits}, npy_float{bits}, and npy_complex{bits}
where {bits} is the number of bits in the type and can be 8, 16, 32, 64, 128, and 256 for integer types; 16, 32 , 64, 80, 96, 128, and 256 for floating-point types; and 32, 64, 128, 160, 192, and 512 for complex-valued types. Which bit-widths are available is platform dependent. The bolded bit-widths are usually available on all platforms.
For help in printing, the following strings are defined as the correct format specifier in printf and related commands.
NPY_LONGLONG_FMT, NPY_ULONGLONG_FMT, NPY_INTP_FMT, NPY_UINTP_FMT, NPY_LONGDOUBLE_FMT