The standard array can have 24 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 24 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}:
The enumeration value for the boolean type, stored as one byte. It may only be set to the values 0 and 1.
The enumeration value for an 8-bit/1-byte signed integer.
The enumeration value for a 16-bit/2-byte signed integer.
The enumeration value for a 32-bit/4-byte signed integer.
Equivalent to either NPY_INT or NPY_LONGLONG, depending on the platform.
The enumeration value for a 64-bit/8-byte signed integer.
The enumeration value for an 8-bit/1-byte unsigned integer.
The enumeration value for a 16-bit/2-byte unsigned integer.
The enumeration value for a 32-bit/4-byte unsigned integer.
Equivalent to either NPY_UINT or NPY_ULONGLONG, depending on the platform.
The enumeration value for a 64-bit/8-byte unsigned integer.
The enumeration value for a 16-bit/2-byte IEEE 754-2008 compatible floating point type.
The enumeration value for a 32-bit/4-byte IEEE 754 compatible floating point type.
The enumeration value for a 64-bit/8-byte IEEE 754 compatible floating point type.
The enumeration value for a platform-specific floating point type which is at least as large as NPY_DOUBLE, but larger on many platforms.
The enumeration value for a 64-bit/8-byte complex type made up of two NPY_FLOAT values.
The enumeration value for a 128-bit/16-byte complex type made up of two NPY_DOUBLE values.
The enumeration value for a platform-specific complex floating point type which is made up of two NPY_LONGDOUBLE values.
The enumeration value for a data type which holds dates or datetimes with a precision based on selectable date or time units.
The enumeration value for a data type which holds lengths of times in integers of selectable date or time units.
The enumeration value for ASCII strings of a selectable size. The strings have a fixed maximum size within a given array.
The enumeration value for UCS4 strings of a selectable size. The strings have a fixed maximum size within a given array.
The enumeration value for references to arbitrary Python objects.
Primarily used to hold struct dtypes, but can contain arbitrary binary data.
Some useful aliases of the above types are
The enumeration value for a signed integer type which is the same size as a (void *) pointer. This is the type used by all arrays of indices.
The enumeration value for an unsigned integer type which is the same size as a (void *) pointer.
The enumeration value of the type used for masks, such as with the NPY_ITER_ARRAYMASK iterator flag. This is equivalent to NPY_UINT8.
The default type to use when no dtype is explicitly specified, for example when calling np.zero(shape). This is equivalent to NPY_DOUBLE.
Other useful related constants are
The total number of built-in NumPy types. The enumeration covers the range from 0 to NPY_NTYPES-1.
A signal value guaranteed not to be a valid type enumeration number.
The start of type numbers used for Custom Data types.
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, HALF, FLOAT, DOUBLE, LONGDOUBLE, CFLOAT, CDOUBLE, CLONGDOUBLE, DATETIME, TIMEDELTA, 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.
These are defined for {bits} = 8, 16, 32, 64, 128, and 256 and provide the maximum (minimum) value of the corresponding (unsigned) integer type. Note: the actual integer type may not be available on all platforms (i.e. 128-bit and 256-bit integers are rare).
This is defined for {type} = BYTE, SHORT, INT, LONG, LONGLONG, INTP
This is defined for all defined for {type} = BYTE, UBYTE, SHORT, USHORT, INT, UINT, LONG, ULONG, LONGLONG, ULONGLONG, INTP, UINTP
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 NPY_INTP and NPY_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 NPY_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.
(unsigned) char
(unsigned) short
(unsigned) int
(unsigned) long int
(unsigned long long int)
(unsigned) Py_intptr_t (an integer that is the size of a pointer on the platform).
float
double
long double
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