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# Data Type API

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.

## Enumerated Types

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.

## Defines

### Max and min values for integers

`NPY_MAX_INT{bits}`

`NPY_MAX_UINT{bits}`

`NPY_MIN_INT{bits}`

  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).

`NPY_MIN_{type}`

  This is defined for `{type}` = BYTE, SHORT, INT, LONG, LONGLONG, INTP

`NPY_MAX_{type}`

  This is defined for all defined for `{type}` = BYTE, UBYTE, SHORT, USHORT, INT, UINT, LONG, ULONG, LONGLONG, ULONGLONG, INTP, UINTP

### Number of bits in data types

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

### Bit-width references to enumerated typenums

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.

### Integer that can hold a pointer

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.

## C-type names

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.

### Boolean

`npy_bool`

  unsigned char; The constants `NPY_FALSE` and `NPY_TRUE` are also defined.

### (Un)Signed Integer

Unsigned versions of the integers can be defined by pre-pending a ‘u’ to the front of the integer name.

`npy_(u)byte`

  (unsigned) char

`npy_(u)short`

  (unsigned) short

`npy_(u)int`

  (unsigned) int

`npy_(u)long`

  (unsigned) long int

`npy_(u)longlong`

  (unsigned long long int)

`npy_(u)intp`

  (unsigned) Py_intptr_t (an integer that is the size of a pointer on the platform).

### (Complex) Floating point

`npy_(c)float`

  float

`npy_(c)double`

  double

`npy_(c)longdouble`

  long double

complex types are structures with .real and .imag members (in that order).

### Bit-width names

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.

## Printf Formatting

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`

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