Data Types¶

Array API specification for supported data types.

A conforming implementation of the array API standard must provide and support the following data types.

bool¶

Boolean (True or False).

int8¶

An 8-bit signed integer whose values exist on the interval [-128, +127].

int16¶

A 16-bit signed integer whose values exist on the interval [−32,767, +32,767].

int32¶

A 32-bit signed integer whose values exist on the interval [−2,147,483,647, +2,147,483,647].

int64¶

A 64-bit signed integer whose values exist on the interval [−9,223,372,036,854,775,807, +9,223,372,036,854,775,807].

uint8¶

An 8-bit unsigned integer whose values exist on the interval [0, +255].

uint16¶

A 16-bit unsigned integer whose values exist on the interval [0, +65,535].

uint32¶

A 32-bit unsigned integer whose values exist on the interval [0, +4,294,967,295].

uint64¶

A 64-bit unsigned integer whose values exist on the interval [0, +18,446,744,073,709,551,615].

float32¶

IEEE 754 single-precision (32-bit) binary floating-point number (see IEEE 754-2019).

float64¶

IEEE 754 double-precision (64-bit) binary floating-point number (see IEEE 754-2019).

complex64¶

Single-precision (64-bit) complex floating-point number whose real and imaginary components must be IEEE 754 single-precision (32-bit) binary floating-point numbers (see IEEE 754-2019).

complex128¶

Double-precision (128-bit) complex floating-point number whose real and imaginary components must be IEEE 754 double-precision (64-bit) binary floating-point numbers (see IEEE 754-2019).

Note

IEEE 754-2019 requires support for subnormal (a.k.a., denormal) numbers, which are useful for supporting gradual underflow. However, hardware support for subnormal numbers is not universal, and many platforms (e.g., accelerators) and compilers support toggling denormals-are-zero (DAZ) and/or flush-to-zero (FTZ) behavior to increase performance and to guard against timing attacks.

Accordingly, subnormal behavior is left unspecified and, thus, implementation-defined. Conforming implementations may vary in their support for subnormal numbers.

Note

A conforming implementation of the array API standard may provide and support additional data types beyond those described in this specification.

Data Type Objects¶

Data types (“dtypes”) are objects which are used as dtype specifiers in functions and methods (e.g., zeros((2, 3), dtype=float32)).

Note

A conforming implementation may add additional methods or attributes to data type objects beyond those described in this specification.

Note

Implementations may provide other ways to specify data types (e.g., zeros((2, 3), dtype='f4')) which are not described in this specification; however, in order to ensure portability, array library consumers are recommended to use data type objects as provided by specification conforming array libraries.

A conforming implementation of the array API standard must provide and support data type objects having the following attributes and methods.

Methods¶

__eq__(self, other, /)

Computes the truth value of self == other in order to test for data type object equality.

Default Data Types¶

A conforming implementation of the array API standard must define the following default data types.

a default real-valued floating-point data type (either float32 or float64).
a default complex floating-point data type (either complex64 or complex128).
a default integer data type (either int32 or int64).
a default array index data type (either int32 or int64).

The default real-valued floating-point and complex floating-point data types must be the same across platforms.

The default complex floating-point point data type should match the default real-valued floating-point data type. For example, if the default real-valued floating-point data type is float32, the default complex floating-point data type must be complex64. If the default real-valued floating-point data type is float64, the default complex floating-point data type must be complex128.

The default integer data type should be the same across platforms, but the default may vary depending on whether Python is 32-bit or 64-bit.

The default array index data type may be int32 on 32-bit platforms, but the default should be int64 otherwise.

Note that it is possible that a library supports multiple devices, with not all those device types supporting the same data types. In this case, the default integer or floating-point data types may vary with device. If that is the case, the library should clearly warn about this in its documentation.

Note

The default data types should be clearly defined in a conforming library’s documentation.

Data Type Categories¶

For the purpose of organizing functions within this specification, the following data type categories are defined.

Note

Conforming libraries are not required to organize data types according to these categories. These categories are only intended for use within this specification.

Numeric Data Types¶

int8, int16, int32, int64, uint8, uint16, uint32, uint64, float32, float64, complex64, and complex128.

Real-valued Data Types¶

int8, int16, int32, int64, uint8, uint16, uint32, uint64, float32, and float64.

Integer Data Types¶

int8, int16, int32, int64, uint8, uint16, uint32, and uint64.

Floating-point Data Types¶

float32, float64, complex64, and complex128.

Real-valued Floating-point Data Types¶

float32 and float64.

Complex Floating-point Data Types¶

complex64 and complex128.

Boolean Data Types¶

bool.