What do the > < signs in numpy dtype mean?

Question

What is the difference between dtype='f', dtype='f4', dtype='>f4', dtype'<f4'? The syntax is not explained in docs on types (except that 'f' is a shorthand for 'float32'); it is extensively used in the page on records but the meaning of >/< is also left unexplained in there.

After some experimentation I found out that

    In [13]: a = np.array([1.0], dtype='f')
    In [15]: print(a.dtype)
    float32

and

    In [16]: a = np.array([1.0], dtype='<f4')
    In [17]: print(a.dtype)
    float32

but

    In [18]: a = np.array([1.0], dtype='>f4')
    In [19]: print(a.dtype)
    >f4

It makes me believe those are not equivalent, which may be the explanation for issues I am facing with an external library.

Answer 1

Endian-ness.

< = little-endian (LSB first)

> = big-endian (MSB first)

https://docs.scipy.org/doc/numpy/reference/generated/numpy.dtype.byteorder.html

Answer 2

By looking up the data type object you can see that the '>' and '<' reference the Endianess of the datatype

https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html

>>> dt = np.dtype('>H') # big-endian unsigned short
>>> dt = np.dtype('<f') # little-endian single-precision float

f is a single-precision floating point number and in your case it uses 4 bytes (4 x 8 = 32 bits).

dtype='<f4'

Makes dtype a 32 bit single-precision floating point number using little endian order of bytes.

More on Endianness can be found using wiki https://en.wikipedia.org/wiki/Endianness