numpy.rec.fromstring#

rec.fromstring(datastring, dtype=None, shape=None, offset=0, formats=None, names=None, titles=None, aligned=False, byteorder=None)[source]#

Create a record array from binary data

Note that despite the name of this function it does not accept str instances.

Parameters:

datastringbytes-like: Buffer of binary data
dtypedata-type, optional: Valid dtype for all arrays
shapeint or tuple of ints, optional: Shape of each array.
offsetint, optional: Position in the buffer to start reading from.
formats, names, titles, aligned, byteorder: If dtype is None, these arguments are passed to numpy.format_parser to construct a dtype. See that function for detailed documentation.

Returns:

np.recarray: Record array view into the data in datastring. This will be readonly if datastring is readonly.

See also

numpy.frombuffer

Examples

>>> a = b'\x01\x02\x03abc'
>>> np.rec.fromstring(a, dtype='u1,u1,u1,S3')
rec.array([(1, 2, 3, b'abc')],
        dtype=[('f0', 'u1'), ('f1', 'u1'), ('f2', 'u1'), ('f3', 'S3')])

>>> grades_dtype = [('Name', (np.str_, 10)), ('Marks', np.float64),
...                 ('GradeLevel', np.int32)]
>>> grades_array = np.array([('Sam', 33.3, 3), ('Mike', 44.4, 5),
...                         ('Aadi', 66.6, 6)], dtype=grades_dtype)
>>> np.rec.fromstring(grades_array.tobytes(), dtype=grades_dtype)
rec.array([('Sam', 33.3, 3), ('Mike', 44.4, 5), ('Aadi', 66.6, 6)],
        dtype=[('Name', '<U10'), ('Marks', '<f8'), ('GradeLevel', '<i4')])

>>> s = '\x01\x02\x03abc'
>>> np.rec.fromstring(s, dtype='u1,u1,u1,S3')
Traceback (most recent call last):
   ...
TypeError: a bytes-like object is required, not 'str'