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
isNone
, 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
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'