numpy/numpy · error · TypeError

fromstring() needs a 'dtype' or 'formats' argument

Error message

fromstring() needs a 'dtype' or 'formats' argument

What it means

Raised by numpy.rec.fromstring because decoding a binary buffer into a record array requires a structured layout. You must supply either a dtype or the formats/names/titles set so NumPy knows how to interpret the bytes.

Source

Thrown at numpy/_core/records.py:810

            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'
    """

    if dtype is None and formats is None:
        raise TypeError("fromstring() needs a 'dtype' or 'formats' argument")

    if dtype is not None:
        descr = sb.dtype(dtype)
    else:
        descr = format_parser(formats, names, titles, aligned, byteorder).dtype

    itemsize = descr.itemsize

    # NumPy 1.19.0, 2020-01-01
    shape = _deprecate_shape_0_as_None(shape)

    if shape in (None, -1):
        shape = (len(datastring) - offset) // itemsize

    _array = recarray(shape, descr, buf=datastring, offset=offset)
    return _array

def get_remaining_size(fd):

View on GitHub (pinned to e117b3ca4e)

Solutions

1. Pass dtype= a valid structured dtype, e.g. np.rec.fromstring(buf, dtype='u1,u1,u1,S3').
2. Or pass formats= (plus names=) so NumPy builds the dtype via format_parser.
3. Remember the buffer must be bytes-like; if you have a str, encode it first.

Example fix

// before
np.rec.fromstring(buf)
// after
np.rec.fromstring(buf, dtype='u1,u1,u1,S3')

if dtype is None and formats is None:
    raise TypeError('provide dtype= or formats= to np.rec.fromstring')

def has_layout(dtype, formats):
    return dtype is not None or formats is not None

When it happens

Trigger: Calling np.rec.fromstring(datastring) or np.rec.fromstring(buf, formats=None, dtype=None) with neither a dtype nor a formats argument.

Common situations: Omitting the dtype after refactoring a call that previously inferred it; copy-pasting a frombuffer call and forgetting to carry over the dtype; assuming fromstring can auto-detect the layout from the bytes.

Related errors

• fromfile() needs a 'dtype' or 'formats' argument
• Must define formats (or dtype) if object is None, string, or
• Must define a shape if obj is None
• array-shape mismatch in array {k} ("{name}")
• Can only deal with 1-d array.

AI-assisted analysis of numpy/numpy@e117b3ca4e (2026-08-07). Data as JSON: /api/errors/6851d63f166c04b2. Report an issue: GitHub.