# numpy.fromstring

numpy.fromstring(string, dtype=float, count=- 1, *, sep, like=None)

  A new 1-D array initialized from text data in a string.

  Parameters
    string str

      A string containing the data.

    dtype data-type, optional

      The data type of the array; default: float. For binary input data, the data must be in exactly this format. Most builtin numeric types are supported and extension types may be supported.

      New in version 1.18.0: Complex dtypes.

    count int, optional

      Read this number of `dtype` elements from the data. If this is negative (the default), the count will be determined from the length of the data.

    sep str, optional

      The string separating numbers in the data; extra whitespace between elements is also ignored.

      Deprecated since version 1.14: Passing `sep=''`, the default, is deprecated since it will trigger the deprecated binary mode of this function. This mode interprets `string` as binary bytes, rather than ASCII text with decimal numbers, an operation which is better spelt `frombuffer(string, dtype, count)`. If `string` contains unicode text, the binary mode of `fromstring` will first encode it into bytes using either utf-8 (python 3) or the default encoding (python 2), neither of which produce sane results.

    like array_like, optional

      Reference object to allow the creation of arrays which are not NumPy arrays. If an array-like passed in as `like` supports the `__array_function__` protocol, the result will be defined by it. In this case, it ensures the creation of an array object compatible with that passed in via this argument.

      New in version 1.20.0.

  Returns
    arr ndarray

      The constructed array.

  Raises
    ValueError

      If the string is not the correct size to satisfy the requested `dtype` and count.

  See also

  `frombuffer`, `fromfile`, `fromiter`

  Examples

      >>> np.fromstring('1 2', dtype=int, sep=' ')
      array([1, 2])
      >>> np.fromstring('1, 2', dtype=int, sep=',')
      array([1, 2])

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