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�
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    Check whether obj behaves like a string.
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    Returns the filehandle corresponding to a string or a file.
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    Parameters
    ----------
    fname : string, filehandle
        Name of the file whose filehandle must be returned.
    flag : string, optional
        Flag indicating the status of the file ('r' for read, 'w' for write).
    return_opened : boolean, optional
        Whether to return the opening status of the file.
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    Returns whether one or several fields of a dtype are nested.

    Parameters
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    ndtype : dtype
        Data-type of a structured array.

    Raises
    ------
    AttributeError
        If `ndtype` does not have a `names` attribute.

    Examples
    --------
    >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float)])
    >>> np.lib._iotools.has_nested_fields(dt)
    False

    ((tnamesRR(tndtypetname((sE/opt/alt/python27/lib64/python2.7/site-packages/numpy/lib/_iotools.pythas_nested_fieldsWs
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    Note that the field names are lost.

    Parameters
    ----------
    ndtype : dtype
        The datatype to collapse
    flatten_base : {False, True}, optional
        Whether to transform a field with a shape into several fields or not.

    Examples
    --------
    >>> dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
    ...                ('block', int, (2, 3))])
    >>> np.lib._iotools.flatten_dtype(dt)
    [dtype('|S4'), dtype('float64'), dtype('float64'), dtype('int32')]
    >>> np.lib._iotools.flatten_dtype(dt, flatten_base=True)
    [dtype('|S4'), dtype('float64'), dtype('float64'), dtype('int32'),
     dtype('int32'), dtype('int32'), dtype('int32'), dtype('int32'),
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    Object to split a string at a given delimiter or at given places.

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        If a string, character used to delimit consecutive fields.
        If an integer or a sequence of integers, width(s) of each field.
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        Character used to mark the beginning of a comment. Default is '#'.
    autostrip : bool, optional
        Whether to strip each individual field. Default is True.

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        method : function
            Function that takes a single argument and returns a sequence of
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            The result of wrapping `method`. `wrapped` takes a single input
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            white-space.

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NameValidatorcB`s\eZdZdddgZed�Zd
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    of names to exclude, as well as a list of invalid characters. Names in
    the exclusion list are appended a '_' character.

    Once an instance has been created, it can be called with a list of
    names, and a list of valid names will be created.  The `__call__`
    method accepts an optional keyword "default" that sets the default name
    in case of ambiguity. By default this is 'f', so that names will
    default to `f0`, `f1`, etc.

    Parameters
    ----------
    excludelist : sequence, optional
        A list of names to exclude. This list is appended to the default
        list ['return', 'file', 'print']. Excluded names are appended an
        underscore: for example, `file` becomes `file_` if supplied.
    deletechars : str, optional
        A string combining invalid characters that must be deleted from the
        names.
    case_sensitive : {True, False, 'upper', 'lower'}, optional
        * If True, field names are case-sensitive.
        * If False or 'upper', field names are converted to upper case.
        * If 'lower', field names are converted to lower case.

        The default value is True.
    replace_space : '_', optional
        Character(s) used in replacement of white spaces.

    Notes
    -----
    Calling an instance of `NameValidator` is the same as calling its
    method `validate`.

    Examples
    --------
    >>> validator = np.lib._iotools.NameValidator()
    >>> validator(['file', 'field2', 'with space', 'CaSe'])
    ['file_', 'field2', 'with_space', 'CaSe']

    >>> validator = np.lib._iotools.NameValidator(excludelist=['excl'],
                                                  deletechars='q',
                                                  case_sensitive='False')
    >>> validator(['excl', 'field2', 'no_q', 'with space', 'CaSe'])
    ['excl_', 'field2', 'no_', 'with_space', 'case']

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        Validate a list of strings as field names for a structured array.

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        defaultfmt : str, optional
            Default format string, used if validating a given string
            reduces its length to zero.
        nbfields : integer, optional
            Final number of validated names, used to expand or shrink the
            initial list of names.

        Returns
        -------
        validatednames : list of str
            The list of validated field names.

        Notes
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    Raises
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    ValueError
        If the string is not 'True' or 'False' (case independent)

    Examples
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    True
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    Attributes
    ----------
    func : function
        Function used for the conversion.
    default : any
        Default value to return when the input corresponds to a missing
        value.
    type : type
        Type of the output.
    _status : int
        Integer representing the order of the conversion.
    _mapper : sequence of tuples
        Sequence of tuples (dtype, function, default value) to evaluate in
        order.
    _locked : bool
        Holds `locked` parameter.

    Parameters
    ----------
    dtype_or_func : {None, dtype, function}, optional
        If a `dtype`, specifies the input data type, used to define a basic
        function and a default value for missing data. For example, when
        `dtype` is float, the `func` attribute is set to `float` and the
        default value to `np.nan`.  If a function, this function is used to
        convert a string to another object. In this case, it is recommended
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    default : any, optional
        Value to return by default, that is, when the string to be
        converted is flagged as missing. If not given, `StringConverter`
        tries to supply a reasonable default value.
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    Parameters
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        Function, or sequence of functions

    Examples
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    >>> import dateutil.parser
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        converters are tried.  The order in which these other converters
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            `StringConverter` tries to supply a reasonable default value.
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        locked : bool, optional
            Whether the StringConverter should be locked to prevent
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    Convenience function to create a `np.dtype` object.

    The function processes the input `dtype` and matches it with the given
    names.

    Parameters
    ----------
    ndtype : var
        Definition of the dtype. Can be any string or dictionary recognized
        by the `np.dtype` function, or a sequence of types.
    names : str or sequence, optional
        Sequence of strings to use as field names for a structured dtype.
        For convenience, `names` can be a string of a comma-separated list
        of names.
    defaultfmt : str, optional
        Format string used to define missing names, such as ``"f%i"``
        (default) or ``"fields_%02i"``.
    validationargs : optional
        A series of optional arguments used to initialize a
        `NameValidator`.

    Examples
    --------
    >>> np.lib._iotools.easy_dtype(float)
    dtype('float64')
    >>> np.lib._iotools.easy_dtype("i4, f8")
    dtype([('f0', '<i4'), ('f1', '<f8')])
    >>> np.lib._iotools.easy_dtype("i4, f8", defaultfmt="field_%03i")
    dtype([('field_000', '<i4'), ('field_001', '<f8')])

    >>> np.lib._iotools.easy_dtype((int, float, float), names="a,b,c")
    dtype([('a', '<i8'), ('b', '<f8'), ('c', '<f8')])
    >>> np.lib._iotools.easy_dtype(float, names="a,b,c")
    dtype([('a', '<f8'), ('b', '<f8'), ('c', '<f8')])

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