Function safe_eval

numpy/lib/utils.py:1027–1078

Protected string evaluation. Evaluate a string containing a Python literal expression without allowing the execution of arbitrary non-literal code. .. warning:: This function is identical to :py:meth:`ast.literal_eval` and has the same security implications. It m

(source)

def safe_eval(source):
    """
    Protected string evaluation.

    Evaluate a string containing a Python literal expression without
    allowing the execution of arbitrary non-literal code.

    .. warning::

        This function is identical to :py:meth:`ast.literal_eval` and
        has the same security implications.  It may not always be safe
        to evaluate large input strings.

    Parameters
    ----------
    source : str
        The string to evaluate.

    Returns
    -------
    obj : object
       The result of evaluating `source`.

    Raises
    ------
    SyntaxError
        If the code has invalid Python syntax, or if it contains
        non-literal code.

    Examples
    --------
    >>> np.safe_eval('1')
    1
    >>> np.safe_eval('[1, 2, 3]')
    [1, 2, 3]
    >>> np.safe_eval('{"foo": ("bar", 10.0)}')
    {'foo': ('bar', 10.0)}

    >>> np.safe_eval('import os')
    Traceback (most recent call last):
      ...
    SyntaxError: invalid syntax

    >>> np.safe_eval('open("/home/user/.ssh/id_dsa").read()')
    Traceback (most recent call last):
      ...
    ValueError: malformed node or string: <_ast.Call object at 0x...>

    """
    # Local import to speed up numpy's import time.
    import ast
    return ast.literal_eval(source)


def _median_nancheck(data, result, axis):