remove parse methods based on eval from pyspark

Author: mengxr

python/pyspark/mllib/linalg.py

@@ -232,30 +232,6 @@ def dense(elements):
         """
         return array(elements, dtype=float64)
 
-
-    @staticmethod
-    def parse(s):
-        """
-        Parses a string resulted from Vectors.stringify() into a vector.
-
-        >>> Vectors.parse("[0.0,1.0]")
-        array([ 0.,  1.])
-        >>> print Vectors.parse("(2,[1],[1.0])")
-        (2,[1],[1.0])
-        """
-        return Vectors._parse_structured(eval(s))
-
-
-    @staticmethod
-    def _parse_structured(data):
-        if type(data) == list:
-            return Vectors.dense(data)
-        elif type(data) == tuple:
-            return Vectors.sparse(data[0], data[1], data[2])
-        else:
-            raise SyntaxError("Cannot recognize " + data)
-
-
     @staticmethod
     def stringify(vector):
         """

python/pyspark/mllib/regression.py

@@ -48,23 +48,6 @@ def __str__(self):
         return "(" + ",".join((str(self.label), Vectors.stringify(self.features))) + ")"
 
 
-    @staticmethod
-    def parse(s):
-        """
-        Parses a string resulted from str() to a LabeledPoint.
-
-        >>> print LabeledPoint.parse("(1.0,[0.0,1.0])")
-        (1.0,[0.0,1.0])
-        >>> print LabeledPoint.parse("(1.0,(2,[1],[1.0]))")
-        (1.0,(2,[1],[1.0]))
-        """
-        return LabeledPoint._parse_structured(eval(s))
-
-
-    @staticmethod
-    def _parse_structured(data):
-        return LabeledPoint(data[0], Vectors._parse_structured(data[1]))
-
 class LinearModel(object):
     """A linear model that has a vector of coefficients and an intercept."""
     def __init__(self, weights, intercept):