Github user mateiz commented on a diff in the pull request:
https://github.com/apache/spark/pull/685#discussion_r12502581
--- Diff: python/pyspark/mllib/linalg.py ---
@@ -234,6 +233,45 @@ 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))
--- End diff --
We can't use eval here; it will be both slow and a security risk. If it's a
lot of work to create a fast parser in Python (which is might be), maybe we
should instead do JSON, with just tuples.
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