Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/11663#discussion_r57077422
--- Diff: python/pyspark/ml/param/__init__.py ---
@@ -65,6 +80,144 @@ def __eq__(self, other):
return False
+class TypeConverters(object):
+ """
+ .. note:: DeveloperApi
+
+ Factory methods for common type conversion functions for
`Param.typeConverter`.
+
+ .. versionadded:: 2.0.0
+ """
+
+ @staticmethod
+ def _is_numeric(value):
+ vtype = type(value)
+ return vtype in [int, float, np.float64, np.int64] or
vtype.__name__ == 'long'
+
+ @staticmethod
+ def _is_integer(value):
+ return TypeConverters._is_numeric(value) and
float(value).is_integer()
+
+ @staticmethod
+ def _can_convert_to_list(value):
+ vtype = type(value)
+ return vtype in [list, np.ndarray, tuple, xrange, array.array] or
isinstance(value, Vector)
+
+ @staticmethod
+ def _can_convert_to_string(value):
--- End diff --
I changed this to do "safe" unicode to str conversions. The way it was
previously, a user could provide non-ascii characters in a string param and get
a somewhat mysterious `UnicodeEncodeError`. This way, they should at least get
an error message consistent with other TypeConverters. I appreciate feedback on
this.
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