Github user ilganeli commented on a diff in the pull request:
https://github.com/apache/spark/pull/6686#discussion_r32785670
--- Diff: python/pyspark/sql/types.py ---
@@ -368,8 +367,43 @@ def __init__(self, fields):
>>> struct1 == struct2
False
"""
- assert all(isinstance(f, DataType) for f in fields), "fields
should be a list of DataType"
- self.fields = fields
+ if not fields:
+ self.fields = []
+ else:
+ self.fields = fields
+ assert all(isinstance(f, StructField) for f in fields),\
+ "fields should be a list of StructField"
+
+ def add(self, name_or_struct_field, data_type=None, nullable=True,
metadata=None):
+ """
+ Construct a StructType by adding new elements to it to define the
schema
+
+ >>> struct1 = StructType().add("f1", StringType(), True).add("f2",
StringType(), True, None)
+ >>> struct2 = StructType([StructField("f1", StringType(), True),\
+ StructField("f2", StringType(), True, None)])
+ >>> struct1 == struct2
+ True
+ >>> struct1 = (StructType().add(StructField("f1", StringType(),
True))
+ ... .add(StructField("f2", StringType(), True, None)))
+ >>> struct2 = StructType([StructField("f1", StringType(), True),
+ ... StructField("f2", StringType(), True, None)])
+ >>> struct1 == struct2
+ True
+
+ :param nameOrStructField: Either the name of the field or a
StructField object
+ :param data_type: If present, the DataType of the StructField to
create
+ :param nullable: Whether the field to add should be nullable
(default True)
+ :param metadata: Any additional metadata (default None)
+ :return: a new updated StructType
+ """
+ if isinstance(name_or_struct_field, StructField):
+ self.fields.append(name_or_struct_field)
+ return self
+ else:
+ if isinstance(name_or_struct_field, str) and data_type is None:
+ raise ValueError("Must specify DataType if passing name of
struct_field to create.")
+ self.fields.append(StructField(name_or_struct_field,
data_type, nullable, metadata))
--- End diff --
@davies Is there an equivalent of the DataTypeParser in Python?
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