[SPARK-35340][PYTHON] Standardize TypeError messages for unsupported basic operations
### What changes were proposed in this pull request? The PR is proposed to standardize TypeError messages for unsupported basic operations by: - Capitalize the first letter - Leverage TypeError messages defined in `pyspark/pandas/data_type_ops/base.py` - Take advantage of the utility `is_valid_operand_for_numeric_arithmetic` to save duplicated TypeError messages Related unit tests should be adjusted as well. ### Why are the changes needed? Inconsistent TypeError messages are shown for unsupported data-type-based basic operations. Take addition's TypeError messages for example: - addition can not be applied to given types. - string addition can only be applied to string series or literals. Standardizing TypeError messages would improve user experience and reduce maintenance costs. ### Does this PR introduce _any_ user-facing change? No user-facing behavior change. Only TypeError messages are modified. ### How was this patch tested? Unit tests. Closes #33237 from xinrong-databricks/datatypeops_err. Authored-by: Xinrong Meng <xinrong.meng@databricks.com> Signed-off-by: Takuya UESHIN <ueshin@databricks.com>
This commit is contained in:
Xinrong Meng
Takuya UESHIN
parent
ee945e99cc
commit
819c482498
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@ -62,7 +62,7 @@ class DateOps(DataTypeOps):
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warnings.warn(msg, UserWarning)
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return column_op(F.datediff)(left, SF.lit(right)).astype("long")
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else:
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raise TypeError("date subtraction can only be applied to date series.")
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raise TypeError("Date subtraction can only be applied to date series.")
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def rsub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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# Note that date subtraction casts arguments to integer. This is to mimic pandas's
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@ -76,7 +76,7 @@ class DateOps(DataTypeOps):
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warnings.warn(msg, UserWarning)
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return -column_op(F.datediff)(left, SF.lit(right)).astype("long")
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else:
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raise TypeError("date subtraction can only be applied to date series.")
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raise TypeError("Date subtraction can only be applied to date series.")
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def lt(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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from pyspark.pandas.base import column_op
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@ -67,7 +67,7 @@ class DatetimeOps(DataTypeOps):
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),
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)
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else:
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raise TypeError("datetime subtraction can only be applied to datetime series.")
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raise TypeError("Datetime subtraction can only be applied to datetime series.")
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def rsub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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# Note that timestamp subtraction casts arguments to integer. This is to mimic pandas's
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@ -86,7 +86,7 @@ class DatetimeOps(DataTypeOps):
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),
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)
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else:
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raise TypeError("datetime subtraction can only be applied to datetime series.")
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raise TypeError("Datetime subtraction can only be applied to datetime series.")
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def lt(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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from pyspark.pandas.base import column_op
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@ -41,7 +41,6 @@ from pyspark.sql.column import Column
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from pyspark.sql.types import (
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BooleanType,
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StringType,
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TimestampType,
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)
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@ -53,39 +52,24 @@ class NumericOps(DataTypeOps):
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return "numerics"
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def add(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("string addition can only be applied to string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("addition can not be applied to given types.")
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raise TypeError("Addition can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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return column_op(Column.__add__)(left, right)
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def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("subtraction can not be applied to string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("subtraction can not be applied to given types.")
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raise TypeError("Subtraction can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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return column_op(Column.__sub__)(left, right)
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def mod(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("modulo can not be applied on string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("modulo can not be applied to given types.")
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raise TypeError("Modulo can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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@ -95,13 +79,8 @@ class NumericOps(DataTypeOps):
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return column_op(mod)(left, right)
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def pow(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("exponentiation can not be applied on string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("exponentiation can not be applied to given types.")
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raise TypeError("Exponentiation can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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@ -111,34 +90,26 @@ class NumericOps(DataTypeOps):
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return column_op(pow_func)(left, right)
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def radd(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("string addition can only be applied to string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("addition can not be applied to given types.")
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raise TypeError("Addition can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right)
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return column_op(Column.__radd__)(left, right)
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def rsub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("subtraction can not be applied to string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("subtraction can not be applied to given types.")
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raise TypeError("Subtraction can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right)
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return column_op(Column.__rsub__)(left, right)
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def rmul(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("multiplication can not be applied to a string literal.")
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if not isinstance(right, numbers.Number):
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raise TypeError("multiplication can not be applied to given types.")
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raise TypeError("Multiplication can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right)
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return column_op(Column.__rmul__)(left, right)
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def rpow(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("exponentiation can not be applied on string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("exponentiation can not be applied to given types.")
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raise TypeError("Exponentiation can not be applied to given types.")
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def rpow_func(left: Column, right: Any) -> Column:
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return F.when(SF.lit(right == 1), right).otherwise(Column.__rpow__(left, right))
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@ -147,10 +118,8 @@ class NumericOps(DataTypeOps):
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return column_op(rpow_func)(left, right)
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def rmod(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("modulo can not be applied on string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("modulo can not be applied to given types.")
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raise TypeError("Modulo can not be applied to given types.")
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def rmod(left: Column, right: Any) -> Column:
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return ((right % left) + left) % left
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@ -204,30 +173,19 @@ class IntegralOps(NumericOps):
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return "integrals"
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def mul(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("multiplication can not be applied to a string literal.")
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if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
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raise TypeError("multiplication can not be applied to date times.")
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if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType):
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return column_op(SF.repeat)(right, left)
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("multiplication can not be applied to given types.")
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raise TypeError("Multiplication can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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return column_op(Column.__mul__)(left, right)
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def truediv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("True division can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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@ -239,13 +197,8 @@ class IntegralOps(NumericOps):
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return numpy_column_op(truediv)(left, right)
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def floordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("Floor division can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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@ -259,10 +212,8 @@ class IntegralOps(NumericOps):
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return numpy_column_op(floordiv)(left, right)
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def rtruediv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("True division can not be applied to given types.")
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def rtruediv(left: Column, right: Any) -> Column:
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return F.when(left == 0, SF.lit(np.inf).__div__(right)).otherwise(
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@ -273,10 +224,8 @@ class IntegralOps(NumericOps):
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return numpy_column_op(rtruediv)(left, right)
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def rfloordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("Floor division can not be applied to given types.")
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def rfloordiv(left: Column, right: Any) -> Column:
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return F.when(SF.lit(left == 0), SF.lit(np.inf).__div__(right)).otherwise(
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@ -310,27 +259,16 @@ class FractionalOps(NumericOps):
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return "fractions"
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def mul(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("multiplication can not be applied to a string literal.")
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if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
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raise TypeError("multiplication can not be applied to date times.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("multiplication can not be applied to given types.")
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raise TypeError("Multiplication can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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return column_op(Column.__mul__)(left, right)
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def truediv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("True division can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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@ -346,13 +284,8 @@ class FractionalOps(NumericOps):
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return numpy_column_op(truediv)(left, right)
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def floordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if (
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isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, StringType)
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) or isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not is_valid_operand_for_numeric_arithmetic(right):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("Floor division can not be applied to given types.")
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right = transform_boolean_operand_to_numeric(right, left.spark.data_type)
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@ -370,10 +303,8 @@ class FractionalOps(NumericOps):
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return numpy_column_op(floordiv)(left, right)
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def rtruediv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("True division can not be applied to given types.")
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def rtruediv(left: Column, right: Any) -> Column:
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return F.when(left == 0, SF.lit(np.inf).__div__(right)).otherwise(
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@ -384,10 +315,8 @@ class FractionalOps(NumericOps):
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return numpy_column_op(rtruediv)(left, right)
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def rfloordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("division can not be applied on string series or literals.")
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if not isinstance(right, numbers.Number):
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raise TypeError("division can not be applied to given types.")
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raise TypeError("Floor division can not be applied to given types.")
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def rfloordiv(left: Column, right: Any) -> Column:
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return F.when(SF.lit(left == 0), SF.lit(np.inf).__div__(right)).otherwise(
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@ -53,15 +53,9 @@ class StringOps(DataTypeOps):
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elif isinstance(right, str):
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return column_op(F.concat)(left, SF.lit(right))
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else:
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raise TypeError("string addition can only be applied to string series or literals.")
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def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("subtraction can not be applied to string series or literals.")
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raise TypeError("Addition can not be applied to given types.")
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def mul(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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raise TypeError("multiplication can not be applied to a string literal.")
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if (
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isinstance(right, IndexOpsMixin)
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and isinstance(right.spark.data_type, IntegralType)
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@ -69,19 +63,7 @@ class StringOps(DataTypeOps):
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) or isinstance(right, int):
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return column_op(SF.repeat)(left, right)
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else:
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raise TypeError("a string series can only be multiplied to an int series or literal")
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def truediv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("division can not be applied on string series or literals.")
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def floordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("division can not be applied on string series or literals.")
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def mod(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("modulo can not be applied on string series or literals.")
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def pow(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("exponentiation can not be applied on string series or literals.")
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raise TypeError("Multiplication can not be applied to given types.")
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def radd(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, str):
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@ -90,28 +72,13 @@ class StringOps(DataTypeOps):
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left._with_new_scol(F.concat(SF.lit(right), left.spark.column)), # TODO: dtype?
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)
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else:
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raise TypeError("string addition can only be applied to string series or literals.")
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def rsub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("subtraction can not be applied to string series or literals.")
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raise TypeError("Addition can not be applied to given types.")
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def rmul(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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if isinstance(right, int):
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return column_op(SF.repeat)(left, right)
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else:
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raise TypeError("a string series can only be multiplied to an int series or literal")
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def rtruediv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("division can not be applied on string series or literals.")
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def rfloordiv(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("division can not be applied on string series or literals.")
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def rpow(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("exponentiation can not be applied on string series or literals.")
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def rmod(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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raise TypeError("modulo can not be applied on string series or literals.")
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raise TypeError("Multiplication can not be applied to given types.")
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def lt(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
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from pyspark.pandas.base import column_op
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@ -212,7 +212,7 @@ class DatetimeIndexTest(PandasOnSparkTestCase, TestUtils):
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self.assertRaisesRegex(TypeError, expected_err_msg, lambda: psidx % other)
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self.assertRaisesRegex(TypeError, expected_err_msg, lambda: other % psidx)
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expected_err_msg = "datetime subtraction can only be applied to datetime series."
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expected_err_msg = "Datetime subtraction can only be applied to datetime series."
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for other in [1, 0.1]:
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self.assertRaisesRegex(TypeError, expected_err_msg, lambda: psidx - other)
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@ -2347,7 +2347,7 @@ class DataFrameTest(PandasOnSparkTestCase, SQLTestUtils):
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self.assert_eq(psdf["c"] + psdf["d"], pdf["c"] + pdf["d"])
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|
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# Negative
|
||||
ks_err_msg = "string addition can only be applied to string series or literals"
|
||||
ks_err_msg = "Addition can not be applied to given types"
|
||||
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] + psdf["c"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["c"] + psdf["a"])
|
||||
|
|
@ -2365,12 +2365,13 @@ class DataFrameTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
|
||||
# Negative
|
||||
psdf = ps.DataFrame({"a": ["x"], "b": [1]})
|
||||
ks_err_msg = "subtraction can not be applied to string series or literals"
|
||||
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] - psdf["b"])
|
||||
ks_err_msg = "Subtraction can not be applied to given types"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] - psdf["a"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] - "literal")
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: "literal" - psdf["b"])
|
||||
|
||||
ks_err_msg = "Subtraction can not be applied to strings"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] - psdf["b"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: 1 - psdf["a"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] - 1)
|
||||
|
||||
|
|
@ -2386,23 +2387,27 @@ class DataFrameTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
|
||||
# Negative
|
||||
psdf = ps.DataFrame({"a": ["x"], "b": [1]})
|
||||
ks_err_msg = "division can not be applied on string series or literals"
|
||||
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] / psdf["b"])
|
||||
ks_err_msg = "True division can not be applied to given types"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] / psdf["a"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] / "literal")
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: "literal" / psdf["b"])
|
||||
|
||||
ks_err_msg = "True division can not be applied to strings"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] / psdf["b"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: 1 / psdf["a"])
|
||||
|
||||
def test_binary_operator_floordiv(self):
|
||||
psdf = ps.DataFrame({"a": ["x"], "b": [1]})
|
||||
ks_err_msg = "division can not be applied on string series or literals"
|
||||
|
||||
ks_err_msg = "Floor division can not be applied to strings"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] // psdf["b"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: 1 // psdf["a"])
|
||||
|
||||
ks_err_msg = "Floor division can not be applied to given types"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] // psdf["a"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] // "literal")
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: "literal" // psdf["b"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: 1 // psdf["a"])
|
||||
|
||||
def test_binary_operator_mod(self):
|
||||
# Positive
|
||||
|
|
@ -2413,11 +2418,12 @@ class DataFrameTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
|
||||
# Negative
|
||||
psdf = ps.DataFrame({"a": ["x"], "b": [1]})
|
||||
ks_err_msg = "modulo can not be applied on string series or literals"
|
||||
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] % psdf["b"])
|
||||
ks_err_msg = "Modulo can not be applied to given types"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] % psdf["a"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] % "literal")
|
||||
|
||||
ks_err_msg = "Modulo can not be applied to strings"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] % psdf["b"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: 1 % psdf["a"])
|
||||
|
||||
def test_binary_operator_multiply(self):
|
||||
|
|
@ -2436,12 +2442,11 @@ class DataFrameTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
|
||||
# Negative
|
||||
psdf = ps.DataFrame({"a": ["x"], "b": [2]})
|
||||
ks_err_msg = "multiplication can not be applied to a string literal"
|
||||
ks_err_msg = "Multiplication can not be applied to given types"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["b"] * "literal")
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: "literal" * psdf["b"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] * "literal")
|
||||
|
||||
ks_err_msg = "a string series can only be multiplied to an int series or literal"
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] * psdf["a"])
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: psdf["a"] * 0.1)
|
||||
self.assertRaisesRegex(TypeError, ks_err_msg, lambda: 0.1 * psdf["a"])
|
||||
|
|
|
|||
|
|
@ -70,7 +70,7 @@ class SeriesDateTimeTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
psdf = ps.DataFrame(
|
||||
{"a": pd.date_range("2016-12-31", "2017-01-08", freq="D"), "b": pd.Series(range(9))}
|
||||
)
|
||||
expected_error_message = "datetime subtraction can only be applied to datetime series."
|
||||
expected_error_message = "Datetime subtraction can only be applied to datetime series."
|
||||
with self.assertRaisesRegex(TypeError, expected_error_message):
|
||||
psdf["a"] - psdf["b"]
|
||||
with self.assertRaisesRegex(TypeError, expected_error_message):
|
||||
|
|
@ -104,7 +104,7 @@ class SeriesDateTimeTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
self.assertRaisesRegex(TypeError, expected_err_msg, lambda: psser % other)
|
||||
self.assertRaisesRegex(TypeError, expected_err_msg, lambda: other % psser)
|
||||
|
||||
expected_err_msg = "datetime subtraction can only be applied to datetime series."
|
||||
expected_err_msg = "Datetime subtraction can only be applied to datetime series."
|
||||
|
||||
for other in [1, 0.1]:
|
||||
self.assertRaisesRegex(TypeError, expected_err_msg, lambda: psser - other)
|
||||
|
|
@ -135,7 +135,7 @@ class SeriesDateTimeTest(PandasOnSparkTestCase, SQLTestUtils):
|
|||
psdf = ps.DataFrame(
|
||||
{"a": pd.date_range("2016-12-31", "2017-01-08", freq="D"), "b": pd.Series(range(9))}
|
||||
)
|
||||
expected_error_message = "date subtraction can only be applied to date series."
|
||||
expected_error_message = "Date subtraction can only be applied to date series."
|
||||
with self.assertRaisesRegex(TypeError, expected_error_message):
|
||||
psdf["a"].dt.date - psdf["b"]
|
||||
with self.assertRaisesRegex(TypeError, expected_error_message):
|
||||
|
|
|
|||
Loading…
Reference in a new issue