@@ -98,15 +98,15 @@ def __new__(
9898 )
9999
100100 # 2) Check that the columns referenced in the group rules exist.
101- for name , rule in result .rules .items ():
101+ for rule_name , rule in result .rules .items ():
102102 if isinstance (rule , GroupRule ):
103103 missing_columns = set (rule .group_columns ) - set (result .columns )
104104 if len (missing_columns ) > 0 :
105105 missing_list = ", " .join (
106106 sorted (f"'{ col } '" for col in missing_columns )
107107 )
108108 raise ImplementationError (
109- f"Group validation rule '{ name } ' has been implemented "
109+ f"Group validation rule '{ rule_name } ' has been implemented "
110110 f"incorrectly. It references { len (missing_columns )} columns "
111111 f"which are not in the schema: { missing_list } ."
112112 )
@@ -116,16 +116,16 @@ def __new__(
116116 # empty data frame and checking for the evaluated dtypes.
117117 if len (result .rules ) > 0 :
118118 lf_empty = pl .LazyFrame (
119- schema = {name : col .dtype for name , col in result .columns .items ()}
119+ schema = {col_name : col .dtype for col_name , col in result .columns .items ()}
120120 )
121121 # NOTE: For some reason, `polars` does not yield correct dtypes when calling
122122 # `collect_schema()`
123123 schema = with_evaluation_rules (lf_empty , result .rules ).collect ().schema
124- for name , rule in result .rules .items ():
125- dtype = schema [name ]
124+ for rule_name , rule in result .rules .items ():
125+ dtype = schema [rule_name ]
126126 if not isinstance (dtype , pl .Boolean ):
127127 raise RuleImplementationError (
128- name , dtype , isinstance (rule , GroupRule )
128+ rule_name , dtype , isinstance (rule , GroupRule )
129129 )
130130
131131 return super ().__new__ (mcs , name , bases , namespace , * args , ** kwargs )
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