spark/sql/functions/generated.go (55 lines):
	- line 60: // TODO: broadcast: (df: 'DataFrame') -> 'DataFrame'
	- line 158: // TODO: when: (condition: pyspark.sql.connect.column.Column, value: Any) -> pyspark.sql.connect.column.Column
	- line 758: // TODO: first: (col: 'ColumnOrName', ignorenulls: bool = False) -> pyspark.sql.connect.column.Column
	- line 796: // TODO: last: (col: 'ColumnOrName', ignorenulls: bool = False) -> pyspark.sql.connect.column.Column
	- line 848: // TODO: percentile: (col: 'ColumnOrName', percentage: Union[pyspark.sql.connect.column.Column, float, List[float], Tuple[float]], frequency: Union[pyspark.sql.connect.column.Column, int] = 1) -> pyspark.sql.connect.column.Column
	- line 850: // TODO: percentile_approx: (col: 'ColumnOrName', percentage: Union[pyspark.sql.connect.column.Column, float, List[float], Tuple[float]], accuracy: Union[pyspark.sql.connect.column.Column, float] = 10000) -> pyspark.sql.connect.column.Column
	- line 852: // TODO: approx_percentile: (col: 'ColumnOrName', percentage: Union[pyspark.sql.connect.column.Column, float, List[float], Tuple[float]], accuracy: Union[pyspark.sql.connect.column.Column, float] = 10000) -> pyspark.sql.connect.column.Column
	- line 1079: // TODO: lag: (col: 'ColumnOrName', offset: int = 1, default: Optional[Any] = None) -> pyspark.sql.connect.column.Column
	- line 1081: // TODO: lead: (col: 'ColumnOrName', offset: int = 1, default: Optional[Any] = None) -> pyspark.sql.connect.column.Column
	- line 1083: // TODO: nth_value: (col: 'ColumnOrName', offset: int, ignoreNulls: Optional[bool] = None) -> pyspark.sql.connect.column.Column
	- line 1085: // TODO: any_value: (col: 'ColumnOrName', ignoreNulls: Union[bool, pyspark.sql.connect.column.Column, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 1087: // TODO: first_value: (col: 'ColumnOrName', ignoreNulls: Union[bool, pyspark.sql.connect.column.Column, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 1089: // TODO: last_value: (col: 'ColumnOrName', ignoreNulls: Union[bool, pyspark.sql.connect.column.Column, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 1156: // TODO: aggregate: (col: 'ColumnOrName', initialValue: 'ColumnOrName', merge: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column], finish: Optional[Callable[[pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]] = None) -> pyspark.sql.connect.column.Column
	- line 1158: // TODO: reduce: (col: 'ColumnOrName', initialValue: 'ColumnOrName', merge: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column], finish: Optional[Callable[[pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]] = None) -> pyspark.sql.connect.column.Column
	- line 1167: // TODO: array_append: (col: 'ColumnOrName', value: Any) -> pyspark.sql.connect.column.Column
	- line 1169: // TODO: array_contains: (col: 'ColumnOrName', value: Any) -> pyspark.sql.connect.column.Column
	- line 1186: // TODO: array_insert: (arr: 'ColumnOrName', pos: Union[ForwardRef('ColumnOrName'), int], value: Any) -> pyspark.sql.connect.column.Column
	- line 1241: // TODO: array_position: (col: 'ColumnOrName', value: Any) -> pyspark.sql.connect.column.Column
	- line 1243: // TODO: array_prepend: (col: 'ColumnOrName', value: Any) -> pyspark.sql.connect.column.Column
	- line 1245: // TODO: array_remove: (col: 'ColumnOrName', element: Any) -> pyspark.sql.connect.column.Column
	- line 1254: // TODO: array_sort: (col: 'ColumnOrName', comparator: Optional[Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]] = None) -> pyspark.sql.connect.column.Column
	- line 1301: // TODO: element_at: (col: 'ColumnOrName', extraction: Any) -> pyspark.sql.connect.column.Column
	- line 1315: // TODO: exists: (col: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1336: // TODO: filter: (col: 'ColumnOrName', f: Union[Callable[[pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column], Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]]) -> pyspark.sql.connect.column.Column
	- line 1347: // TODO: forall: (col: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1349: // TODO: from_csv: (col: 'ColumnOrName', schema: Union[pyspark.sql.connect.column.Column, str], options: Optional[Dict[str, str]] = None) -> pyspark.sql.connect.column.Column
	- line 1351: // TODO: from_json: (col: 'ColumnOrName', schema: Union[pyspark.sql.types.ArrayType, pyspark.sql.types.StructType, pyspark.sql.connect.column.Column, str], options: Optional[Dict[str, str]] = None) -> pyspark.sql.connect.column.Column
	- line 1418: // TODO: map_contains_key: (col: 'ColumnOrName', value: Any) -> pyspark.sql.connect.column.Column
	- line 1427: // TODO: map_filter: (col: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1458: // TODO: map_zip_with: (col1: 'ColumnOrName', col2: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1503: // TODO: schema_of_csv: (csv: 'ColumnOrName', options: Optional[Dict[str, str]] = None) -> pyspark.sql.connect.column.Column
	- line 1505: // TODO: schema_of_json: (json: 'ColumnOrName', options: Optional[Dict[str, str]] = None) -> pyspark.sql.connect.column.Column
	- line 1529: // TODO: sort_array: (col: 'ColumnOrName', asc: bool = True) -> pyspark.sql.connect.column.Column
	- line 1547: // TODO: to_csv: (col: 'ColumnOrName', options: Optional[Dict[str, str]] = None) -> pyspark.sql.connect.column.Column
	- line 1549: // TODO: to_json: (col: 'ColumnOrName', options: Optional[Dict[str, str]] = None) -> pyspark.sql.connect.column.Column
	- line 1551: // TODO: transform: (col: 'ColumnOrName', f: Union[Callable[[pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column], Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]]) -> pyspark.sql.connect.column.Column
	- line 1553: // TODO: transform_keys: (col: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1555: // TODO: transform_values: (col: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1557: // TODO: zip_with: (left: 'ColumnOrName', right: 'ColumnOrName', f: Callable[[pyspark.sql.connect.column.Column, pyspark.sql.connect.column.Column], pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1804: // TODO: regexp_extract_all: (str: 'ColumnOrName', regexp: 'ColumnOrName', idx: Union[int, pyspark.sql.connect.column.Column, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 1806: // TODO: regexp_replace: (string: 'ColumnOrName', pattern: Union[str, pyspark.sql.connect.column.Column], replacement: Union[str, pyspark.sql.connect.column.Column]) -> pyspark.sql.connect.column.Column
	- line 1816: // TODO: regexp_instr: (str: 'ColumnOrName', regexp: 'ColumnOrName', idx: Union[int, pyspark.sql.connect.column.Column, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 2116: // TODO: like: (str: 'ColumnOrName', pattern: 'ColumnOrName', escapeChar: Optional[ForwardRef('Column')] = None) -> pyspark.sql.connect.column.Column
	- line 2118: // TODO: ilike: (str: 'ColumnOrName', pattern: 'ColumnOrName', escapeChar: Optional[ForwardRef('Column')] = None) -> pyspark.sql.connect.column.Column
	- line 2383: // TODO: months_between: (date1: 'ColumnOrName', date2: 'ColumnOrName', roundOff: bool = True) -> pyspark.sql.connect.column.Column
	- line 2666: // TODO: session_window: (timeColumn: 'ColumnOrName', gapDuration: Union[pyspark.sql.connect.column.Column, str]) -> pyspark.sql.connect.column.Column
	- line 2691: // TODO: bucket: (numBuckets: Union[pyspark.sql.connect.column.Column, int], col: 'ColumnOrName') -> pyspark.sql.connect.column.Column
	- line 2725: // TODO: convert_timezone: (sourceTz: Optional[pyspark.sql.connect.column.Column], targetTz: pyspark.sql.connect.column.Column, sourceTs: 'ColumnOrName') -> pyspark.sql.connect.column.Column
	- line 2823: // TODO: assert_true: (col: 'ColumnOrName', errMsg: Union[pyspark.sql.connect.column.Column, str, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 2825: // TODO: raise_error: (errMsg: Union[pyspark.sql.connect.column.Column, str]) -> pyspark.sql.connect.column.Column
	- line 2878: // TODO: hll_sketch_agg: (col: 'ColumnOrName', lgConfigK: Union[int, pyspark.sql.connect.column.Column, NoneType] = None) -> pyspark.sql.connect.column.Column
	- line 2880: // TODO: hll_union_agg: (col: 'ColumnOrName', allowDifferentLgConfigK: Optional[bool] = None) -> pyspark.sql.connect.column.Column
	- line 2890: // TODO: hll_union: (col1: 'ColumnOrName', col2: 'ColumnOrName', allowDifferentLgConfigK: Optional[bool] = None) -> pyspark.sql.connect.column.Column
	- line 3078: // TODO: udf: (f: Union[Callable[..., Any], ForwardRef('DataTypeOrString'), NoneType] = None, returnType: 'DataTypeOrString' = StringType(), useArrow: Optional[bool] = None) -> Union[ForwardRef('UserDefinedFunctionLike'), Callable[[Callable[..., Any]], ForwardRef('UserDefinedFunctionLike')]]


spark/client/retry.go (2 lines):
	- line 186: // TODO: Should this simoly return the original error?
	- line 348: // TODO: Re-attaching needs to be retriable as well.


dev/gen.py (2 lines):
	- line 83: print(f"// TODO: {fun}: {sig}")
	- line 140: print(f"// TODO: {fun}: {sig}")


spark/sql/dataframe.go (1 line):
	- line 282: relation *proto.Relation // TODO change to proto.Plan?


spark/sql/column/expressions.go (1 line):
	- line 82: // TODO: return proper pyspark error


spark/sql/sparksession.go (1 line):
	- line 178: // TODO (PySpark does a lot of casting here to convert the schema that does not exist yet.


spark/sql/types/arrow.go (1 line):
	- line 226: // TODO: Unfortunately, this ends up being stored as a slice of slices of any. But not


spark/sql/dataframereader.go (1 line):
	- line 20: // TODO needs to implement other methods like Option(), Schema(), and also "strong typed"