pathwaycom/pathway · error · ValueError

Schema.with_types() argument name has to be an existing colu

Error message

Schema.with_types() argument name has to be an existing column name, received f{name}.

What it means

Schema.with_types(**kwargs) rewrites the dtypes of existing columns. Every keyword name must match a column of the schema; an unknown name cannot be remapped, so schema.py raises this ValueError (the message text contains a formatting bug — 'received f{name}' prints a literal 'f' — but the offending name is still shown).

Source

Thrown at python/pathway/internals/schema.py:392

        return pkey_fields if pkey_fields else None

    def default_values(self) -> dict[str, Any]:
        return {
            name: column.default_value
            for name, column in self.__columns__.items()
            if column.has_default_value()
        }

    def keys(self) -> KeysView[str]:
        return self.__columns__.keys()

    def with_types(self, **kwargs) -> type[Schema]:
        columns: dict[str, ColumnDefinition] = {
            col.name: col.to_definition() for col in self.__columns__.values()
        }
        for name, dtype in kwargs.items():
            if name not in columns:
                raise ValueError(
                    f"Schema.with_types() argument name has to be an existing column name, received f{name}."
                )
            columns[name] = dataclasses.replace(columns[name], dtype=dt.wrap(dtype))

        return schema_builder(columns=columns, id_dtype=self.id.dtype)

    def without(self, *args: str | expr.ColumnReference) -> type[Schema]:
        columns: dict[str, ColumnDefinition] = {
            col.name: col.to_definition() for col in self.__columns__.values()
        }
        for arg in args:
            if isinstance(arg, str):
                name = arg
            else:
                name = arg._name
            try:
                columns.pop(name)
            except KeyError:

View on GitHub (pinned to fa2f74a464)

Solutions

1. Check the schema's column names first (list(MySchema.keys()) or MySchema.column_names()) and use the exact name.
2. If you need to add a column, use schema composition (SchemaA | SchemaB) or define a new schema instead of with_types.
3. If the name should exist, fix the upstream rename so it does.

Example fix

# before
S2 = MySchema.with_types(price=float)  # column is 'cost'

# after
S2 = MySchema.with_types(cost=float)

import pathway as pw

def with_types_args_valid(schema_cls, kwargs: dict) -> bool:
    return set(kwargs.keys()) <= set(schema_cls.keys())

When it happens

Trigger: MySchema.with_types(price=float) when MySchema has no 'price' column (e.g. it is named 'cost' or 'amount'); also typos or renamed columns after refactors.

Common situations: Aligning CSV/json input schemas with connector expectations; renaming columns in a query but forgetting to update with_types calls.

Related errors

• Schema.without() argument {name!r} has to refer to an existi
• Failed to detect the region of S3 bucket {bucket!r} (HTTP st
• `{self.name}` has no attribute `{name}`
• You cannot use {dep.to_column_expression()} in this reduce s
• join condition should be of form <left_table>.<column> == <r

AI-assisted analysis of pathwaycom/pathway@fa2f74a464 (2026-08-15). Data as JSON: /api/errors/ef5ac4fc2b7006c8. Report an issue: GitHub.