Method table_from_markdown

python/pathway/debug/__init__.py:698–714

A function for creating a table from its definition in markdown. If it contains a column ``_time``, rows will be split into batches with timestamps from ``_time`` column. Then ``_worker`` column will be interpreted as the id of a worker which will process the row and ``_diff`

(
        self,
        table: str,
        id_from: list[str] | None = None,
        unsafe_trusted_ids: bool = False,
        schema: type[Schema] | None = None,
        _stacklevel: int = 1,
    )

        return self._table_from_dict(batches, schema, _stacklevel=_stacklevel + 1)

    def table_from_markdown(
        self,
        table: str,
        id_from: list[str] | None = None,
        unsafe_trusted_ids: bool = False,
        schema: type[Schema] | None = None,
        _stacklevel: int = 1,
    ) -> Table:
        """A function for creating a table from its definition in markdown. If it
        contains a column ``_time``, rows will be split into batches with timestamps from ``_time`` column.
        Then ``_worker`` column will be interpreted as the id of a worker which will process the row and
        ``_diff`` column as an event type - with ``1`` treated as inserting row and ``-1`` as removing.
        """
        df = _markdown_to_pandas(table)
        return self.table_from_pandas(
            df, id_from, unsafe_trusted_ids, schema, _stacklevel=_stacklevel + 1
        )

    def persistence_config(self) -> persistence.Config | None:
        """Returns a persistece config to be used during run. Needs to be passed to ``pw.run``