Method __setitem__

tables/table.py:2242–2315

Set a row or a range of rows in the table. It takes different actions depending on the type of the *key* parameter: if it is an integer, the corresponding table row is set to *value* (a record or sequence capable of being converted to the table structure). If *key*

(
        self,
        key: int | slice | list[int] | list[bool] | np.ndarray,
        value: Any,
    )

            raise IndexError(f"Invalid index or slice: {key!r}")

    def __setitem__(
        self,
        key: int | slice | list[int] | list[bool] | np.ndarray,
        value: Any,
    ) -> int:
        """Set a row or a range of rows in the table.

        It takes different actions depending on the type of the *key*
        parameter: if it is an integer, the corresponding table row is
        set to *value* (a record or sequence capable of being converted
        to the table structure).  If *key* is a slice, the row slice
        determined by it is set to *value* (a record array or sequence
        capable of being converted to the table structure).

        In addition, NumPy-style point selections are supported.  In
        particular, if key is a list of row coordinates, the set of rows
        determined by it is set to value.  Furthermore, if key is an array of
        boolean values, only the coordinates where key is True are set to
        values from value.  Note that for the latter to work it is necessary
        that key list would contain exactly as many rows as the table has.

        Examples
        --------
        ::

            # Modify just one existing row
            table[2] = [456,'db2',1.2]

            # Modify two existing rows
            rows = np.rec.array(
                [[457,'db1',1.2],[6,'de2',1.3]], formats='i4,S3,f8'
            )
            table[1:30:2] = rows             # modify a table slice
            table[[1,3]] = rows              # only modifies rows 1 and 3
            table[[True,False,True]] = rows  # only modifies rows 0 and 2

        Which is equivalent to::

            table.modify_rows(start=2, rows=[456,'db2',1.2])
            rows = np.rec.array(
                [[457,'db1',1.2],[6,'de2',1.3]], formats='i4,S3,f8'
            )
            table.modify_rows(start=1, stop=3, step=2, rows=rows)
            table.modify_coordinates([1,3,2], rows)
            table.modify_coordinates([True, False, True], rows)

        Here, you can see how indexing can be used as a shorthand for the
        :meth:`Table.modify_rows` and :meth:`Table.modify_coordinates`
        methods.

        """
        self._g_check_open()
        self._v_file._check_writable()

        if is_idx(key):
            key = operator.index(key)

            # Index out of range protection