Function write

python/pathway/io/fs/__init__.py:274–382

Writes ``table``'s stream of updates to a file in the given format. Args: table: Table to be written. filename: Path to the target output file. format: Format to use for data output. Currently, there are two supported formats: ``"json"`` and ``"csv"``.

(
    table: Table,
    filename: str | PathLike,
    format: Literal["json", "csv"],
    *,
    name: str | None = None,
    sort_by: Iterable[ColumnReference] | None = None,
)

@check_arg_types
@trace_user_frame
def write(
    table: Table,
    filename: str | PathLike,
    format: Literal["json", "csv"],
    *,
    name: str | None = None,
    sort_by: Iterable[ColumnReference] | None = None,
) -> None:
    """Writes ``table``'s stream of updates to a file in the given format.

    Args:
        table: Table to be written.
        filename: Path to the target output file.
        format: Format to use for data output. Currently, there are two supported
            formats: ``"json"`` and ``"csv"``.
        name: A unique name for the connector. If provided, this name will be used in
            logs and monitoring dashboards.
        sort_by: If specified, the output will be sorted in ascending order based on the
            values of the given columns within each minibatch. When multiple columns are provided,
            the corresponding value tuples will be compared lexicographically.

    Returns:
        None

    Example:

    In this simple example you can see how table output works.
    First, import Pathway Live Data Framework and create a table:

    >>> import pathway as pw
    >>> t = pw.debug.table_from_markdown("age owner pet \\n1 10 Alice dog \\n2 9 Bob cat \\n3 8 Alice cat")

    Consider you would want to output the stream of changes of this table in ``"csv"`` format.
    In order to do that you simply do:

    >>> pw.io.fs.write(t, "table.csv", format="csv")

    Now, let's see what you have on the output:

    .. code-block:: bash

        cat table.csv

    .. code-block:: csv

        age,owner,pet,time,diff
        10,"Alice","dog",0,1
        9,"Bob","cat",0,1
        8,"Alice","cat",0,1

    The first three columns clearly represent the data columns you have. The column ``time``
    represents the number of operations minibatch, in which each of the rows was read. In
    this example, since the data is static: you have ``0``. The ``diff`` is another
    element of this stream of updates. In this context, it is ``1`` because all three rows were read from
    the input. All in all, the extra information in ``time`` and ``diff`` columns - in this case -
    shows us that in the initial minibatch (``time = 0``), you have read three rows and all of
    them were added to the collection (``diff = 1``).