pathwaycom/pathway · error · ValueError

Column {api.TIME_PSEUDOCOLUMN} cannot contain negative times

Error message

Column {api.TIME_PSEUDOCOLUMN} cannot contain negative times.

What it means

The start_from_timestamp_ms parameter is only meaningful when start_from="timestamp". The shared validation helper rejects any other combination so that the encoded value passed to the engine is unambiguous.

Source

Thrown at python/pathway/debug/__init__.py:308

        if include_id:
            series = pd.Series(columns[name], dtype=dtype)
        else:
            # we need to remove original keys, otherwise pandas will use them to create index
            series = pd.Series(list(columns[name].values()), dtype=dtype)
        series_dict[name] = series
    index = keys if include_id else None
    res = pd.DataFrame(series_dict, index=index)
    return res


def _validate_dataframe(df: pd.DataFrame, stacklevel: int = 1) -> None:
    for pseudocolumn in api.PANDAS_PSEUDOCOLUMNS:
        if pseudocolumn in df.columns:
            if not pd.api.types.is_integer_dtype(df[pseudocolumn].dtype):
                raise ValueError(f"Column {pseudocolumn} has to contain integers only.")
    if api.TIME_PSEUDOCOLUMN in df.columns:
        if any(df[api.TIME_PSEUDOCOLUMN] < 0):
            raise ValueError(
                f"Column {api.TIME_PSEUDOCOLUMN} cannot contain negative times."
            )
        if any(df[api.TIME_PSEUDOCOLUMN] % 2 == 1):
            warn(
                "timestamps are required to be even; all timestamps will be doubled",
                stacklevel=stacklevel + 1,
            )
            df[api.TIME_PSEUDOCOLUMN] = 2 * df[api.TIME_PSEUDOCOLUMN]

    if api.DIFF_PSEUDOCOLUMN in df.columns:
        if any((df[api.DIFF_PSEUDOCOLUMN] != 1) & (df[api.DIFF_PSEUDOCOLUMN] != -1)):
            raise ValueError(
                f"Column {api.DIFF_PSEUDOCOLUMN} can only have 1 and -1 values."
            )


@check_arg_types
@trace_user_frame

View on GitHub (pinned to fa2f74a464)

Solutions

1. Remove start_from_timestamp_ms from the call when start_from is not "timestamp".
2. If you meant to start from a specific time, set start_from="timestamp" and keep the timestamp argument.

Example fix

# before
pw.io.kafka.read(..., start_from="end", start_from_timestamp_ms=1700000000000)

# after
pw.io.kafka.read(..., start_from="end")

def encode_start_from(start_from: str, ts: int | None) -> dict:
    if start_from == "timestamp":
        return {"start_from": "timestamp", "start_from_timestamp_ms": ts}
    assert ts is None, "start_from_timestamp_ms only valid with start_from='timestamp'"
    return {"start_from": start_from}

pw.io.kafka.read(..., **encode_start_from(start_from, ts))

When it happens

Trigger: Calling a Pathway IO read API with start_from set to anything other than "timestamp" (e.g. "start" or "end") while still passing a non-None start_from_timestamp_ms.

Common situations: User changes start_from from "timestamp" to "end" but leaves the old timestamp argument in place; or a config template supplies both keys and only one is updated when switching modes.

Related errors

• Failed to install dependencies
• 'subject' must be a non-empty string; got an empty string. S
• 'topic' must be a non-empty string; got {topic!r}. Kafka doe
• 'topic_name' must be a non-empty string; got an empty string
• Column {pseudocolumn} has to contain integers only.

AI-assisted analysis of pathwaycom/pathway@fa2f74a464 (2026-08-15). Data as JSON: /api/errors/8f99bc8a145c91c1. Report an issue: GitHub.