pathwaycom/pathway · error · ValueError

can't generate Schema based on an empty CSV file

Error message

can't generate Schema based on an empty CSV file

What it means

Raised by Pathway's CSV schema autogeneration (python/pathway/internals/schema.py:977). It builds a csv.DictReader over the file (with comment lines stripped) and requires fieldnames — the header row. If csv_reader.fieldnames is None, the reader saw no header at all, so no schema can be inferred, and a ValueError is thrown.

Source

Thrown at python/pathway/internals/schema.py:977

        Schema
    """

    def remove_comments_from_file(f: Iterable[str], comment_char: str | None):
        for line in f:
            if line.lstrip()[0] != comment_char:
                yield line

    with open(path) as f:
        csv_reader = csv.DictReader(
            remove_comments_from_file(f, comment_character),
            delimiter=delimiter,
            escapechar=escape,
            quoting=csv.QUOTE_ALL,
            quotechar=quote,
            doublequote=double_quote_escapes,
        )
        if csv_reader.fieldnames is None:
            raise ValueError("can't generate Schema based on an empty CSV file")
        column_names = csv_reader.fieldnames
        if num_parsed_rows is None:
            csv_data = list(csv_reader)
        else:
            csv_data = list(itertools.islice(csv_reader, num_parsed_rows))

    def choose_type(entries: list[str]):
        if len(entries) == 0:
            return Any
        if all(_is_parsable_to(s, int) for s in entries):
            return int
        if all(_is_parsable_to(s, float) for s in entries):
            return float
        return str

    column_types = {
        column_name: choose_type([row[column_name] for row in csv_data])
        for column_name in column_names

View on GitHub (pinned to fa2f74a464)

Solutions

1. Check the file is non-empty and starts with a header row before generating the schema
2. Verify comment_character does not strip the header line
3. Supply an explicit schema (a pw.Schema class or pw.schema_from_types) instead of relying on autodetection
4. If the file appears later, wait for it to contain data before building the schema

Example fix

# before
schema = pw.schema_from_csv("data.csv")  # data.csv is empty -> ValueError

# after
import os
if os.path.getsize("data.csv") == 0:
    raise RuntimeError("data.csv is empty; cannot infer schema")
schema = pw.schema_from_csv("data.csv")

import os

def csv_has_header(path: str) -> bool:
    return os.path.getsize(path) > 0

try:
    schema = pw.schema_from_csv(path)
except ValueError:
    schema = MyExplicitSchema  # fall back to a declared pw.Schema

When it happens

Trigger: Calling pw.csv_schema / pw.schema_from_csv (or a CSV connector in schema-autodetect mode) on a file that is empty, contains only blank lines, or contains only lines stripped as comments (comment_character matching every line); pointing at a wrong/empty file path.

Common situations: Tail-ing a file that has been created but not yet written to; a download/ETL step that produced a 0-byte CSV; comment_character that accidentally matches the header line; passing num_parsed_rows with a file whose data rows are all consumed as comments.

Related errors

• Failed to find the column '{column._name}' in table {column.
• Failed to detect the region of S3 bucket {bucket!r} (HTTP st
• SchemaRegistryHeader.value must be a str, got {type(self.val
• argument {name} has incorrect schema
• The column {column} doesn't belong to the target table {tabl

AI-assisted analysis of pathwaycom/pathway@fa2f74a464 (2026-08-15). Data as JSON: /api/errors/fcf55eed0a92444b. Report an issue: GitHub.