deepset-ai/haystack · error · ValueError

max_effective_lines must be at least 1.

Error message

max_effective_lines must be at least 1.

What it means

PythonCodeSplitter's __init__ requires max_effective_lines >= 1: the maximum number of effective code lines per chunk must be positive. Values below 1 make chunking impossible, so ValueError is raised.

Source

Thrown at haystack/components/preprocessors/python_code_splitter.py:126

            ``oversized_factor * max_effective_lines`` triggers the line-based secondary
            split with overlap.
        :param strip_docstrings: If ``True``, function/method/class docstrings are moved
            from the chunk content into ``meta["docstrings"]`` (source order). The
            module-level docstring is kept in place since it is itself a top-level unit.
        :param preserve_class_definition: If ``True`` (default), chunks that contain class
            members but not the class header are prefixed with the bare class signature
            (decorators plus the ``class Foo(...):`` lines) in source order.
        :param secondary_split_overlap: Line overlap for the secondary splitter; only used
            in the oversized fallback. The primary AST split never adds overlap.
        :param secondary_split_length: Lines per chunk for the secondary splitter.
            Defaults to ``max_effective_lines`` when ``None``.
        :raises ValueError: If any parameter is invalid (negative, zero where positive is
            required, or ``min_effective_lines > max_effective_lines``).
        """
        if min_effective_lines < 1:
            raise ValueError("min_effective_lines must be at least 1.")
        if max_effective_lines < 1:
            raise ValueError("max_effective_lines must be at least 1.")
        if min_effective_lines > max_effective_lines:
            raise ValueError("min_effective_lines must not be greater than max_effective_lines.")
        if expected_chars_per_line < 1:
            raise ValueError("expected_chars_per_line must be at least 1.")
        if oversized_factor < 1:
            raise ValueError("oversized_factor must be at least 1.")
        if secondary_split_overlap < 0:
            raise ValueError("secondary_split_overlap must be non-negative.")
        if secondary_split_length is not None and secondary_split_length < 1:
            raise ValueError("secondary_split_length must be at least 1.")

        self.min_effective_lines = min_effective_lines
        self.max_effective_lines = max_effective_lines
        self.expected_chars_per_line = expected_chars_per_line
        self.oversized_factor = oversized_factor
        self.strip_docstrings = strip_docstrings
        self.preserve_class_definition = preserve_class_definition
        self.secondary_split_overlap = secondary_split_overlap

View on GitHub (pinned to e318778c9b)

Solutions

  1. Pass max_effective_lines >= 1 and >= min_effective_lines, e.g. max_effective_lines=30.
  2. Omit the parameter to use the default.
  3. Clamp dynamic values: max_effective_lines=max(1, computed).
  4. Validate the whole (min, max) pair together before construction.

Example fix

// before
PythonCodeSplitter(max_effective_lines=0)
// after
PythonCodeSplitter(min_effective_lines=5, max_effective_lines=30)
Defensive patterns

Strategy: validation

Validate before calling

max_effective_lines = max(1, int(max_effective_lines))
if max_effective_lines < min_effective_lines:
    max_effective_lines = min_effective_lines

Type guard

def is_valid_line_range(min_l, max_l) -> bool:
    return is_positive_int(min_l) and is_positive_int(max_l) and min_l <= max_l

Try / catch

try:
    splitter = PythonCodeSplitter(max_effective_lines=max_lines)
except ValueError as e:
    logging.warning("Invalid max_effective_lines (%s), using default", e)
    splitter = PythonCodeSplitter()

Prevention

When it happens

Trigger: Calling PythonCodeSplitter(max_effective_lines=0) or negative, typically from a bad config value, a division result, or an env var defaulting to 0.

Common situations: Zero defaults in config files, tuning experiments setting the max below the minimum, or unit errors (lines vs tokens confusion).

Related errors


AI-assisted analysis of deepset-ai/haystack@e318778c9b (2026-08-30). Data as JSON: /api/errors/08109ee1a9693c15. Report an issue: GitHub.