fix: return empty JSON for markdown tables with blank headers

[santhreal]

markdown_table_to_json hits EmptyDataError when |\n|-|. This PR fixes the regression with a focused test covering the case.

Summary by CodeRabbit

• Bug Fixes
  • Improved handling of Markdown tables when the header row contains no meaningful text.
  • Converting header-only or effectively empty/malformed Markdown tables to JSON now returns an empty list (with no errors).

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Pro Plus

Run ID: 2c2a313d-bc20-4a89-aee3-4c8c7c85ec01

📥 Commits

Reviewing files that changed from the base of the PR and between 42ee078 and a21b757.

📒 Files selected for processing (2)

• src/chonkie/utils/table_converter.py
• tests/test_table_converter.py

🚧 Files skipped from review as they are similar to previous changes (2)

• tests/test_table_converter.py
• src/chonkie/utils/table_converter.py

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📝 Walkthrough

Walkthrough

The table converter now treats Markdown tables with empty or blank header rows as empty data and returns an empty JSON list. Tests cover single-cell, empty-cell, and multi-column blank-header formats.

Changes

Empty Markdown Table Handling

Layer / File(s)	Summary
Guard empty headers and validate empty results src/chonkie/utils/table_converter.py, tests/test_table_converter.py	_read_markdown_table returns an empty DataFrame when the first parsed line has no meaningful header content. Tests verify empty JSON results for several empty-header formats.

Estimated code review effort: 1 (Trivial) | ~5 minutes

Poem

A rabbit found a table bare,
With empty headers floating there.
“No rows to parse,” it softly said,
And hopped away with tests well fed.
🐇

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately summarizes the main fix for markdown tables with blank headers returning empty JSON.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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[gemini-code-assist]

Code Review

This pull request aims to prevent pandas EmptyDataError when parsing markdown tables with empty header cells by returning an empty DataFrame, and adds corresponding test cases. The review feedback correctly points out that the proposed check not lines[0] is insufficient for tables with three or more empty columns because strip("|") only removes leading and trailing pipes, and suggests a more robust check to handle these cases.

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[gemini-code-assist]

The current check 'not lines[0]' only detects empty headers for tables with 1 or 2 columns. For tables with 3 or more columns (e.g., '| | | |'), 'lines[0]' will be evaluated as '|' (or containing multiple pipes) because 'strip("|")' only removes the leading and trailing pipes. As a result, 'not lines[0]' evaluates to False, and the function will still attempt to parse the table and return non-empty JSON with 'Unnamed' keys, which contradicts the PR's objective of returning empty JSON for tables with blank headers.\n\nTo ensure consistent behavior across any number of columns, we should check if the header line contains only pipes and whitespace.

    if len(lines) < 2 or not lines[0].replace('|', '').strip():\n        return pd.DataFrame()