markdown-table-extractor 0.1.1

Robust structured data extraction from markdown text, built with literate programming using marimo notebooks

Markdown Table Extractor

Robust structured data extraction from markdown text, built with literate programming using marimo notebooks.

✨ Features

• ✅ Proper separator detection - Handles :--:, ---:, :--- alignment syntax
• ✅ Caption detection - Finds "Table 3. Results" patterns above tables
• ✅ Continuation merging - Automatically merges "Table 3 (Continued)" tables
• ✅ HTML cleanup - Removes <br> and other artifacts from headers
• ✅ Sub-header handling - Merges multi-level headers properly
• ✅ LLM extraction - AI-powered fallback for complex edge cases
• ✅ Type-safe - Full type hints with py.typed marker
• ✅ Literate programming - Each module is a marimo notebook

📚 Literate Programming with Marimo

Unlike traditional packages, every module is a marimo notebook:

src/markdown_table_extractor/core/
├── models.py      # 📓 Data classes notebook
├── parser.py      # 📓 Markdown parsing notebook  
├── cleaner.py     # 📓 Data cleaning notebook
├── merger.py      # 📓 Table merging notebook
└── extractor.py   # 📓 Main extraction notebook

Each file is simultaneously:

• A Python module - Import normally: from markdown_table_extractor import extract_tables
• A notebook - Edit interactively: marimo edit src/.../parser.py
• Documentation - Read the code alongside explanations
• A script - Run standalone: python src/.../parser.py

This follows the literate programming paradigm pioneered by Donald Knuth, similar to nbdev but with marimo's pure-Python notebooks.

Installation

# Using uv (recommended)
uv add markdown-table-extractor

# With LLM support (OpenAI/Anthropic)
uv add "markdown-table-extractor[llm]"

# Development with marimo
uv add "markdown-table-extractor[notebook]"

Quick Start

Simple Usage

from markdown_table_extractor import extract_tables

markdown = """
| Name | Age |
| --- | --- |
| Alice | 30 |
| Bob | 25 |
"""

tables = extract_tables(markdown)
print(tables[0])
#    Name  Age
# 0  Alice   30
# 1    Bob   25

Full API with Metadata

from markdown_table_extractor import extract_markdown_tables, TableMergeStrategy

result = extract_markdown_tables(
    markdown_text,
    merge_strategy=TableMergeStrategy.IDENTICAL_HEADERS,
    detect_captions=True,
    skip_sub_headers=True
)

for table in result:
    print(f"Caption: {table.caption}")
    print(f"Shape: {table.dataframe.shape}")
    print(table.dataframe)

Exploring the Notebooks

# Open any module as an interactive notebook
marimo edit src/markdown_table_extractor/core/parser.py

# Run the interactive demo
marimo edit src/markdown_table_extractor/core/extractor.py

API Reference

Core Functions

Function	Description
extract_tables(text)	Simple API returning list[DataFrame]
extract_markdown_tables(text, ...)	Full API returning ExtractionResult

Models

Class	Description
ExtractedTable	Single table with metadata (caption, line numbers)
ExtractionResult	Collection of tables with errors and merge count
TableMergeStrategy	Enum: NONE, IDENTICAL_HEADERS, COMPATIBLE_COLUMNS

Utilities (from parser.py notebook)

Function	Description
is_separator_row(line)	Check if line is a table separator
is_table_row(line)	Check if line is any table row
parse_table_row(line)	Extract cell values from a row
detect_caption(lines, start)	Find table caption

Utilities (from cleaner.py notebook)

Function	Description
clean_column_name(name)	Remove HTML artifacts from header
headers_match(h1, h2)	Check if headers are compatible
normalize_headers(headers)	Canonical form for comparison

Development

# Clone and setup
git clone https://github.com/username/markdown-table-extractor
cd markdown-table-extractor
uv sync --all-extras

# Run tests
uv run pytest

# Run linter
uv run ruff check src tests

# Type checking
uv run mypy src

# Edit any module interactively
uv run marimo edit src/markdown_table_extractor/core/parser.py

Project Structure

markdown-table-extractor/
├── pyproject.toml              # Package configuration
├── README.md
├── src/
│   └── markdown_table_extractor/
│       ├── __init__.py         # Public API
│       ├── py.typed            # Type hints marker
│       └── core/
│           ├── __init__.py     # Re-exports from notebooks
│           ├── models.py       # 📓 Data classes notebook
│           ├── parser.py       # 📓 Parsing utilities notebook
│           ├── cleaner.py      # 📓 Cleaning utilities notebook
│           ├── merger.py       # 📓 Merging logic notebook
│           └── extractor.py    # 📓 Main extraction notebook
└── tests/
    └── test_extractor.py

Why Marimo Notebooks?

Traditional	Marimo Literate
Code in .py, docs separate	Code + docs in same file
Read code, guess intent	Read explanation alongside code
Tests in separate files	Interactive tests in notebook
Static documentation	Interactive documentation
Jupyter: JSON format	Pure Python, Git-friendly

Why Not nbdev?

nbdev	marimo
Jupyter notebooks (JSON)	Pure Python files
Requires export step	Direct import
`#	export` directives
Complex build process	Just Python

License

MIT License - see LICENSE for details.

Contributing

Contributions welcome! Edit the notebooks, add tests, and submit PRs.