wehub-resource-sync
155 lines
4.6 KiB
Python
155 lines
4.6 KiB
Python
#!/usr/bin/env python3
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"""
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Convert Crawl4AI URL Seeder tutorial markdown to Colab notebook format
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"""
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import json
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import re
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from pathlib import Path
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def parse_markdown_to_cells(markdown_content):
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"""Parse markdown content and convert to notebook cells"""
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cells = []
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# Split content by cell markers
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lines = markdown_content.split('\n')
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# Extract the header content before first cell marker
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header_lines = []
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i = 0
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while i < len(lines) and not lines[i].startswith('# cell'):
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header_lines.append(lines[i])
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i += 1
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# Add header as markdown cell if it exists
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if header_lines:
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header_content = '\n'.join(header_lines).strip()
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if header_content:
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cells.append({
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"cell_type": "markdown",
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"metadata": {},
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"source": header_content.split('\n')
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})
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# Process cells marked with # cell X type:Y
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current_cell_content = []
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current_cell_type = None
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while i < len(lines):
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line = lines[i]
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# Check for cell marker
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cell_match = re.match(r'^# cell (\d+) type:(markdown|code)$', line)
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if cell_match:
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# Save previous cell if exists
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if current_cell_content and current_cell_type:
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content = '\n'.join(current_cell_content).strip()
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if content:
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if current_cell_type == 'code':
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cells.append({
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"cell_type": "code",
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"execution_count": None,
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"metadata": {},
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"outputs": [],
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"source": content.split('\n')
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})
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else:
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cells.append({
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"cell_type": "markdown",
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"metadata": {},
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"source": content.split('\n')
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})
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# Start new cell
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current_cell_type = cell_match.group(2)
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current_cell_content = []
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else:
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# Add line to current cell
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current_cell_content.append(line)
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i += 1
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# Add last cell if exists
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if current_cell_content and current_cell_type:
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content = '\n'.join(current_cell_content).strip()
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if content:
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if current_cell_type == 'code':
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cells.append({
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"cell_type": "code",
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"execution_count": None,
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"metadata": {},
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"outputs": [],
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"source": content.split('\n')
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})
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else:
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cells.append({
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"cell_type": "markdown",
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"metadata": {},
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"source": content.split('\n')
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})
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return cells
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def create_colab_notebook(cells):
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"""Create a Colab notebook structure"""
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notebook = {
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"name": "Crawl4AI_URL_Seeder_Tutorial.ipynb",
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"provenance": [],
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"collapsed_sections": [],
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"toc_visible": True
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": cells
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}
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return notebook
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def main():
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# Read the markdown file
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md_path = Path("tutorial_url_seeder.md")
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if not md_path.exists():
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print(f"Error: {md_path} not found!")
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return
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print(f"Reading {md_path}...")
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with open(md_path, 'r', encoding='utf-8') as f:
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markdown_content = f.read()
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# Parse markdown to cells
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print("Parsing markdown content...")
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cells = parse_markdown_to_cells(markdown_content)
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print(f"Created {len(cells)} cells")
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# Create notebook
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print("Creating Colab notebook...")
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notebook = create_colab_notebook(cells)
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# Save notebook
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output_path = Path("Crawl4AI_URL_Seeder_Tutorial.ipynb")
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with open(output_path, 'w', encoding='utf-8') as f:
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json.dump(notebook, f, indent=2, ensure_ascii=False)
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print(f"✅ Successfully created {output_path}")
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print(f" - Total cells: {len(cells)}")
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print(f" - Markdown cells: {sum(1 for c in cells if c['cell_type'] == 'markdown')}")
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print(f" - Code cells: {sum(1 for c in cells if c['cell_type'] == 'code')}")
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if __name__ == "__main__":
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main() |