markdown_to_html_loop.ipynb

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    "# MARKDOWN TO HTML\n",
    "\n",
    "This notebook converts markdown to HTML by iterating through a CSV where each cell (in a column named 'article') contains the full article as markdown.\n",
    "\n",
    "## STEPS\n",
    "\n",
    "1. upload a csv (make sure there is a column named `article`)\n",
    "2. run all\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# !pip install markdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import html2text\n",
    "import markdown\n",
    "\n",
    "\n",
    "csv_file = input(\"Input your csv filepath: \")  # Replace with your CSV file path\n",
    "df = pd.read_csv(csv_file)\n",
    "\n",
    "\n",
    "# Function to convert Markdown to HTML\n",
    "def markdown_to_html(md):\n",
    "    if pd.isna(md) or md.strip() == \"\":\n",
    "        return None\n",
    "    return markdown.markdown(md)\n",
    "\n",
    "\n",
    "# Loop through the 'article' column which now contains Markdown, convert the Markdown to HTML, and store the result in a new column 'article_html'\n",
    "df[\"article_html\"] = df[\"article\"].apply(markdown_to_html)\n",
    "\n",
    "# Save the modified DataFrame to a new CSV file\n",
    "df.to_csv(f\"{csv_file}_output.csv\", index=False)"
   ]
  }
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