Markdown Table Generator.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "053406b3",
   "metadata": {},
   "source": [
    "# Markdown Table Generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4ec69e1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def add_header(mk_text, header):\n",
    "    \"\"\"\n",
    "    Adds a header row to a Markdown table represented as text.\n",
    "\n",
    "    Parameters:\n",
    "        mk_text (str): The Markdown table text.\n",
    "        header (str): The header text to add.\n",
    "\n",
    "    Returns:\n",
    "        str: The updated Markdown table text with the header row added.\n",
    "    \"\"\"\n",
    "    # Validate mk_text parameter\n",
    "    if not isinstance(mk_text, str):\n",
    "        raise ValueError(\"The mk_text parameter must be a string.\")\n",
    "\n",
    "    # Validate header parameter\n",
    "    if not isinstance(header, str):\n",
    "        raise ValueError(\"The header parameter must be a string.\")\n",
    "\n",
    "    mk_lines = tuple(filter(None, mk_text.strip().split('\\n')))\n",
    "\n",
    "    if not mk_lines:\n",
    "        header_line, table_line, other_lines = \"|\", \"|\", []\n",
    "    elif len(mk_lines) == 1:\n",
    "        header_line, table_line, other_lines = mk_lines[0], \"|\", []\n",
    "    else:\n",
    "        header_line, table_line, *other_lines = mk_lines\n",
    "\n",
    "    header_line += header + '|'\n",
    "    table_line += '---|'\n",
    "\n",
    "    mk_text = '\\n'.join([header_line, table_line] + other_lines)\n",
    "    return mk_text\n",
    "\n",
    "\n",
    "\n",
    "def add_row(mk_text, row):\n",
    "    \"\"\"\n",
    "    Adds a row to a Markdown table represented as text.\n",
    "\n",
    "    Parameters:\n",
    "        mk_text (str): The Markdown table text.\n",
    "        row (str): The row text to add.\n",
    "\n",
    "    Returns:\n",
    "        str: The updated Markdown table text with the row added.\n",
    "\n",
    "    Raises:\n",
    "        AssertionError: If the number of lines in mk_text is less than 2.\n",
    "        ValueError: If mk_text or row parameters are not strings.\n",
    "    \"\"\"\n",
    "    # Validate mk_text parameter\n",
    "    if not isinstance(mk_text, str):\n",
    "        raise ValueError(\"The mk_text parameter must be a string.\")\n",
    "\n",
    "    # Validate row parameter\n",
    "    if not isinstance(row, str):\n",
    "        raise ValueError(\"The row parameter must be a string.\")\n",
    "\n",
    "    mk_lines = tuple(filter(None, mk_text.strip().split('\\n')))\n",
    "    assert len(mk_lines) >= 2, 'Header Lines Missing!'\n",
    "\n",
    "    header_line, table_line, *other_lines = mk_lines\n",
    "\n",
    "    columns = tuple(filter(None, header_line.split('|')))\n",
    "\n",
    "    if not row:\n",
    "        row = '|' + ' |' * len(columns)\n",
    "    other_lines.append(row)\n",
    "\n",
    "    mk_text = '\\n'.join([header_line, table_line] + other_lines)\n",
    "    return mk_text\n",
    "\n",
    "\n",
    "def _get_max_length(d):\n",
    "    max_length = 0\n",
    "    for key in d.keys():\n",
    "        value = d.get(key, [])\n",
    "        max_length = max(max_length, len(value))\n",
    "    return max_length\n",
    "\n",
    "\n",
    "def _fill_value(string, sep, pos, value=''):\n",
    "    \"\"\"\n",
    "    Fills a value into a string at a specified position.\n",
    "\n",
    "    Parameters:\n",
    "        string (str): The input string.\n",
    "        sep (str): The separator used for splitting the string.\n",
    "        pos (int): The position at which to insert the value.\n",
    "        value (str): The value to insert (default: '').\n",
    "\n",
    "    Returns:\n",
    "        str: The updated string with the value inserted.\n",
    "\n",
    "    Raises:\n",
    "        ValueError: If the string or sep parameter is not a string, or the pos parameter is not an integer.\n",
    "    \"\"\"\n",
    "    # Validate string parameter\n",
    "    if not isinstance(string, str):\n",
    "        raise ValueError(\"The string parameter must be a string.\")\n",
    "\n",
    "    # Validate sep parameter\n",
    "    if not isinstance(sep, str):\n",
    "        raise ValueError(\"The sep parameter must be a string.\")\n",
    "\n",
    "    # Validate pos parameter\n",
    "    if not isinstance(pos, int):\n",
    "        raise ValueError(\"The pos parameter must be an integer.\")\n",
    "\n",
    "    split_string = string.split(sep)\n",
    "    num_elements = len(split_string)\n",
    "\n",
    "    # Handle pos out of range\n",
    "    if pos < 0 or pos >= num_elements:\n",
    "        raise IndexError(\"Position is out of range.\")\n",
    "\n",
    "    updated_string = sep.join(split_string[:pos] + [value] + split_string[pos+1:])\n",
    "    return updated_string\n",
    "\n",
    "\n",
    "def add_values(mk_text, pos, data):\n",
    "    \"\"\"\n",
    "    Adds values to a specific column position in a Markdown table represented as text.\n",
    "\n",
    "    Parameters:\n",
    "        mk_text (str): The Markdown table text.\n",
    "        pos (int): The column position to add the values.\n",
    "        data (list): The list of values to add to the table.\n",
    "\n",
    "    Returns:\n",
    "        str: The updated Markdown table text with the values added.\n",
    "\n",
    "    Raises:\n",
    "        AssertionError: If the number of lines in mk_text is less than 2.\n",
    "        IndexError: If the specified column position is out of range.\n",
    "        ValueError: If mk_text parameter is not a string or data parameter is not a list.\n",
    "    \"\"\"\n",
    "    # Validate mk_text parameter\n",
    "    if not isinstance(mk_text, str):\n",
    "        raise ValueError(\"The mk_text parameter must be a string.\")\n",
    "\n",
    "    # Validate pos parameter\n",
    "    if not isinstance(pos, int):\n",
    "        raise ValueError(\"The pos parameter must be an integer.\")\n",
    "\n",
    "    # Validate data parameter\n",
    "    if not isinstance(data, list):\n",
    "        raise ValueError(\"The data parameter must be a list.\")\n",
    "\n",
    "    mk_lines = tuple(filter(None, mk_text.strip().split('\\n')))\n",
    "    assert len(mk_lines) >= 2, 'Header Lines Missing!'\n",
    "\n",
    "    header_line, table_line, *other_lines = mk_lines\n",
    "    new_lines = []\n",
    "\n",
    "    if pos < 0 or pos >= header_line.count('|'):\n",
    "        raise IndexError(\"Column position is out of range.\")\n",
    "\n",
    "    for line, value in list(zip(other_lines, data)):\n",
    "        text = f'[{value[0]}]({value[1]})'\n",
    "        line = _fill_value(line, '|', pos, text)\n",
    "        new_lines.append(line)\n",
    "        other_lines.pop(0)\n",
    "\n",
    "    if len(other_lines) > 0:\n",
    "        new_lines += other_lines\n",
    "\n",
    "    mk_text = '\\n'.join([header_line, table_line] + new_lines)\n",
    "    return mk_text\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e1e16c8a",
   "metadata": {},
   "source": [
    "## Github Table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d2916b07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Python': [('Python Beginners Guide',\n",
       "   'https://github.com/jamwine/Python-Beginners-Guide'),\n",
       "  ('Data Structures & Algorithms',\n",
       "   'https://github.com/jamwine/Data-Structures-and-Algorithm'),\n",
       "  ('python-cookiecutter', 'https://github.com/jamwine/python-cookiecutter'),\n",
       "  ('python-utils', 'https://github.com/jamwine/python-utils'),\n",
       "  ('Images Using Python', 'https://github.com/jamwine/Images-using-Python'),\n",
       "  ('Genetic Algorithms', 'https://github.com/jamwine/Genetic-Algorithms')],\n",
       " 'Data Science': [('Statistics', 'https://github.com/jamwine/Statistics'),\n",
       "  ('Probability and Random Processes',\n",
       "   'https://github.com/jamwine/Probability-and-Random-Processes'),\n",
       "  ('Machine learning', 'https://github.com/jamwine/Machine-Learning'),\n",
       "  ('TensorFlow', 'https://github.com/jamwine/Tensorflow')],\n",
       " 'Data Engineering': [('SQL', 'https://github.com/jamwine/SQL-in-Python'),\n",
       "  ('Unix', 'https://github.com/jamwine/Unix'),\n",
       "  ('Docker', 'https://github.com/jamwine/Docker'),\n",
       "  ('Apache Airflow', 'https://github.com/jamwine/Apache-Airflow'),\n",
       "  ('Apache Beam', 'https://github.com/jamwine/Apache-Beam'),\n",
       "  ('GCP Qwiklabs', 'https://github.com/jamwine/GCP-Qwiklabs')],\n",
       " 'Data Analytics & Visualizations': [('Pandas',\n",
       "   'https://github.com/jamwine/Learn-Pandas'),\n",
       "  ('Numpy', 'https://github.com/jamwine/Learn-NumPy'),\n",
       "  ('Matplotlib', 'https://github.com/jamwine/Data-Visualization'),\n",
       "  ('Pygal', 'https://github.com/jamwine/Pygal'),\n",
       "  ('Exploratory-Data-Analysis',\n",
       "   'https://github.com/jamwine/Exploratory-Data-Analysis')],\n",
       " 'Web': [('Web-Fundamentals (HTML & CSS)',\n",
       "   'https://github.com/jamwine/Web-Dev-Fundamentals'),\n",
       "  ('Javascript-Beginner-Guide',\n",
       "   'https://github.com/jamwine/Javascript-Beginner-Guide'),\n",
       "  ('Web-Scraping', 'https://github.com/jamwine/Web-Scraping'),\n",
       "  ('Django', 'https://github.com/jamwine/Django'),\n",
       "  ('React-Projects', 'https://github.com/jamwine/React-Projects')]}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = {'Python' : [('Python Beginners Guide', 'https://github.com/jamwine/Python-Beginners-Guide'),\n",
    "                    ('Data Structures & Algorithms', 'https://github.com/jamwine/Data-Structures-and-Algorithm'),\n",
    "                    ('python-cookiecutter', 'https://github.com/jamwine/python-cookiecutter'),\n",
    "                    ('python-utils', 'https://github.com/jamwine/python-utils'),\n",
    "                    ('Images Using Python', 'https://github.com/jamwine/Images-using-Python'),\n",
    "                    ('Genetic Algorithms', 'https://github.com/jamwine/Genetic-Algorithms'),\n",
    "                   ],\n",
    "    \n",
    "        \"Data Science\" : [('Statistics', 'https://github.com/jamwine/Statistics'),\n",
    "                          ('Probability and Random Processes', 'https://github.com/jamwine/Probability-and-Random-Processes'),\n",
    "                          ('Machine learning', 'https://github.com/jamwine/Machine-Learning'),\n",
    "                          ('TensorFlow', 'https://github.com/jamwine/Tensorflow')],\n",
    "    \n",
    "        \"Data Engineering\" : [('SQL', 'https://github.com/jamwine/SQL-in-Python'),\n",
    "                              ('Unix', 'https://github.com/jamwine/Unix'),\n",
    "                              ('Docker', 'https://github.com/jamwine/Docker'),\n",
    "                              ('Apache Airflow', 'https://github.com/jamwine/Apache-Airflow'),\n",
    "                              ('Apache Beam', 'https://github.com/jamwine/Apache-Beam'),\n",
    "                              ('GCP Qwiklabs', 'https://github.com/jamwine/GCP-Qwiklabs'),],\n",
    "                             \n",
    "    \n",
    "        \"Data Analytics & Visualizations\" : [('Pandas', 'https://github.com/jamwine/Learn-Pandas'),\n",
    "                                             ('Numpy', 'https://github.com/jamwine/Learn-NumPy'),\n",
    "                                             ('Matplotlib', 'https://github.com/jamwine/Data-Visualization'),\n",
    "                                             ('Pygal', 'https://github.com/jamwine/Pygal'),\n",
    "                                             ('Exploratory-Data-Analysis', 'https://github.com/jamwine/Exploratory-Data-Analysis')],\n",
    "        \n",
    "        \n",
    "        \"Web\" : [('Web-Fundamentals (HTML & CSS)', \"https://github.com/jamwine/Web-Dev-Fundamentals\"),\n",
    "                 ('Javascript-Beginner-Guide', 'https://github.com/jamwine/Javascript-Beginner-Guide'),\n",
    "                 ('Web-Scraping', 'https://github.com/jamwine/Web-Scraping'),\n",
    "                 ('Django', 'https://github.com/jamwine/Django'),\n",
    "                 ('React-Projects', 'https://github.com/jamwine/React-Projects')],\n",
    "        \n",
    "    \n",
    "       }\n",
    "\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c1649e41",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|Python|Data Science|Data Engineering|Data Analytics & Visualizations|Web|\n",
      "|---|---|---|---|---|\n",
      "|[Python Beginners Guide](https://github.com/jamwine/Python-Beginners-Guide)|[Statistics](https://github.com/jamwine/Statistics)|[SQL](https://github.com/jamwine/SQL-in-Python)|[Pandas](https://github.com/jamwine/Learn-Pandas)|[Web-Fundamentals (HTML & CSS)](https://github.com/jamwine/Web-Dev-Fundamentals)|\n",
      "|[Data Structures & Algorithms](https://github.com/jamwine/Data-Structures-and-Algorithm)|[Probability and Random Processes](https://github.com/jamwine/Probability-and-Random-Processes)|[Unix](https://github.com/jamwine/Unix)|[Numpy](https://github.com/jamwine/Learn-NumPy)|[Javascript-Beginner-Guide](https://github.com/jamwine/Javascript-Beginner-Guide)|\n",
      "|[python-cookiecutter](https://github.com/jamwine/python-cookiecutter)|[Machine learning](https://github.com/jamwine/Machine-Learning)|[Docker](https://github.com/jamwine/Docker)|[Matplotlib](https://github.com/jamwine/Data-Visualization)|[Web-Scraping](https://github.com/jamwine/Web-Scraping)|\n",
      "|[python-utils](https://github.com/jamwine/python-utils)|[TensorFlow](https://github.com/jamwine/Tensorflow)|[Apache Airflow](https://github.com/jamwine/Apache-Airflow)|[Pygal](https://github.com/jamwine/Pygal)|[Django](https://github.com/jamwine/Django)|\n",
      "|[Images Using Python](https://github.com/jamwine/Images-using-Python)| |[Apache Beam](https://github.com/jamwine/Apache-Beam)|[Exploratory-Data-Analysis](https://github.com/jamwine/Exploratory-Data-Analysis)|[React-Projects](https://github.com/jamwine/React-Projects)|\n",
      "|[Genetic Algorithms](https://github.com/jamwine/Genetic-Algorithms)| |[GCP Qwiklabs](https://github.com/jamwine/GCP-Qwiklabs)| | |\n"
     ]
    }
   ],
   "source": [
    "mk_text = ''\n",
    "columns = data.keys()\n",
    "for col in columns:\n",
    "    mk_text = add_header(mk_text, col)\n",
    "\n",
    "max_length = _get_max_length(data)\n",
    "\n",
    "for _ in range(max_length):\n",
    "    mk_text = add_row(mk_text, row='')\n",
    "\n",
    "for i, key in enumerate(data.keys(), start=1):\n",
    "    mk_text = add_values(mk_text, i, data.get(key))\n",
    "\n",
    "print(mk_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "427b43f6",
   "metadata": {},
   "source": [
    "### Inserting a new column `Others`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3449bfaf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|Python|Data Science|Data Engineering|Data Analytics & Visualizations|Web|Others|\n",
      "|---|---|---|---|---|---|\n",
      "|[Python Beginners Guide](https://github.com/jamwine/Python-Beginners-Guide)|[Statistics](https://github.com/jamwine/Statistics)|[SQL](https://github.com/jamwine/SQL-in-Python)|[Pandas](https://github.com/jamwine/Learn-Pandas)|[Web-Fundamentals (HTML & CSS)](https://github.com/jamwine/Web-Dev-Fundamentals)|[System Design](https://github.com/jamwine/System-Design)\n",
      "|[Data Structures & Algorithms](https://github.com/jamwine/Data-Structures-and-Algorithm)|[Probability and Random Processes](https://github.com/jamwine/Probability-and-Random-Processes)|[Unix](https://github.com/jamwine/Unix)|[Numpy](https://github.com/jamwine/Learn-NumPy)|[Javascript-Beginner-Guide](https://github.com/jamwine/Javascript-Beginner-Guide)|[Data](https://github.com/jamwine/Data)\n",
      "|[python-cookiecutter](https://github.com/jamwine/python-cookiecutter)|[Machine learning](https://github.com/jamwine/Machine-Learning)|[Docker](https://github.com/jamwine/Docker)|[Matplotlib](https://github.com/jamwine/Data-Visualization)|[Web-Scraping](https://github.com/jamwine/Web-Scraping)|[Markdown Table Generator](https://github.com/jamwine/Markdown)\n",
      "|[python-utils](https://github.com/jamwine/python-utils)|[TensorFlow](https://github.com/jamwine/Tensorflow)|[Apache Airflow](https://github.com/jamwine/Apache-Airflow)|[Pygal](https://github.com/jamwine/Pygal)|[Django](https://github.com/jamwine/Django)|\n",
      "|[Images Using Python](https://github.com/jamwine/Images-using-Python)| |[Apache Beam](https://github.com/jamwine/Apache-Beam)|[Exploratory-Data-Analysis](https://github.com/jamwine/Exploratory-Data-Analysis)|[React-Projects](https://github.com/jamwine/React-Projects)|\n",
      "|[Genetic Algorithms](https://github.com/jamwine/Genetic-Algorithms)| |[GCP Qwiklabs](https://github.com/jamwine/GCP-Qwiklabs)| | |\n"
     ]
    }
   ],
   "source": [
    "data['Others'] = [('System Design', 'https://github.com/jamwine/System-Design'),\n",
    "                  ('Data', 'https://github.com/jamwine/Data'),\n",
    "                  ('Markdown Table Generator', 'https://github.com/jamwine/Markdown')\n",
    "                 ]\n",
    "\n",
    "mk_text = add_header(mk_text, 'Others')\n",
    "mk_text = add_values(mk_text, pos=6, data = data.get('Others'))\n",
    "\n",
    "print(mk_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5be01222",
   "metadata": {},
   "source": [
    "#### Copy and paste the result in the bottom Markdown cell"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6493943",
   "metadata": {},
   "source": [
    "|Python|Data Science|Data Engineering|Data Analytics & Visualizations|Web|Others|\n",
    "|---|---|---|---|---|---|\n",
    "|[Python Beginners Guide](https://github.com/jamwine/Python-Beginners-Guide)|[Statistics](https://github.com/jamwine/Statistics)|[SQL](https://github.com/jamwine/SQL-in-Python)|[Pandas](https://github.com/jamwine/Learn-Pandas)|[Web-Fundamentals (HTML & CSS)](https://github.com/jamwine/Web-Dev-Fundamentals)|[System Design](https://github.com/jamwine/System-Design)\n",
    "|[Data Structures & Algorithms](https://github.com/jamwine/Data-Structures-and-Algorithm)|[Probability and Random Processes](https://github.com/jamwine/Probability-and-Random-Processes)|[Unix](https://github.com/jamwine/Unix)|[Numpy](https://github.com/jamwine/Learn-NumPy)|[Javascript-Beginner-Guide](https://github.com/jamwine/Javascript-Beginner-Guide)|[Data](https://github.com/jamwine/Data)\n",
    "|[python-cookiecutter](https://github.com/jamwine/python-cookiecutter)|[Machine learning](https://github.com/jamwine/Machine-Learning)|[Docker](https://github.com/jamwine/Docker)|[Matplotlib](https://github.com/jamwine/Data-Visualization)|[Web-Scraping](https://github.com/jamwine/Web-Scraping)|[Markdown Table Generator](https://github.com/jamwine/Markdown)\n",
    "|[python-utils](https://github.com/jamwine/python-utils)|[TensorFlow](https://github.com/jamwine/Tensorflow)|[Apache Airflow](https://github.com/jamwine/Apache-Airflow)|[Pygal](https://github.com/jamwine/Pygal)|[Django](https://github.com/jamwine/Django)|\n",
    "|[Images Using Python](https://github.com/jamwine/Images-using-Python)| |[Apache Beam](https://github.com/jamwine/Apache-Beam)|[Exploratory-Data-Analysis](https://github.com/jamwine/Exploratory-Data-Analysis)|[React-Projects](https://github.com/jamwine/React-Projects)|\n",
    "|[Genetic Algorithms](https://github.com/jamwine/Genetic-Algorithms)| |[GCP Qwiklabs](https://github.com/jamwine/GCP-Qwiklabs)| | |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6a91597",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "300840db",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "253bb9ba",
   "metadata": {},
   "source": [
    "### Markdown Formatted text to Normal text"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0edb38f",
   "metadata": {},
   "source": [
    "```python\n",
    "import markdown # pip install markdown\n",
    "from bs4 import BeautifulSoup # pip install beautifulsoup4\n",
    "\n",
    "def md_to_text(md):\n",
    "    html = markdown.markdown(md)\n",
    "    soup = BeautifulSoup(html, features='html.parser')\n",
    "    return soup.get_text()\n",
    "\n",
    "def example(mk_text = '**A** [B](http://example.com) <!-- C -->'):\n",
    "    text = md_to_text(mk_text)\n",
    "    print(text)\n",
    "    \n",
    "example(mk_text)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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