{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "aa822bce-181c-42bc-a695-db004af6fa21",
   "metadata": {},
   "source": [
    "# Lesson 04 in-class demo\n",
    "\n",
    "## 1. Data types\n",
    "\n",
    "### 1.1. Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "af516941-4bd2-4628-b384-8fd3edb02e9b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello world!\n"
     ]
    }
   ],
   "source": [
    "my_string = 'Hello world!'\n",
    "print(my_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c17287ec-8f25-404b-bd33-2c22d1f533c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "str"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(my_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b01f5697-76fc-4ac6-ba3c-28772cebe177",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(my_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6dfafe53-9da2-496a-9e65-bee56ebe65fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "lower_string = my_string.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d71b04ef-84a7-476e-a07b-1094f9effd44",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hello world!\n"
     ]
    }
   ],
   "source": [
    "print(lower_string)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5141666f-80d9-44ec-a268-a51a8aac51eb",
   "metadata": {},
   "source": [
    "### 1.2. Numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "716f5bec-3111-4cbe-9db3-805121fae850",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32\n"
     ]
    }
   ],
   "source": [
    "my_int = 32\n",
    "print(my_int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9ab7de70-d2a7-46df-9f7f-54d0e850abd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(my_int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "58d2d8c6-8735-4471-bb25-fa02e8b880a9",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_float = 32.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8c844c76-427d-4d3e-8b4f-13d0f2cba773",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32.0\n"
     ]
    }
   ],
   "source": [
    "print(my_float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d3e83fb2-b065-435f-bbaa-df8d4275a71f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(my_float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f2904641-b26c-4ce3-9c51-d3f0f3770669",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32.0"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_float"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "067a2a02-f9b6-4865-a36a-f09c5422f2f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "int(my_float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "121b7ca3-37d1-4548-98a7-2ae084b3b026",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "int"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(int(my_float))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "afe8dc40-0411-4f54-a43b-508c64420a41",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32.0\n"
     ]
    }
   ],
   "source": [
    "print(my_float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "0a9f99b5-de86-4a18-ba40-b833fb9d9b61",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_float = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "b513da24-70ed-4de8-9c13-ac4a437b2e69",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "print(my_float)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b37afc7f-160d-48b9-8f28-0de251ba4f8e",
   "metadata": {},
   "source": [
    "### 1.3. Lists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "fdfce683-3868-4c30-824f-c11f877725ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_list = ['zero', 'one', 'two', 'three']\n",
    "type(my_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "38976328-db06-4070-831e-dfde4a0759ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(my_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "baec64a6-6854-4a28-8f35-3ceddc4b26ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['zero', 'one', 'two', 'three']\n"
     ]
    }
   ],
   "source": [
    "print(my_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c3290ce5-93e1-4a67-a2ba-726fb72428dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_list.append('four')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e3239a7e-02e2-4265-8571-1a61769066ac",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['zero', 'one', 'two', 'three', 'four']\n"
     ]
    }
   ],
   "source": [
    "print(my_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a1fd81a-60b3-4cab-a87f-654e0b6630af",
   "metadata": {},
   "source": [
    "### 1.4. Dictionaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bba940cb-38d7-45f3-8108-eefef1fc26f0",
   "metadata": {},
   "outputs": [],
   "source": [
    "my_dict = {\n",
    "    'name': 'George',\n",
    "    'State': 'NY',\n",
    "    'status': 'Caffinated',\n",
    "    'Age': 999,\n",
    "    'Intrests': ['AI', 'ML', 'data science']\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3daec62d-3d7e-4892-8777-461d5b060896",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(my_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "fe2b34d2-fcc6-4c48-871a-4aca3889e62e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'name': 'George', 'State': 'NY', 'status': 'Caffinated', 'Age': 999, 'Intrests': ['AI', 'ML', 'data science']}\n"
     ]
    }
   ],
   "source": [
    "print(my_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5903352b-33d6-476f-849c-a34f19f7764a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'George'"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_dict['name']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a4a18833-8d55-422e-9815-40c65abde55b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['name', 'State', 'status', 'Age', 'Intrests'])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_dict.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "69a99f60-9a09-43a4-aa0e-e6ae8f4e47af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_values(['George', 'NY', 'Caffinated', 999, ['AI', 'ML', 'data science']])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_dict.values()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10e8ec84-cd3b-4cf2-83ae-6cd4a31498ae",
   "metadata": {},
   "source": [
    "## 2. Working with files\n",
    "\n",
    "### 3.1. Reading from a file\n",
    "\n",
    "**Note:** this example needs a file called `test_file.txt` in the same directory as the notebook to work."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "6de3f962-a924-401c-86f8-c46a9e3f80bd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "_io.TextIOWrapper"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = open('data/test_file.txt','r')\n",
    "type(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "0c65c332-7cc4-40d3-89ed-28e330be24fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the data!This is more new dataThis is more new dataThis is more new data\n"
     ]
    }
   ],
   "source": [
    "contents = file.read()\n",
    "print(contents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "4b6d020e-4425-4e9b-9e0b-e77ec517a786",
   "metadata": {},
   "outputs": [],
   "source": [
    "file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af89ae80-9c5e-4671-8428-81bbd406f844",
   "metadata": {},
   "source": [
    "### 3.2. Context manager"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "6a4e714d-e73c-4558-b82e-2ca273ca7f61",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the data!This is more new dataThis is more new dataThis is more new data\n"
     ]
    }
   ],
   "source": [
    "with open('data/test_file.txt', 'r') as file:\n",
    "    contents = file.read()\n",
    "    print(contents)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49edc05e-b021-4fa0-ae48-d87979582d90",
   "metadata": {},
   "source": [
    "### 3.3. Writing to a file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "4764576b-9445-493f-b5d1-7105ed21c8c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "file = open('test_output.txt', 'w')\n",
    "new_data = 'This is the new data'\n",
    "file.write(new_data)\n",
    "file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "d98c7b3c-c7ff-4a3e-b63a-e49777963579",
   "metadata": {},
   "outputs": [],
   "source": [
    "file = open('test_output.txt', 'w')\n",
    "more_data = 'This is more new data'\n",
    "file.write(more_data)\n",
    "file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b0ce221-4f86-4120-a10d-2cff5d3eaebf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the data!This is more new dataThis is more new dataThis is more new data\n"
     ]
    }
   ],
   "source": [
    "with open('test_file.txt', 'a') as file:\n",
    "    more_data = 'This is more new data'\n",
    "    file.write(more_data)\n",
    "\n",
    "print(contents)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b755b178-d44d-4793-8aa4-34b7c7aeb242",
   "metadata": {},
   "source": [
    "## 4. Error handling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e252306f-8ac2-4e75-9d40-c6065dd1deb1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now it exists!\n"
     ]
    }
   ],
   "source": [
    "file = open('data/bad_file.txt', 'r')\n",
    "contents = file.read()\n",
    "print(contents)\n",
    "file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ae67224-78a1-4f4d-ac63-253c5559d5bc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now it exists!\n",
      "This is the finally clause - it closes the file handle\n",
      "Do other things\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "\n",
    "    file = open('data/bad_file.txt', 'r')\n",
    "    contents = file.read()\n",
    "    print(contents)\n",
    "\n",
    "except:\n",
    "\n",
    "    print('File not found')\n",
    "\n",
    "finally:\n",
    "\n",
    "    print('This is the finally clause - it closes the file handle')\n",
    "    file.close()\n",
    "\n",
    "print('Do other things')\n"
   ]
  }
 ],
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