Python Basics - Session 6.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5bb6c3e5",
   "metadata": {},
   "source": [
    "<p align=\"center\"><img src = \"https://upload.wikimedia.org/wikipedia/commons/thumb/f/f8/Python_logo_and_wordmark.svg/2560px-Python_logo_and_wordmark.svg.png\" width=\"200\" height=\"auto\" style=\"display: block;margin-left: auto;margin-right: auto;margin-bottom:-30px\" /></p>\n",
    "<h1 align=\"center\" style=\"font-family:Calibri;color:#407daf;margin-left: 50px;text-align: center;\">Introduction to python</h1>\n",
    "<h2 align=\"center\" style=\"font-family:Calibri;color:#ffe262;margin-left: 50px;margin-top: 0px;text-align: center;\">Koorosh Komeilizadeh</h2>\n",
    "<p align=\"center\"><img src = \"https://www.irangi.org/uploads/images/4_1560089256_1291127534.png\" style=\"  -webkit-filter: drop-shadow(1px 1px 0 white)\n",
    "                  drop-shadow(-1px -1px 0 white);\n",
    "  filter: drop-shadow(1px 1px 0 white) \n",
    "          drop-shadow(-1px -1px 0 white);display: block;margin-left: auto;margin-right: auto;margin-top:15px\" width=\"250\" height=\"auto\"/></p>\n",
    "<h1 align=\"center\" style=\"margin-left:50px;\">Session 6</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ada422f6",
   "metadata": {},
   "source": [
    "# Session 4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8211b7a8",
   "metadata": {},
   "source": [
    "## Task 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2e17550",
   "metadata": {},
   "source": [
    "### مرتب کردن اسم های ورودی"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31419c86",
   "metadata": {},
   "source": [
    "نمونه ورودی"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "245b4374",
   "metadata": {},
   "outputs": [],
   "source": [
    "ko oroSh   \n",
    "SAm \n",
    "Maha  Tma "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9864000",
   "metadata": {},
   "source": [
    "نمونه خروجی"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5aec5ff9",
   "metadata": {},
   "outputs": [],
   "source": [
    "Koorosh\n",
    "Sam\n",
    "Mahatma"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d71fc67",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6f68ca0b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the names and submit 0 when finished.\n",
      "  KooRo SH\n",
      "Mah At mA\n",
      "Sa        M\n",
      "0\n",
      "['  KooRo SH', 'Mah At mA', 'Sa        M']\n",
      "['Koorosh', 'Mahatma', 'Sam']\n"
     ]
    }
   ],
   "source": [
    "print(\"Enter the names and submit 0 when finished.\")\n",
    "names = []\n",
    "\n",
    "while 1:\n",
    "    names.append(input())\n",
    "    if \"0\" in names:\n",
    "        names.pop()\n",
    "        print(names)\n",
    "        break\n",
    "\n",
    "for i in range(len(names)):\n",
    "    names[i] = names[i].replace(\" \", \"\")\n",
    "    names[i] = names[i].capitalize()\n",
    "\n",
    "print(names)\n",
    "\n",
    "#Alternate for Capitalize()\n",
    "#    names[i] = names[i].lower()\n",
    "#    names[i][0] = names[i][0].upper()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fd64a93",
   "metadata": {},
   "source": [
    "<hr style=\"height: 2px;\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "654b0aa4",
   "metadata": {},
   "source": [
    "## Task 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfad70ff",
   "metadata": {},
   "source": [
    "### سیستم رزرو غذا\n",
    "#### سامانه ای که بتوان با نام کاربری و کلمه عبور را وارد کردن نوع غذای موجود را رزرو و در انتها لیستی از دانشجو ها و غذای درخواستی را نشان دهد"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4a7bc00",
   "metadata": {},
   "source": [
    "نمونه ورودی"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e77882af",
   "metadata": {},
   "outputs": [],
   "source": [
    "user: 40126000\n",
    "pass: 2938\n",
    "Which one do you want to reserve? \n",
    "1.Pizza 2.Fish 3.Burger"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58384bd9",
   "metadata": {},
   "source": [
    "نمونه خروجی"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ade8d133",
   "metadata": {},
   "outputs": [],
   "source": [
    "40126000 have burger\n",
    "40026000 have pizza and ..."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "016e2734",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9870bbcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter username: 40012049\n",
      "Enter password: 3455\n",
      "{0: 'Not Reserved', 1: 'Pizza', 2: 'Fish', 3: 'Burger'}\n",
      "Enter your meal number: 2\n",
      "User 40126032 have Not Reserved\n",
      "User 40012049 have Fish\n",
      "User 9913012 have Not Reserved\n"
     ]
    }
   ],
   "source": [
    "db = {40126032 : {\"pass\" : 3213, \"meal\" : 0},\n",
    "      40012049 : {\"pass\" : 3455, \"meal\" : 0},\n",
    "      9913012  : {\"pass\" : 7532, \"meal\" : 0}}\n",
    "\n",
    "meals = {0: \"Not Reserved\",\n",
    "         1: \"Pizza\",\n",
    "         2: \"Fish\",\n",
    "         3: \"Burger\"}\n",
    "\n",
    "def show():\n",
    "    for i in (db):\n",
    "        print(f\"User {i} have {meals[int(db[i]['meal'])]}\")\n",
    "\n",
    "user = int(input(\"Enter username: \"))\n",
    "if user in db:\n",
    "    pwd = int(input(\"Enter password: \"))\n",
    "    if pwd == db[user][\"pass\"]:\n",
    "        print(meals)\n",
    "        db[user][\"meal\"] = int(input(\"Enter your meal number: \"))\n",
    "        show()\n",
    "    else:\n",
    "        print(\"Password is wrong\")\n",
    "else:\n",
    "    print(\"User not found\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f9956fd",
   "metadata": {},
   "source": [
    "<hr style=\"height: 1px;\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd1cb360",
   "metadata": {},
   "source": [
    "# Session 5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e76c7b9",
   "metadata": {},
   "source": [
    "## Task 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5bebc5b1",
   "metadata": {},
   "source": [
    "برنامه ای بنویسید که نام کاربری که شماره دانشجویی شما و رمز عبور یعنی 4 رقم آخر را در محیط گرافیکی دریافت کند و پس از کلیک روی دکمه بررسی، اگر چهار رقم آخر رمز شما بود عبارت رمز درست است را چاپ کند\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b2fcf58",
   "metadata": {},
   "source": [
    "### Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f8f9d666",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tkinter as tk\n",
    "\n",
    "def check_password():\n",
    "    username = username_entry.get()\n",
    "    password = password_entry.get()\n",
    "    \n",
    "    if password == username[-4:]:\n",
    "        result_label.config(text=\"User found\")\n",
    "    else:\n",
    "        result_label.config(text=\"User not found\")\n",
    "\n",
    "window = tk.Tk()\n",
    "window.title(\"Login\")\n",
    "\n",
    "username_label = tk.Label(window, text=\"Username:\")\n",
    "username_label.pack()\n",
    "username_entry = tk.Entry(window)\n",
    "username_entry.pack()\n",
    "\n",
    "password_label = tk.Label(window, text=\"Password:\")\n",
    "password_label.pack()\n",
    "password_entry = tk.Entry(window, show=\"*\")\n",
    "password_entry.pack()\n",
    "\n",
    "check_button = tk.Button(window, text=\"Check Password\", command=check_password)\n",
    "check_button.pack()\n",
    "\n",
    "result_label = tk.Label(window, text=\"\")\n",
    "result_label.pack()\n",
    "\n",
    "window.mainloop()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c02b60a",
   "metadata": {},
   "source": [
    "<hr style=\"height: 1px;\">"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f382c98d",
   "metadata": {},
   "source": [
    "## Task 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21a504db",
   "metadata": {},
   "source": [
    "برنامه ای بنویسید که ارقام شماره دانشجویی شما مقادیر ایکس و معکوس شماره دانشجویی شما مقادیر ایگرگ نمودار چاپ شده در محیط گرافیکی باشد که خروجی نمودار و فیلد وارد کردن اطلاعات در صفحه باز شده توسط تیکینتر طراحی شده باشد."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ada31ad1",
   "metadata": {},
   "source": [
    "## Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b76462a6",
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import tkinter as tk\n",
    "from tkinter import messagebox\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "root = tk.Tk()\n",
    "root.title(\"Number Plot\")\n",
    "\n",
    "tk.Label(root, text=\"Enter a number: \").pack()\n",
    "number_entry = tk.Entry(root)\n",
    "number_entry.pack()\n",
    "\n",
    "def plot_number():\n",
    "    number_str = number_entry.get()\n",
    "\n",
    "    digits = [int(d) for d in number_str]\n",
    "\n",
    "    reverse_digits = digits[::-1]\n",
    "\n",
    "    fig, ax = plt.subplots()\n",
    "    ax.plot(digits, reverse_digits)\n",
    "\n",
    "    plt.show()\n",
    "\n",
    "plot_button = tk.Button(root, text=\"Plot Number\", command=plot_number)\n",
    "plot_button.pack()\n",
    "\n",
    "root.mainloop()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}