ch12.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# User-Defined Functions (UDFs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Function Decorators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This is the definition of the function decorator\n",
    "def verbose(func):\n",
    "    def wrapper():\n",
    "        print(\"Before calling the function.\")\n",
    "        func()\n",
    "        print(\"After calling the function.\")\n",
    "    return wrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Using a function decorator\n",
    "@verbose\n",
    "def print_hello():\n",
    "    print(\"hello!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Effect of calling the decorated function\n",
    "print_hello()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fetching Data from Google Trends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pytrends.request import TrendReq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First, let's instantiate a TrendRequest object\n",
    "trend = TrendReq()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now we can print the suggestions as they would appear\n",
    "# online in the dropdown of Google Trends after typing in \"Python\"\n",
    "trend.suggestions(\"Python\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Caching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cache = {}\n",
    "\n",
    "def slow_sum(a, b):\n",
    "    key = (a, b)\n",
    "    if key in cache:\n",
    "        return cache[key]\n",
    "    else:\n",
    "        time.sleep(2)  # sleep for 2 seconds\n",
    "        result = a + b\n",
    "        cache[key] = result\n",
    "        return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "slow_sum(1, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "slow_sum(1, 2)"
   ]
  }
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