{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exceptions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An exception is an event, which occurs during the execution of a program, that disrupts the normal flow of the program's instructions.\n",
    "\n",
    "You've already seen some exceptions in the **Debugging** lesson."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many programs want to know about exceptions when they occur. For example, if the input to a program is a file path. If the user inputs an invalid or non-existent path, the program generates an exception. It may be desired to provide a response to the user in this case."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It may also be that programs will *generate* exceptions. This is a way of indicating that there is an error in the inputs provided. In general, this is the preferred style for dealing with invalid inputs or states inside a python function rather than having an error return."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Catching Exceptions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Python provides a way to detect when an exception occurs. This is done by the use of a block of code surrounded by a \"try\" and \"except\" statement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def divide(numerator, denominator):\n",
    "    result = numerator/denominator\n",
    "    print(\"result = %f\" % result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide(1.0, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def divide1(numerator, denominator):\n",
    "    try:\n",
    "        result = numerator/denominator\n",
    "        print(\"result = %f\" % result)\n",
    "    except:\n",
    "        print(\"You can't divide by 0!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide1(1.0, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide1(1.0, 'a')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While this does catch the exception, the error message doesn't really match the condition because conceptually `'a' != 0`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide1(\"x\", 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Moreover, this is also not correct, because `2 != 0` but the message says it does because the real error is in the first argument!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def divide2(numerator, denominator):\n",
    "    try:\n",
    "        result = numerator / denominator\n",
    "        print(\"result = %f\" % result)\n",
    "    except (ZeroDivisionError, TypeError) as err:\n",
    "        print(\"Got an exception: %s\" % err)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide2(1, \"X\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide2(\"x\", 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "divide2(1, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### What do you do when you get an exception?\n",
    "\n",
    "First, you can feel relieved that you caught a problematic element of your software! Yes, relieved. Silent fails are much worse. (Again, another plug for testing.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generating Exceptions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Why *generate* exceptions? (Don't I have enough unintentional errors?)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "def validateDF(df):\n",
    "    if not \"hours\" in df.columns:\n",
    "        raise ValueError(\"DataFrame should have a column named 'hours'.\")\n",
    "    else:\n",
    "        pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({'hours': range(10) })\n",
    "validateDF(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({'years': range(10) })\n",
    "validateDF(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Class exercise\n",
    "Choose one of the functions from the last exercise. Create two new functions:\n",
    "- The first function throws an exception if there is a negative argument.\n",
    "- The second function catches an exception if the modulo operator (`%`) throws an exception and attempts to correct it by coercing the argument to a positive integer."
   ]
  }
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