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   "source": [
    "# <font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 7</font>\n",
    "\n",
    "## Download: http://github.com/dsacademybr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missão 2: Implementar o Algoritmo de Ordenação \"Selection sort\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nível de Dificuldade: Alto"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Premissas\n",
    "\n",
    "* As duplicatas são permitidas?\n",
    "     * Sim\n",
    "* Podemos assumir que a entrada é válida?\n",
    "     * Não\n",
    "* Podemos supor que isso se encaixa na memória?\n",
    "     * Sim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Teste Cases\n",
    "\n",
    "* None -> Exception\n",
    "* [] -> []\n",
    "* One element -> [element]\n",
    "* Two or more elements"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algoritmo\n",
    "\n",
    "Animação do Wikipedia:\n",
    "![alt text](http://upload.wikimedia.org/wikipedia/commons/9/94/Selection-Sort-Animation.gif)\n",
    "\n",
    "Podemos fazer isso de forma recursiva ou iterativa. Iterativamente será mais eficiente, pois não requer sobrecarga de espaço extra com as chamadas recursivas.\n",
    "\n",
    "* Para cada elemento\n",
    "     * Verifique cada elemento à direita para encontrar o min\n",
    "     * Se min < elemento atual, swap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solução"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class SelectionSort(object):\n",
    "\n",
    "    def sort(self, data):\n",
    "        # Implemente aqui sua solução"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Teste da Solução"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing missao4.py\n"
     ]
    }
   ],
   "source": [
    "%%writefile missao4.py\n",
    "from nose.tools import assert_equal, assert_raises\n",
    "\n",
    "\n",
    "class TestSelectionSort(object):\n",
    "\n",
    "    def test_selection_sort(self, func):\n",
    "        print('None input')\n",
    "        assert_raises(TypeError, func, None)\n",
    "\n",
    "        print('Input vazio')\n",
    "        assert_equal(func([]), [])\n",
    "\n",
    "        print('Um elemento')\n",
    "        assert_equal(func([5]), [5])\n",
    "\n",
    "        print('Dois ou mais elementos')\n",
    "        data = [5, 1, 7, 2, 6, -3, 5, 7, -10]\n",
    "        assert_equal(func(data), sorted(data))\n",
    "\n",
    "        print('Sua solução foi executada com sucesso! Parabéns!')\n",
    "\n",
    "\n",
    "def main():\n",
    "    test = TestSelectionSort()\n",
    "    try:\n",
    "        selection_sort = SelectionSort()\n",
    "        test.test_selection_sort(selection_sort.sort)\n",
    "    except NameError:\n",
    "        pass\n",
    "\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None input\n",
      "Input vazio\n",
      "Um elemento\n",
      "Dois ou mais elementos\n",
      "Sua solução foi executada com sucesso! Parabéns!\n"
     ]
    }
   ],
   "source": [
    "%run -i missao4.py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obrigado - Data Science Academy - <a href=\"http://facebook.com/dsacademybr\">facebook.com/dsacademybr</a>"
   ]
  }
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