Santiago-j-s/Objects.ipynb

## Objects.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Objetos en python\n",
    "\n",
    "Ayer te dije que en python todo es un objeto ¿qué significa que todo sea un objeto?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bueno, por ejemplo, los objetos tienen id y tipo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id de 2: 9454656\n",
      "<class 'int'>\n",
      "\n",
      "id de \"hi\": 140507759267944\n",
      "<class 'str'>\n",
      "\n",
      "id de 2.1: 140507575629048\n",
      "<class 'float'>\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(f\"id de 2: {id(2)}\")\n",
    "print(type(2))\n",
    "print()\n",
    "\n",
    "print(f'id de \"hi\": {id(\"hi\")}')\n",
    "print(type(\"hi\"))\n",
    "print()\n",
    "\n",
    "print(f\"id de 2.1: {id(2.1)}\")\n",
    "print(type(2.1))\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A los objetos también los puedo asignar a variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9454656\n",
      "<class 'int'>\n"
     ]
    }
   ],
   "source": [
    "a = 2\n",
    "\n",
    "print(id(a))\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mira lo que ocurre con el primer id de antes ¿recuerdas que te dije que los primeros números enteros estaban precargados (-5 a 256, no comments about that)? Le asigne a la variable `a` el literal 2 y python no creo un objeto nuevo sino que uso el nro precargado."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a es 2: True\n",
      "\n",
      "9454656\n",
      "\n",
      "a es b: True\n",
      "\n",
      "c es 257: False\n",
      "id de c: 140507575339120\n",
      "id de 257: 140507575338928\n",
      "\n",
      "False\n"
     ]
    }
   ],
   "source": [
    "print(f\"a es 2: {a is 2}\")\n",
    "print()\n",
    "\n",
    "b = a\n",
    "print(id(b))\n",
    "print()\n",
    "\n",
    "print(f\"a es b: {a is b}\")\n",
    "print()\n",
    "\n",
    "c = 257\n",
    "print(f\"c es 257: {c is 257}\")\n",
    "# ¡Cuidado con el operador `is` que no realiza una comparación\n",
    "# sino que nos dice si dos objetos son el mismo objeto!\n",
    "\n",
    "print(f\"id de c: {id(c)}\")\n",
    "print(f\"id de 257: {id(257)}\")\n",
    "print()\n",
    "\n",
    "print(id(c) == id(257))\n",
    "## ¡Los ids no son iguales, no son el mismo objeto!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ¿Qué ocurre con las clases?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Persona:\n",
    "    def __init__(self, nombre: str):\n",
    "        self.nombre = nombre\n",
    "        \n",
    "    def saludar(self):\n",
    "        return f\"Hi {self.nombre}\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Bueno, cuando creo una nueva _instancia_ de una clase se crea un objeto cuyo tipo es la clase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.Persona object at 0x7fca781b1128>\n",
      "<__main__.Persona object at 0x7fca781b10f0>\n",
      "\n",
      "<class '__main__.Persona'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'0x7fca781b1128'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = Persona(\"Persona\")\n",
    "b = Persona(\"Otra persona\")\n",
    "\n",
    "print(a)\n",
    "print(b)\n",
    "print()\n",
    "\n",
    "print(type(a)) # El tipo es la clase, ignoremos de momento el __main__.\n",
    "hex(id(a)) # El id no es más que la dirección de memoria donde se encuentra el objeto,\n",
    "           # funciona muy bien como identificador único"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ahora viene lo divertido\n",
    "\n",
    "a y b son instancias de la clase persona, y por tanto son objetos.\n",
    "\n",
    "Pero antes dije que *todo* en python es un objeto, ¿es posible que la clase Persona sea en si misma un objeto?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'type'>\n",
      "0x28653b8\n",
      "\n",
      "<class 'type'>\n",
      "0x28653b8\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Hi nombre'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(type(Persona))\n",
    "print(hex(id(Persona)))\n",
    "print()\n",
    "\n",
    "# Parece que sí, que es una instancia de la clase `type`\n",
    "# ¿Puedo asignar `Persona` a una variable?\n",
    "\n",
    "p = Persona\n",
    "\n",
    "print(type(p))\n",
    "print(hex(id(p)))\n",
    "print()\n",
    "\n",
    "# ¿Podré crear una nueva instancia de `Persona` usando la variable `p` en lugar de `Persona`?\n",
    "nueva_persona = p(\"nombre\")\n",
    "nueva_persona.saludar()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Entonces _of course_ las funciones también son objetos, y esta es la parte linda de POO, los objetos no solo representan sustantivos\n",
    "\n",
    "(no funciona así en todos los lenguajes \"orientados a objetos\", pero así funcionaba Smalltalk y a Alan Kay le encantaba lisp que es un lenguaje super flexible con el uso de las funciones)\n",
    "\n",
    "Juguemos un poco con esta idea de las funciones como objetos y la flexibilidad que ello nos brinda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from typing import Callable\n",
    "\n",
    "def f3(\n",
    "    f: Callable[[np.ndarray], np.ndarray],\n",
    "    g: Callable[[np.ndarray], np.ndarray],\n",
    "    x: np.ndarray\n",
    "):\n",
    "    return np.piecewise(x, [x < 0, x >= 0], [f, g])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`f3` recibe dos funciones, `f` y `g`, y un numpy array.\n",
    "\n",
    "Retorna el array resultante de aplicar `f` a los valores a los valores menores que 0 y `g` a los valores mayores o iguales a cero. Una idea tan simple como \"las funciones son objetos\" nos permite hacer en forma muy sencilla cosas que de otra forma llevarían bastante trabajo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fca50f43898>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def f1(x: np.ndarray):\n",
    "    return x ** 2\n",
    "\n",
    "def f2(x: np.ndarray):\n",
    "    return x * 2\n",
    "\n",
    "x = np.linspace(-50, 50, 1000)\n",
    "y = f3(f1, f2, x)\n",
    "\n",
    "plt.plot(x, y)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# Objetos en python\n",
	"\n",
	"Ayer te dije que en python todo es un objeto ¿qué significa que todo sea un objeto?"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"## Bueno, por ejemplo, los objetos tienen id y tipo"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 1,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"id de 2: 9454656\n",
	"<class 'int'>\n",
	"\n",
	"id de \"hi\": 140507759267944\n",
	"<class 'str'>\n",
	"\n",
	"id de 2.1: 140507575629048\n",
	"<class 'float'>\n",
	"\n"
	]
	}
	],
	"source": [
	"print(f\"id de 2: {id(2)}\")\n",
	"print(type(2))\n",
	"print()\n",
	"\n",
	"print(f'id de \"hi\": {id(\"hi\")}')\n",
	"print(type(\"hi\"))\n",
	"print()\n",
	"\n",
	"print(f\"id de 2.1: {id(2.1)}\")\n",
	"print(type(2.1))\n",
	"print()"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"## A los objetos también los puedo asignar a variables"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 2,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"9454656\n",
	"<class 'int'>\n"
	]
	}
	],
	"source": [
	"a = 2\n",
	"\n",
	"print(id(a))\n",
	"print(type(a))"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"Mira lo que ocurre con el primer id de antes ¿recuerdas que te dije que los primeros números enteros estaban precargados (-5 a 256, no comments about that)? Le asigne a la variable `a` el literal 2 y python no creo un objeto nuevo sino que uso el nro precargado."
	]
	},
	{
	"cell_type": "code",
	"execution_count": 3,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"a es 2: True\n",
	"\n",
	"9454656\n",
	"\n",
	"a es b: True\n",
	"\n",
	"c es 257: False\n",
	"id de c: 140507575339120\n",
	"id de 257: 140507575338928\n",
	"\n",
	"False\n"
	]
	}
	],
	"source": [
	"print(f\"a es 2: {a is 2}\")\n",
	"print()\n",
	"\n",
	"b = a\n",
	"print(id(b))\n",
	"print()\n",
	"\n",
	"print(f\"a es b: {a is b}\")\n",
	"print()\n",
	"\n",
	"c = 257\n",
	"print(f\"c es 257: {c is 257}\")\n",
	"# ¡Cuidado con el operador `is` que no realiza una comparación\n",
	"# sino que nos dice si dos objetos son el mismo objeto!\n",
	"\n",
	"print(f\"id de c: {id(c)}\")\n",
	"print(f\"id de 257: {id(257)}\")\n",
	"print()\n",
	"\n",
	"print(id(c) == id(257))\n",
	"## ¡Los ids no son iguales, no son el mismo objeto!"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"## ¿Qué ocurre con las clases?"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 4,
	"metadata": {},
	"outputs": [],
	"source": [
	"class Persona:\n",
	" def __init__(self, nombre: str):\n",
	" self.nombre = nombre\n",
	" \n",
	" def saludar(self):\n",
	" return f\"Hi {self.nombre}\""
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"## Bueno, cuando creo una nueva _instancia_ de una clase se crea un objeto cuyo tipo es la clase"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 5,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"<__main__.Persona object at 0x7fca781b1128>\n",
	"<__main__.Persona object at 0x7fca781b10f0>\n",
	"\n",
	"<class '__main__.Persona'>\n"
	]
	},
	{
	"data": {
	"text/plain": [
	"'0x7fca781b1128'"
	]
	},
	"execution_count": 5,
	"metadata": {},
	"output_type": "execute_result"
	}
	],
	"source": [
	"a = Persona(\"Persona\")\n",
	"b = Persona(\"Otra persona\")\n",
	"\n",
	"print(a)\n",
	"print(b)\n",
	"print()\n",
	"\n",
	"print(type(a)) # El tipo es la clase, ignoremos de momento el __main__.\n",
	"hex(id(a)) # El id no es más que la dirección de memoria donde se encuentra el objeto,\n",
	" # funciona muy bien como identificador único"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"## Ahora viene lo divertido\n",
	"\n",
	"a y b son instancias de la clase persona, y por tanto son objetos.\n",
	"\n",
	"Pero antes dije que todo en python es un objeto, ¿es posible que la clase Persona sea en si misma un objeto?"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 6,
	"metadata": {},
	"outputs": [
	{
	"name": "stdout",
	"output_type": "stream",
	"text": [
	"<class 'type'>\n",
	"0x28653b8\n",
	"\n",
	"<class 'type'>\n",
	"0x28653b8\n",
	"\n"
	]
	},
	{
	"data": {
	"text/plain": [
	"'Hi nombre'"
	]
	},
	"execution_count": 6,
	"metadata": {},
	"output_type": "execute_result"
	}
	],
	"source": [
	"print(type(Persona))\n",
	"print(hex(id(Persona)))\n",
	"print()\n",
	"\n",
	"# Parece que sí, que es una instancia de la clase `type`\n",
	"# ¿Puedo asignar `Persona` a una variable?\n",
	"\n",
	"p = Persona\n",
	"\n",
	"print(type(p))\n",
	"print(hex(id(p)))\n",
	"print()\n",
	"\n",
	"# ¿Podré crear una nueva instancia de `Persona` usando la variable `p` en lugar de `Persona`?\n",
	"nueva_persona = p(\"nombre\")\n",
	"nueva_persona.saludar()"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"## Entonces _of course_ las funciones también son objetos, y esta es la parte linda de POO, los objetos no solo representan sustantivos\n",
	"\n",
	"(no funciona así en todos los lenguajes \"orientados a objetos\", pero así funcionaba Smalltalk y a Alan Kay le encantaba lisp que es un lenguaje super flexible con el uso de las funciones)\n",
	"\n",
	"Juguemos un poco con esta idea de las funciones como objetos y la flexibilidad que ello nos brinda"
	]
	},
	{
	"cell_type": "code",
	"execution_count": 7,
	"metadata": {},
	"outputs": [],
	"source": [
	"import numpy as np\n",
	"import matplotlib.pyplot as plt\n",
	"\n",
	"from typing import Callable\n",
	"\n",
	"def f3(\n",
	" f: Callable[[np.ndarray], np.ndarray],\n",
	" g: Callable[[np.ndarray], np.ndarray],\n",
	" x: np.ndarray\n",
	"):\n",
	" return np.piecewise(x, [x < 0, x >= 0], [f, g])"
	]
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"`f3` recibe dos funciones, `f` y `g`, y un numpy array.\n",
	"\n",
	"Retorna el array resultante de aplicar `f` a los valores a los valores menores que 0 y `g` a los valores mayores o iguales a cero. Una idea tan simple como \"las funciones son objetos\" nos permite hacer en forma muy sencilla cosas que de otra forma llevarían bastante trabajo."
	]
	},
	{
	"cell_type": "code",
	"execution_count": 8,
	"metadata": {},
	"outputs": [
	{
	"data": {
	"text/plain": [
	"[<matplotlib.lines.Line2D at 0x7fca50f43898>]"
	]
	},
	"execution_count": 8,
	"metadata": {},
	"output_type": "execute_result"
	},
	{
	"data": {
	"image/png": 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\n",
	"text/plain": [
	"<Figure size 432x288 with 1 Axes>"
	]
	},
	"metadata": {
	"needs_background": "light"
	},
	"output_type": "display_data"
	}
	],
	"source": [
	"def f1(x: np.ndarray):\n",
	" return x ** 2\n",
	"\n",
	"def f2(x: np.ndarray):\n",
	" return x * 2\n",
	"\n",
	"x = np.linspace(-50, 50, 1000)\n",
	"y = f3(f1, f2, x)\n",
	"\n",
	"plt.plot(x, y)"
	]
	}
	],
	"metadata": {
	"kernelspec": {
	"display_name": "Python 3",
	"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": "3.7.0"
	}
	},
	"nbformat": 4,
	"nbformat_minor": 2
	}