{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial Go\n",
    "\n",
    "[Grupo 2022-1](http://nbviewer.jupyter.org/url/ferestrepoca.github.io/paradigmas-de-programacion/progconcurrente/tutoriales/GO/GO(ProgConcurrente).ipynb)\n",
    "\n",
    "# API REST con Go 2024-1\n",
    "\n",
    "**API de Go - CRUD con GORM, Gin y PostgreSQL**\n",
    "\n",
    "Cordial saludo, para el grupo encargado de la sección del tutorial de Go, del curso de lenguajes de programación de la Universidad de los Nacional de Colombia, del año 2024 primer semestre. Nos complace presentarles el siguiente aporte, muchas veces en la vida de un programador se necesita realizar operaciones CRUD (Create, Read, Update, Delete) en una base de datos, en este caso se presenta un ejemplo de como realizar estas operaciones en una base de datos PostgreSQL, utilizando el ORM GORM y el framework Gin.\n",
    "\n",
    "Muchos de los ejemplos que se encuentran en la web, no están actualizados o no son claros, por lo que se presenta este ejemplo, que es claro y conciso, para que puedan entender como realizar estas operaciones en Go, de manera sencilla y rápida.\n",
    "\n",
    "Las instrucciones para la instalación de las dependencias y la ejecución del código se encuentran en el archivo README.md, ubicado en la carpeta del proyecto.\n",
    "\n",
    "Pueden descargar el código fuente descargando el archivo zip, ubicado en el siguiente enlace: [Descargar código fuente](https://github.com/sacostaa/api-rest-goland.git)\n",
    "\n",
    "\n",
    "\n",
    "## Instalacion \n",
    "\n",
    "En este apartado se mostrara paso a paso la instalacion de el lenguaje de programacion GO y que este pueda ser ejecutado por un jupyter notebook a traves del editor de texto visual studio code \n",
    "\n",
    "Este tutorial se basa en parte al tutorial que brinda la siguiente pagina: https://girishv.hashnode.dev/setting-up-jupyter-notebook-kernels-for-golang-and-nodejs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prerequisitos \n",
    "\n",
    "Tener instalado previamente lo siguiente:\n",
    "\n",
    "1. Python en su ultima version https://www.python.org/downloads/\n",
    "2. Golang en su ultima version https://go.dev/dl/\n",
    "3. Visual Studio Code https://code.visualstudio.com/download\n",
    "4. Jupyter notebook en su ultima version https://jupyter.org/install"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Instalacion directa\n",
    "\n",
    "Como se menciono anteriormente esta instalacion se basa en el paso a paso brindado por esta pagina https://girishv.hashnode.dev/setting-up-jupyter-notebook-kernels-for-golang-and-nodejs\n",
    "\n",
    "Pero en este proceso existe una problematica y es que si bien el metodo es facil y directo ya que son solo lineas de comando, este metodo esta mas enfocado para usuarios de Linux, ya que estos comandos en algun punto suelen tener problemas cuando se ejecutan desde el sistema operativo Windows \n",
    "\n",
    "En primera instancia pueden intentar el paso a paso que brinda dicha pagina pero no se desesperen si este no funciona ya que a continuacion se les presentara un metodo mucho mas directo para realizar la instalacion del kernel de Go para Jupyter notebooks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Instalacion de Gophernotes\n",
    "\n",
    "Gophernotes es un kernel de Go para Jupyter Notebooks, para esto se va a ejecutar el siguiente comando desde consola \n",
    "\n",
    "```sh\n",
    " go get github.com/gopherdata/gophernotes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Verificacion de rutas de instalacion\n",
    "\n",
    "Para los siguientes pasos necesitas saber las rutas donde se instalo el gophernotes y donde esta instalado jupyther notebook por lo que vas a ejecutar los siguientes comandos o codigos  para obtenerlas "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### *Gophernotes*\n",
    "\n",
    "```sh\n",
    "go env GOPATH\n",
    "```\n",
    "el resultado de este va a ser una ruta que vas a tener que expandir un poco, la salida normalmente seria esta: \n",
    "\n",
    "C:\\Users\\YourUsername\\go\n",
    "\n",
    "Dirigete a el explorador de archivos e ingresa la direccion resultante, luego vas a buscar la carpeta bing y revisar si en esta se encuentra alojado el archivo gophernotes.exe, si esto es asi significa que gophernotes se instalo correctamente y posterioremnete guardaras la direccion donde se encuentra el gophernotes.exe pero incluyendolo en el path. Al hacer esto deberia resultar algo muy parecido a esto:\n",
    "\n",
    "C:\\\\Users\\\\YourUsername\\\\go\\\\bin\\\\gophernotes.exe\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### *Jupyter notebook*\n",
    "\n",
    "Primero debes ejecurtar la siguiente linea de comandos para instalar jupyter core\n",
    "\n",
    "```sh\n",
    "pip install jupyter_core\n",
    "```\n",
    "\n",
    "Posterioremente debes ejecutar el siguiente codigo de python de manera local a travez de un notebook o un un archivo.py\n",
    "\n",
    " ```python\n",
    "from jupyter_core.paths import jupyter_data_dir\n",
    "print(jupyter_data_dir())\n",
    "```\n",
    "\n",
    "Este te devolvera la direccion donde se encuentra alojado el directorio de jupyter notebook, esta direccion deberia ser muy parecida a la siguiente \n",
    "\n",
    "C:\\Users\\YourUsername\\AppData\\Roaming\\jupyter\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Instalacion del kernel Go \n",
    "\n",
    "Para este paso te vas a dirigir a traves del explorador de archivos a la direccion que te dio el codigo de python\n",
    "\n",
    "En esta vas a revisar si existe una carpeta llamada \"kernels\", de no ser asi creala, dentro de esta crea una carpeta que se llame \"gophernotes\", y dentro de esta vas a crear un archivo .json que tenga el siguiente contenido \n",
    "\n",
    " ```json\n",
    "{\n",
    "  \"argv\": [\n",
    "    \"(tu direccion de gophernotes con doble slash)\",\n",
    "    \"{connection_file}\"\n",
    "  ],\n",
    "  \"display_name\": \"Go\",\n",
    "  \"language\": \"go\",\n",
    "  \"name\": \"go\"\n",
    "}\n",
    "```\n",
    "La direccion que debes ingresar es la que conseguimos de gophernotes, donde se le adiciona un slash adicional, y lo cual resultaria en algo como esto\n",
    "\n",
    " ```json\n",
    "{\n",
    "  \"argv\": [\n",
    "    \"C:\\\\Users\\\\YourUsername\\\\go\\\\bin\\\\gophernotes\",\n",
    "    \"{connection_file}\"\n",
    "  ],\n",
    "  \"display_name\": \"Go\",\n",
    "  \"language\": \"go\",\n",
    "  \"name\": \"go\"\n",
    "}\n",
    "```\n",
    "Luego de realizar esto, guardas el contenido del archivo y sales del mismo"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Instalacion de jupyter notebooks con el kernel Go en Visual Studio Code \n",
    "\n",
    "Abre visual Studio code y dentro del apartado de extensiones vas a buscar la extencion jupyter e instalarla como se ve en la imagen \n",
    "\n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Posteriormente vas a buscar y a instalar Go para visual studio code como se ve en la imagen \n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "preciona Ctrl+Shift+P para ingresar a al command Palette e ingresa la palabra create jupyter, posteriormente seleccionas la opcion crear un nuevo jupyter notebook \n",
    "\n",
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image-2.png": {
     "image/png": 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    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Al ingresar va a aparecer algo parecido a lo que se ve en la imagen, puede que sin un lenguaje predeterminado como es el caso de python\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "Aqui tendras que hacer dos cosas, la primera es revisar si se instalo bien el kernel de Go oprimiendo select kernel, luego select other kernels, despues jupyter kernels y finalmente go \n",
    "\n",
    "Lo siguiente es hacer que el apartado de codigo detecte el lenguaje Go, para ello oprime el texto que esta en la esquina inferior derecha de el bloque de codigo, en la imagen anterior la palabra que se encuentra ahi es python, luego busca si en las opciones aparece el lenguaje Go y seleccionalo, de no ser asi selecciona la primera opcion que te ayudara a detectar automaticamente el lenguaje y dentro del bloque de codigo escribe un fragmento de codigo como el siguiente:\n",
    "\n",
    " ```Go\n",
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "func main() {\n",
    "    fmt.Println(\"Hello, World\")\n",
    "}\n",
    "\n",
    "main()\n",
    "```\n",
    "\n",
    "Este automaticamente detectara el lenguaje y podras ejecutar el codigo.\n",
    "\n",
    "Si todo salio como se esperaba y se ejecuto bien el codigo se deberia ver parecido a la siguiente imagen\n",
    "\n",
    "![image-2.png](attachment:image-2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tour por el lenguaje \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estructura Básica de un Programa GO\n",
    "\n",
    "Este es el programa más simple en GO. Todos los programas en GO deben pertenecer a un paquete, en este caso el paquete `main`, que es el punto de entrada de todos los programas ejecutables en GO. La función `main` es donde comienza la ejecución del programa. Aquí, utilizamos `fmt.Println` para imprimir \"Hello, World\" en la consola.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, World\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "func main() {\n",
    "    fmt.Println(\"Hello, World\")\n",
    "}\n",
    "\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Tipos de Datos en GO\n",
    "\n",
    "GO soporta varios tipos de datos básicos:\n",
    "- **Enteros**: int, int8, int16, int32, int64\n",
    "- **Flotantes**: float32, float64\n",
    "- **Booleanos**: bool\n",
    "- **Cadenas de Texto**: string\n",
    "\n",
    "En este ejemplo, declaramos variables de cada tipo de datos y las imprimimos usando `fmt.Println`.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a: 10 b: 20\n",
      "x: 3.14 y: 1.618\n",
      "isGoFun: true\n",
      "message: Hello, GO\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "func main() {\n",
    "    var a int = 10\n",
    "    var b int = 20\n",
    "    fmt.Println(\"a:\", a, \"b:\", b)\n",
    "\n",
    "\n",
    "    var x float64 = 3.14\n",
    "    var y float64 = 1.618\n",
    "    fmt.Println(\"x:\", x, \"y:\", y)\n",
    "\n",
    "    var isGoFun bool = true\n",
    "    fmt.Println(\"isGoFun:\", isGoFun)\n",
    "\n",
    "    var message string = \"Hello, GO\"\n",
    "    fmt.Println(\"message:\", message)\n",
    "}\n",
    "\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Control de Flujo en GO\n",
    "\n",
    "GO ofrece varias estructuras de control de flujo:\n",
    "- **Condicionales**: `if`, `else if`, `else` para decisiones.\n",
    "- **Bucles**: `for` para iteraciones.\n",
    "- **Switch**: Para seleccionar entre múltiples opciones.\n",
    "\n",
    "Este ejemplo muestra cómo usar cada una de estas estructuras.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 es par\n",
      "i: 1\n",
      "i: 2\n",
      "i: 3\n",
      "i: 4\n",
      "i: 5\n",
      "Hoy es lunes\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "func main() {\n",
    "    number := 10\n",
    "    if number%2 == 0 {\n",
    "        fmt.Println(number, \"es par\")\n",
    "    } else {\n",
    "        fmt.Println(number, \"es impar\")\n",
    "    }\n",
    "\n",
    "    for i := 1; i <= 5; i++ {\n",
    "        fmt.Println(\"i:\", i)\n",
    "    }\n",
    "\n",
    "    day := \"lunes\"\n",
    "    switch day {\n",
    "    case \"lunes\":\n",
    "        fmt.Println(\"Hoy es lunes\")\n",
    "    case \"martes\":\n",
    "        fmt.Println(\"Hoy es martes\")\n",
    "    default:\n",
    "        fmt.Println(\"Hoy no es lunes ni martes\")\n",
    "    }\n",
    "}\n",
    "\n",
    "main()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Funciones y Métodos en GO\n",
    "\n",
    "GO permite definir funciones y métodos. Las funciones se declaran con la palabra clave `func` seguida del nombre de la función y los parámetros. Los métodos son funciones asociadas a tipos definidos por el usuario, como structs.\n",
    "\n",
    "En este ejemplo, definimos una función `add` que suma dos números y un método `Area` que calcula el área de un rectángulo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Resultado de add: 12\n",
      "Área del rectángulo: 50\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "func add(a int, b int) int {\n",
    "    return a + b\n",
    "}\n",
    "\n",
    "type Rect struct {\n",
    "    width, height int\n",
    "}\n",
    "\n",
    "func (r *Rect) Area() int {\n",
    "    return r.width * r.height\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    result := add(5, 7)\n",
    "    fmt.Println(\"Resultado de add:\", result)\n",
    "\n",
    "    rect := Rect{width: 10, height: 5}\n",
    "    fmt.Println(\"Área del rectángulo:\", rect.Area())\n",
    "}\n",
    "\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Manejo de Errores en GO\n",
    "\n",
    "GO utiliza un sistema explícito de manejo de errores. Las funciones pueden devolver múltiples valores, y uno de ellos puede ser un error. Este enfoque obliga a los desarrolladores a manejar los errores explícitamente.\n",
    "\n",
    "En este ejemplo, la función `checkNumber` devuelve un error si el número proporcionado es negativo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Error: el número no puede ser negativo\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import (\n",
    "    \"errors\"\n",
    "    \"fmt\"\n",
    ")\n",
    "\n",
    "func checkNumber(num int) (string, error) {\n",
    "    if num < 0 {\n",
    "        return \"\", errors.New(\"el número no puede ser negativo\")\n",
    "    }\n",
    "    return \"Número válido\", nil\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    number := -5\n",
    "    message, err := checkNumber(number)\n",
    "    if err != nil {\n",
    "        fmt.Println(\"Error:\", err)\n",
    "    } else {\n",
    "        fmt.Println(\"Mensaje:\", message)\n",
    "    }\n",
    "}\n",
    "\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Otros Paradigmas en GO: Programación Orientada a Objetos\n",
    "\n",
    "GO soporta la programación orientada a objetos a través del uso de structs y métodos. Aunque GO no tiene clases como otros lenguajes orientados a objetos, los structs y métodos proporcionan funcionalidad similar.\n",
    "\n",
    "En este ejemplo, definimos un struct `Rect` con dos campos `width` y `height`, y un método `Area` que calcula el área del rectángulo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "El área del rectángulo es: 50\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "type Rect struct {\n",
    "    width, height int\n",
    "}\n",
    "\n",
    "func (r *Rect) Area() int {\n",
    "    return r.width * r.height\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    rect := Rect{width: 10, height: 5}\n",
    "    \n",
    "    fmt.Println(\"El área del rectángulo es:\", rect.Area())\n",
    "}\n",
    "\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introducción a la Concurrencia en GO\n",
    "\n",
    "La concurrencia en GO permite ejecutar múltiples tareas al mismo tiempo, aprovechando al máximo los recursos del sistema. GO es conocido por su modelo de concurrencia eficiente, basado en goroutines y canales.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Goroutines\n",
    "\n",
    "Las goroutines son funciones que se ejecutan de manera concurrente con otras goroutines en el mismo espacio de memoria. Para crear una goroutine, simplemente se usa la palabra clave `go` seguida de la llamada a la función.\n",
    "\n",
    "En este ejemplo, lanzamos una goroutine que imprime \"Hello, World\". La función `main` continúa ejecutándose y también imprime \"Goroutine lanzada\". Usamos `time.Sleep` para asegurarnos de que la goroutine tenga tiempo de ejecutarse antes de que el programa termine.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Goroutine lanzada\n",
      "Hello, World\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import (\n",
    "    \"fmt\"\n",
    "    \"time\"\n",
    ")\n",
    "\n",
    "func sayHello() {\n",
    "    fmt.Println(\"Hello, World\")\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    go sayHello()\n",
    "    fmt.Println(\"Goroutine lanzada\")\n",
    "    time.Sleep(1 * time.Second) // Permite que la goroutine se ejecute\n",
    "}\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Canales\n",
    "\n",
    "Los canales en GO se utilizan para comunicar y sincronizar goroutines. Permiten enviar y recibir valores entre goroutines de manera segura y eficiente. Para crear un canal, se usa la función `make` con `chan` y el tipo de datos que se enviará a través del canal.\n",
    "\n",
    "En este ejemplo, creamos un canal de cadenas `messages`. La goroutine `sayHello` envía un mensaje a través del canal, y la función `main` recibe y imprime ese mensaje.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, World\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import \"fmt\"\n",
    "\n",
    "func sayHello(c chan string) {\n",
    "    c <- \"Hello, World\"\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    messages := make(chan string)\n",
    "    go sayHello(messages)\n",
    "    msg := <-messages\n",
    "    fmt.Println(msg)\n",
    "}\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Select\n",
    "\n",
    "El `select` en GO se utiliza para esperar múltiples operaciones de canales. Permite a una goroutine esperar hasta que uno de varios canales esté listo para realizar una operación de envío o recepción.\n",
    "\n",
    "En este ejemplo, tenemos dos canales `c1` y `c2`, y dos goroutines que envían mensajes a estos canales después de diferentes periodos de tiempo. Usamos `select` dentro de un bucle `for` para esperar y recibir mensajes de los canales.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "received one\n",
      "received two\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import (\n",
    "    \"fmt\"\n",
    "    \"time\"\n",
    ")\n",
    "\n",
    "func main() {\n",
    "    c1 := make(chan string)\n",
    "    c2 := make(chan string)\n",
    "\n",
    "    go func() {\n",
    "        time.Sleep(1 * time.Second)\n",
    "        c1 <- \"one\"\n",
    "    }()\n",
    "\n",
    "    go func() {\n",
    "        time.Sleep(2 * time.Second)\n",
    "        c2 <- \"two\"\n",
    "    }()\n",
    "\n",
    "    for i := 0; i < 2; i++ {\n",
    "        select {\n",
    "        case msg1 := <-c1:\n",
    "            fmt.Println(\"received\", msg1)\n",
    "        case msg2 := <-c2:\n",
    "            fmt.Println(\"received\", msg2)\n",
    "        }\n",
    "    }\n",
    "}\n",
    "main()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ejemplos basico, intermedio y avanzado de Go (Concurrecia)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ejemplo Básico de Concurrencia en GO\n",
    "\n",
    "#### Descripción del Problema\n",
    "\n",
    "En este ejemplo básico, se mostrará cómo utilizar goroutines y canales en GO para realizar una tarea concurrente. El problema consiste en calcular la suma de los elementos de un arreglo de números enteros. La tarea se dividirá en dos goroutines que calcularán la suma de la primera y la segunda mitad del arreglo respectivamente. Luego, los resultados se combinarán para obtener la suma total.\n",
    "\n",
    "#### Objetivo\n",
    "\n",
    "- Aprender a crear y utilizar goroutines en GO.\n",
    "- Entender cómo los canales pueden facilitar la comunicación entre goroutines.\n",
    "\n",
    "#### Explicación Detallada del Código\n",
    "\n",
    "1. **Definición de la Función sum**:\n",
    "   - La función sum toma un segmento de un arreglo y un canal como parámetros.\n",
    "   - Calcula la suma de los elementos en el segmento y envía el resultado al canal utilizando c <- total.\n",
    "\n",
    "2. **Función main**:\n",
    "   - **Definición del Arreglo**: Se define un arreglo de números enteros, arr, con 10 elementos.\n",
    "   - **Creación del Canal**: Se crea un canal de enteros que se utilizará para recibir los resultados de las goroutines.\n",
    "   - **División de la Tarea**: \n",
    "     - La primera goroutine calcula la suma de la primera mitad del arreglo.\n",
    "     - La segunda goroutine calcula la suma de la segunda mitad del arreglo.\n",
    "   - **Recepción de Resultados**:\n",
    "     - Se reciben los resultados de ambas goroutines a través del canal.\n",
    "   - **Cálculo de la Suma Total**: \n",
    "     - La suma total se calcula combinando los resultados recibidos de las goroutines.\n",
    "   - **Impresión del Resultado**:\n",
    "     - Finalmente, se imprime la suma total.\n",
    "\n",
    "#### Utilización de la Concurrencia en el Ejemplo\n",
    "\n",
    "- **Goroutines**:\n",
    "  - Las goroutines son funciones o métodos que se ejecutan concurrentemente con otras goroutines en el mismo espacio de memoria. En este ejemplo, se utilizan dos goroutines para calcular la suma de dos segmentos diferentes del arreglo de manera concurrente.\n",
    "  - Las goroutines se crean utilizando la palabra clave go seguida de la llamada a la función.\n",
    "  \n",
    "- **Canales**:\n",
    "  - Los canales (chan) en GO se utilizan para comunicar y sincronizar goroutines. Permiten enviar y recibir valores entre goroutines de manera segura.\n",
    "  - En este ejemplo, se utiliza un canal de enteros para recibir los resultados de las dos goroutines que calculan la suma de los segmentos del arreglo.\n",
    "  - Las goroutines envían sus resultados al canal, y la función main recibe esos resultados utilizando el operador <- para leer del canal.\n",
    "\n",
    "#### Beneficios de la Concurrencia\n",
    "\n",
    "- **Eficiencia**:\n",
    "  - La concurrencia permite dividir una tarea grande en sub-tareas más pequeñas que se ejecutan simultáneamente, aprovechando mejor los recursos del sistema.\n",
    "  \n",
    "- **Simplicidad en GO**:\n",
    "  - GO proporciona una manera sencilla y eficiente de manejar la concurrencia utilizando goroutines y canales, facilitando la implementación de soluciones concurrentes sin la complejidad de manejar directamente los hilos del sistema operativo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "La suma total es: 55\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import (\n",
    "    \"fmt\"\n",
    ")\n",
    "\n",
    "// sum calcula la suma de un segmento de un arreglo y envía el resultado a un canal\n",
    "func sum(arr []int, c chan int) {\n",
    "    total := 0\n",
    "    for _, v := range arr {\n",
    "        total += v\n",
    "    }\n",
    "    c <- total // Enviar el resultado al canal\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    arr := []int{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}\n",
    "    c := make(chan int)\n",
    "\n",
    "    // Dividir la tarea en dos goroutines\n",
    "    go sum(arr[:len(arr)/2], c)\n",
    "    go sum(arr[len(arr)/2:], c)\n",
    "\n",
    "    // Recibir los resultados de ambas goroutines\n",
    "    sum1, sum2 := <-c, <-c\n",
    "\n",
    "    // Calcular la suma total\n",
    "    totalSum := sum1 + sum2\n",
    "\n",
    "    fmt.Println(\"La suma total es:\", totalSum)\n",
    "}\n",
    "\n",
    "main()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ejemplo Intermedio de Concurrencia en GO\n",
    "\n",
    "#### Descripción del Problema\n",
    "\n",
    "En este ejemplo intermedio, se mostrará cómo utilizar goroutines y canales en GO para realizar un cálculo concurrente más complejo. El problema consiste en calcular la suma de los números primos en un rango dado. La tarea se dividirá en varias goroutines que calcularán si los números en sub-rangos son primos. Luego, los resultados se combinarán para obtener la suma total de los números primos en el rango.\n",
    "\n",
    "#### Objetivo\n",
    "\n",
    "- Aprender a crear y utilizar múltiples goroutines en GO.\n",
    "- Entender cómo los canales pueden facilitar la comunicación y sincronización entre múltiples goroutines.\n",
    "\n",
    "#### Explicación Detallada del Código\n",
    "\n",
    "1. **Definición de la Función isPrime**:\n",
    "   - La función isPrime toma un número entero y devuelve un booleano indicando si el número es primo o no.\n",
    "\n",
    "2. **Definición de la Función sumPrimes**:\n",
    "   - La función sumPrimes toma un rango de números y un canal como parámetros.\n",
    "   - Calcula la suma de los números primos en ese rango y envía el resultado al canal utilizando c <- total.\n",
    "\n",
    "3. **Función main**:\n",
    "   - **Definición del Rango**: Se define un rango de números enteros.\n",
    "   - **Creación del Canal**: Se crea un canal de enteros que se utilizará para recibir los resultados de las goroutines.\n",
    "   - **División de la Tarea**: \n",
    "     - Se divide el rango en sub-rangos y se lanza una goroutine para cada sub-rango.\n",
    "   - **Recepción de Resultados**:\n",
    "     - Se reciben los resultados de todas las goroutines a través del canal.\n",
    "   - **Cálculo de la Suma Total de Números Primos**: \n",
    "     - La suma total se calcula combinando los resultados recibidos de las goroutines.\n",
    "   - **Impresión del Resultado**:\n",
    "     - Finalmente, se imprime la suma total de números primos.\n",
    "\n",
    "#### Utilización de la Concurrencia en el Ejemplo\n",
    "\n",
    "- **Goroutines**:\n",
    "  - Las goroutines son funciones o métodos que se ejecutan concurrentemente con otras goroutines en el mismo espacio de memoria. En este ejemplo, se utilizan múltiples goroutines para verificar si los números en sub-rangos son primos de manera concurrente.\n",
    "  - Las goroutines se crean utilizando la palabra clave go seguida de la llamada a la función.\n",
    "  \n",
    "- **Canales**:\n",
    "  - Los canales (chan) en GO se utilizan para comunicar y sincronizar goroutines. Permiten enviar y recibir valores entre goroutines de manera segura.\n",
    "  - En este ejemplo, se utiliza un canal de enteros para recibir los resultados de las múltiples goroutines que calculan la suma de números primos en los sub-rangos.\n",
    "  - Las goroutines envían sus resultados al canal, y la función main recibe esos resultados utilizando el operador <- para leer del canal.\n",
    "\n",
    "#### Beneficios de la Concurrencia\n",
    "\n",
    "- **Eficiencia**:\n",
    "  - La concurrencia permite dividir una tarea compleja en sub-tareas más pequeñas que se ejecutan simultáneamente, aprovechando mejor los recursos del sistema.\n",
    "  \n",
    "- **Simplicidad en GO**:\n",
    "  - GO proporciona una manera sencilla y eficiente de manejar la concurrencia utilizando goroutines y canales, facilitando la implementación de soluciones concurrentes sin la complejidad de manejar directamente los hilos del sistema operativo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "La suma total de números primos es: 3203324994356\n"
     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import (\n",
    "    \"fmt\"\n",
    "    \"math\"\n",
    ")\n",
    "\n",
    "// isPrime verifica si un número es primo\n",
    "func isPrime(n int) bool {\n",
    "    if n <= 1 {\n",
    "        return false\n",
    "    }\n",
    "    for i := 2; i <= int(math.Sqrt(float64(n))); i++ {\n",
    "        if n%i == 0 {\n",
    "            return false\n",
    "        }\n",
    "    }\n",
    "    return true\n",
    "}\n",
    "\n",
    "// sumPrimes calcula la suma de números primos en un rango y envía el resultado a un canal\n",
    "func sumPrimes(start, end int, c chan int) {\n",
    "    total := 0\n",
    "    for i := start; i <= end; i++ {\n",
    "        if isPrime(i) {\n",
    "            total += i\n",
    "        }\n",
    "    }\n",
    "    c <- total // Enviar el resultado al canal\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    start, end := 1, 10000000\n",
    "    numGoroutines := 10\n",
    "    rangeSize := (end - start + 1) / numGoroutines\n",
    "    c := make(chan int, numGoroutines)\n",
    "\n",
    "    // Dividir la tarea en varias goroutines\n",
    "    for i := 0; i < numGoroutines; i++ {\n",
    "        subStart := start + i*rangeSize\n",
    "        subEnd := subStart + rangeSize - 1\n",
    "        if i == numGoroutines-1 {\n",
    "            subEnd = end\n",
    "        }\n",
    "        go sumPrimes(subStart, subEnd, c)\n",
    "    }\n",
    "\n",
    "    // Recibir los resultados de todas las goroutines\n",
    "    totalSum := 0\n",
    "    for i := 0; i < numGoroutines; i++ {\n",
    "        totalSum += <-c\n",
    "    }\n",
    "\n",
    "    fmt.Println(\"La suma total de números primos es:\", totalSum)\n",
    "}\n",
    "\n",
    "main()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ejemplo Avanzado de Concurrencia en GO\n",
    "\n",
    "#### Descripción del Problema\n",
    "\n",
    "En este ejemplo avanzado, se demostrará cómo utilizar goroutines y canales en GO para resolver un problema complejo: calcular el producto de múltiples matrices grandes de manera concurrente. Cada multiplicación de matrices se realiza utilizando múltiples goroutines para calcular las filas de la matriz resultante de manera simultánea. La matriz resultante de cada multiplicación se utiliza como entrada para la siguiente multiplicación, formando una cadena de multiplicaciones.\n",
    "\n",
    "#### Objetivo\n",
    "\n",
    "- Aprender a crear y utilizar múltiples goroutines en GO para realizar cálculos concurrentes en una operación compleja.\n",
    "- Entender cómo los canales pueden facilitar la comunicación y sincronización entre goroutines en un contexto de cálculo numérico con múltiples pasos.\n",
    "\n",
    "#### Explicación Detallada del Código\n",
    "\n",
    "1. Función multiplyMatrices:\n",
    "   - La función multiplyMatrices toma dos matrices y un canal como parámetros.\n",
    "   - Calcula el producto de las matrices utilizando múltiples goroutines, cada una encargada de calcular un subconjunto de los elementos de la matriz resultante.\n",
    "   - Los resultados se envían al canal.\n",
    "\n",
    "2. Función generateMatrix:\n",
    "   - La función generateMatrix genera una matriz de tamaño n x m con valores aleatorios entre 0 y 9.\n",
    "\n",
    "3. Función main:\n",
    "   - La función main inicializa varias matrices grandes, crea los canales y lanza las goroutines.\n",
    "   - Recoge los resultados de las goroutines y construye la matriz resultante para cada multiplicación.\n",
    "   - Imprime la matriz resultante final después de todas las multiplicaciones.\n",
    "\n",
    "#### Utilización de la Concurrencia en el Ejemplo\n",
    "\n",
    "- **Goroutines**:\n",
    "  - Las goroutines se utilizan para realizar el cálculo de los elementos de la matriz resultante de manera concurrente. Esto permite dividir el trabajo en múltiples sub-tareas que se ejecutan simultáneamente, mejorando la eficiencia del cálculo.\n",
    "  - Las goroutines se crean utilizando la palabra clave go seguida de la llamada a la función.\n",
    "  \n",
    "- **Canales**:\n",
    "  - Los canales (chan) en GO se utilizan para recolectar los resultados parciales del cálculo de las goroutines.\n",
    "  - Las goroutines envían sus resultados parciales al canal, y la función main recibe esos resultados utilizando el operador <- para leer del canal.\n",
    "\n",
    "#### Beneficios de la Concurrencia\n",
    "\n",
    "- **Eficiencia**:\n",
    "  - La concurrencia permite que el cálculo del producto de matrices se realice de manera más eficiente, dividiendo la carga de trabajo entre múltiples goroutines.\n",
    "  \n",
    "- **Simplicidad en GO**:\n",
    "  - GO proporciona una manera sencilla y eficiente de manejar la concurrencia utilizando goroutines y canales, facilitando la implementación de cálculos numéricos concurrentes sin la complejidad de manejar directamente los hilos del sistema operativo.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Matriz resultante:\n",
      "[383970834 475989308 429576934 415013209 435077774 392235297 429732745 380055987 431877869 426622458 429877249 396069097 443999058 380252049 443037225 408759971 423855987 377570540 402912183 424919294 431324246 429553441 385942906 420157703 435162854 399186468 403472927 424110952 417116631 444589384 408747470 416831864 375705989 436522681 440248975 410601117 477161541 454095877 395294232 411386215 388564792 426178272 451185294 405754414 426631186 353657242 433281793 385677532 428646075 445364079 390716673 378365719 394482106 381839355 453184528 415357712 388913795 431745464 459967402 427020125 389565387 427816471 474125824 398827210 375921788 389628155 378310281 386680158 431494807 379074540 390532957 443252428 410130668 399244041 410330328 379695404 386386773 384165726 405929765 441161809 386204851 397110613 415789308 364304817 436461233 391972490 422776751 395201373 400770008 389250374 439823887 431161235 349804776 436927855 337709151 424806264 410140521 424878317 362669792 367962421]\n",
      "[408024080 505546949 456234482 440755903 462039495 416538286 456575712 403704072 458775908 453143294 456609207 420715745 471732057 403704409 470587772 434024765 450246153 401097874 427974931 451309233 458104812 456115552 409867938 446250504 462307810 424036023 428495042 450419539 442873409 472251946 434036925 442718454 399167008 463521983 467630921 435872272 507100467 482338590 419943700 437049836 412624199 452734047 479329728 431012291 453137641 375537583 460283490 409743442 455212292 473287514 415011707 401696077 419085865 405716459 481258216 441063456 412989913 458221350 488269577 453470260 413917629 454322534 503590603 423709730 399133009 414033007 401911824 410766040 458199812 402719235 414634177 470801676 435537053 424255411 435913586 403389832 410503308 407901398 431020294 468667200 410306224 421773067 441494612 387157296 463503686 416325255 449166563 419700033 425634997 413494393 467205945 457969426 371472414 464131215 358886182 451020528 435703517 451352814 385192706 390805834]\n",
      "[393098171 487058436 439516009 424709535 445369803 401286031 439809383 389104697 442144672 436665885 439967309 405235411 454564165 389031757 453525182 418231981 433762325 386462881 412280007 434862088 441475006 439592130 394805807 430018392 445322954 408538726 412865229 433986235 426795814 455057156 418164626 426612330 384576804 446720631 450414980 420169583 488461668 464642499 404751895 421082844 397520894 436414891 461688253 415461342 436590127 361998026 443478675 394795844 438560253 455983071 399807144 387143289 403878841 390915883 463786638 424936767 398029879 441720997 470432258 437132579 398757623 437805362 485176916 408219011 384678664 398914024 387216581 395658372 441410403 387857272 399753503 453739472 419826326 408782852 419844090 388643835 395436878 393014090 415301926 451627278 395342460 406345390 425435561 372916764 446594894 401124986 432915470 404473011 410213533 398263509 450221138 441310950 358035438 447103863 345752904 434750443 419735593 434879855 371127476 376509066]\n",
      "[398596751 493999141 445885440 430762048 451645479 407241566 446227715 394354234 448339303 442742946 446361215 411069008 460753167 394698292 459913658 424337806 439869122 391958019 418166764 441122576 447817234 445891293 400514590 435946861 451669291 414558144 418666892 440309520 433029992 461463447 424337019 432753533 389947772 453079119 457032825 426201568 495450990 471243122 410262283 426978996 403360386 442343377 468274607 421327207 442773212 367155487 449973454 400301721 444968689 462338843 405680762 392831664 409382065 396402564 470334100 431101691 403659348 448144192 477257840 443161814 404376481 443976573 492175677 413922453 390078943 404528195 392625654 401377781 447936325 393575328 405334099 460041677 425849745 414454727 426056020 394182669 401192651 398745627 421261283 457839237 400770586 412043749 431607683 378365325 453029430 406770961 439059324 410173225 416000148 404093504 456686906 447501239 363148466 453521991 350726003 440799892 425798258 441099848 376375039 381907834]\n",
      "[375253781 465035528 419505362 405482481 424981613 383297552 419793237 371255628 421929466 416706804 419907702 386763997 433637453 371430996 432750721 399170770 413982515 368672614 393531784 415054871 421397755 419663090 376871343 410246461 425123760 390026544 393974472 414218113 407355012 434302283 399284684 407305526 366908311 426298325 430045183 400969995 466251468 443410042 386239719 401858862 379655013 416387382 440642899 396435931 416768707 345567850 423358340 376884045 418629455 435333891 381674515 369474591 385410093 372962461 442639624 405534627 379865597 421668017 449040568 417186437 380632266 417752861 463116278 389637769 366965239 380689313 369564875 377557984 421510166 370311196 381499903 432884678 400696712 390211225 400900317 370909995 377487194 375155333 396463589 431036586 377215659 387908702 406027893 355967058 426357729 382780337 413170791 385921711 391535084 380203233 429691908 421302690 341733367 426768328 329943488 414884854 400728844 415067124 354152917 359484447]\n",
      "[379790084 470670439 424746850 410464432 430182815 387857184 424984969 375856216 427074712 421821873 425166212 391640458 439223719 376057770 438094229 404121051 419111320 373424714 398391779 420113110 426398841 424743769 381657252 415441361 430471887 394727262 398967506 419332732 412398521 439553341 404121607 412256340 371493812 431640705 435334296 405876527 472028363 449046490 390840332 406833123 384271102 421535823 446222714 401268134 421966908 349752093 428494751 381437367 423888263 440436459 386344811 374022135 390145322 377598506 448087060 410606971 384573556 426804032 454731659 422239792 385231775 422994818 468890899 394488601 371563169 385303284 374197806 382331010 426617956 374852184 386042923 438205996 405677931 394919167 405711274 375523473 382229231 379773459 401369058 436324150 381804072 392697991 411116639 360271343 431598979 387491815 418196277 390730576 396342020 384857718 434846870 426556787 346008881 431981031 334105883 420005285 405624539 420170578 358586592 363855027]\n",
      "[412141875 510839435 460968767 445350378 467129529 420974720 461328093 407763452 463446604 457810299 461504678 425037318 476452852 407859050 475614400 438637401 454897621 405301538 432546900 456058009 463016566 460976441 414105662 450854293 467001901 428587487 432860664 455226193 447486800 477109806 438692519 447418236 403244642 468478361 472529905 440547732 512336773 487277972 424351463 441619943 417173922 457475758 484208069 435629259 457778648 379611628 465197061 414064576 460011819 478068120 419401780 405975216 423525483 409929512 486279246 445644540 417433528 463349951 493453163 458227383 418099625 459142705 508861283 428061029 403237199 418391010 406077672 415107303 463001343 406804649 418959424 475682901 440436289 428700577 440531373 407608724 414818821 412230552 435451341 473522728 414456417 426244304 446180116 391128596 468447266 420629783 453974104 424106778 430208014 417767937 472143493 462861924 375517360 468875025 362622546 455774657 440387600 456084144 389179633 394928466]\n",
      "[436821289 541239518 488450010 471886318 494799776 445988384 488840296 432374915 491225791 485124910 489048475 450359316 504973414 432315128 503930251 464771239 482011669 429504127 458117821 483204167 490460169 488447682 438791563 477874757 494929725 454007206 458728648 482396103 474226701 505577196 464748249 474036023 427424313 496352901 500640408 466873552 542866117 516432766 449608387 468021845 441804678 484782790 513100946 461477859 485170255 402299159 492837936 438798431 487444844 506640517 444301851 430196207 448762744 434390446 515332675 472162467 442268437 490882977 522858810 485557545 443060413 486488474 539216322 453538685 427341840 443241814 430264327 439763763 490493968 431133657 444052838 504162816 466414854 454180246 466695264 431962610 439493808 436714032 461488417 501850672 439282303 451538930 472741024 414438144 496339069 445767735 480996050 449406016 455797649 442597522 500214119 490469541 397841478 496945018 384308394 483019228 466537567 483321622 412471454 418335349]\n",
      "[364727227 451993725 407866256 394129746 413051078 372556907 408239321 361074826 410188873 405083406 408219998 376092560 421661791 360988234 420767263 388053052 402577714 358626313 382540172 403560831 409780695 407867814 366490501 399112741 413286907 379042899 383021072 402681204 395974740 422265662 388149236 395920514 356864038 414433310 418104872 389939644 453406730 431231978 375516847 390813443 368978042 405004423 428442649 385356101 405178991 336006147 411658511 366408127 406983109 423025953 371061674 359097896 374777305 362623984 430380976 394443777 369308027 409879002 436532665 405494293 370016964 406196508 450225469 378818621 356934927 370125978 359247638 367246839 409726067 360053876 370831178 420849787 389419038 379378097 389705676 360722749 367003095 364682108 385448136 419025558 366764762 377118409 394716341 345952161 414411461 372230814 401645891 375199265 380666107 369611495 417748309 409526967 332280141 414957663 320946987 403424764 389595388 403661899 344426438 349337557]\n",
      "[380886735 472107929 425990257 411480437 431546692 388944934 426210738 377039257 428336100 423053234 426405479 392712359 440386927 376964964 439390020 405348870 420237199 374506857 399482179 421384524 427783570 425933438 382653926 416666002 431520644 395951641 400152782 420612008 413660458 440924244 405319256 413395862 372707972 432970156 436542323 407181360 473254021 450348996 392131219 408193996 385384585 422630035 447398318 402523882 423149376 350874823 429857121 382621024 425125858 441857991 387411527 375220533 391330145 378802397 449413629 411735047 385645078 428184032 455918732 423539583 386395385 424306829 470257194 395410710 372720619 386537870 375268540 383388135 427840291 375900948 387267617 439728389 406806141 396086092 406908047 376781909 383260532 380900672 402361595 437652176 383088366 393792769 412300951 361477718 432873088 388800633 419486823 391989271 397527346 385941012 436320245 427629014 346944739 433352193 335103775 421255442 406768598 421417015 359733755 364934920]\n",
      "[365185734 452469440 408416667 394598049 413616046 373060961 408726702 361223786 410507744 405531578 408728080 376544795 422086565 361436655 421272328 388593469 402897204 358965320 383016457 403950139 410159745 408396955 366817598 399367192 413766736 379663705 383409850 403304343 396502838 422709402 388616566 396333609 357219322 414952143 418589838 390239103 453861225 431600864 375820448 391097867 369399737 405306108 428977320 385767248 405573467 336323263 412080749 366744514 407548662 423471203 371516759 359660443 375095236 363145533 430833206 394818359 369694849 410365034 437191790 405937478 370325463 406705426 450685897 379262733 357247760 370559129 359666349 367654305 410261827 360394555 371172039 421334543 390068559 379796259 390147532 360957208 367420093 365027624 385928470 419457099 367152122 377515760 395297072 346539105 415023567 372568066 402120420 375637244 381084915 370110910 418202277 410124429 332625727 415378723 321279473 403670498 390110612 403957001 344759714 349820834]\n",
      "[379504943 470142844 424295188 410099079 430054977 387599449 424888984 375592296 426872189 421454228 424819358 391216330 438778571 375729696 437901016 403948695 418932974 373028362 398228328 419852137 426261383 424518199 381332571 415259524 429916519 394549651 398613944 419077195 412208258 439295635 403786454 411997734 371383578 431295706 435093745 405672887 471700186 448799512 390709738 406569408 384180609 421227358 445789915 400944306 421493040 349568791 428268806 381305130 423517429 440190811 386151864 373771613 389874761 377235860 447870102 410416462 384400958 426575148 454476581 421907825 384905164 422691382 468603747 394177333 371296524 385156315 373827940 382250607 426204781 374626265 385738677 438122462 405361165 394666410 405558535 375253875 381993097 379591807 401136222 435989363 381651551 392412338 410704551 360007779 431366620 387240358 417824202 390434695 395958339 384655103 434625582 426201697 345683156 431707183 333791445 419702389 405246780 419978999 358383109 363597128]\n",
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     ]
    }
   ],
   "source": [
    "package main\n",
    "\n",
    "import (\n",
    "    \"fmt\"\n",
    "    \"math/rand\"\n",
    "    \"time\"\n",
    ")\n",
    "\n",
    "// multiplyMatrices calcula el producto de dos matrices y envía la fila calculada al canal\n",
    "func multiplyMatrices(A, B [][]int, C chan<- []int, startRow, endRow int) {\n",
    "    for i := startRow; i < endRow; i++ {\n",
    "        row := make([]int, len(B[0]))\n",
    "        for j := 0; j < len(B[0]); j++ {\n",
    "            sum := 0\n",
    "            for k := 0; k < len(B); k++ {\n",
    "                sum += A[i][k] * B[k][j]\n",
    "            }\n",
    "            row[j] = sum\n",
    "        }\n",
    "        C <- row\n",
    "    }\n",
    "}\n",
    "\n",
    "// generateMatrix genera una matriz de tamaño n x m con valores aleatorios\n",
    "func generateMatrix(n, m int) [][]int {\n",
    "    rand.Seed(time.Now().UnixNano())\n",
    "    matrix := make([][]int, n)\n",
    "    for i := range matrix {\n",
    "        matrix[i] = make([]int, m)\n",
    "        for j := range matrix[i] {\n",
    "            matrix[i][j] = rand.Intn(10) // Valores aleatorios entre 0 y 9\n",
    "        }\n",
    "    }\n",
    "    return matrix\n",
    "}\n",
    "\n",
    "func main() {\n",
    "    // Generar matrices de tamaño 100 x 100\n",
    "    A := generateMatrix(100, 100)\n",
    "    B := generateMatrix(100, 100)\n",
    "    C := generateMatrix(100, 100)\n",
    "    D := generateMatrix(100, 100)\n",
    "\n",
    "    matrices := [][][]int{A, B, C, D}\n",
    "    numMatrices := len(matrices)\n",
    "    result := generateMatrix(100, 100)\n",
    "\n",
    "    for m := 0; m < numMatrices-1; m++ {\n",
    "        current := matrices[m]\n",
    "        next := matrices[m+1]\n",
    "\n",
    "        rows := len(current)\n",
    "        cols := len(next[0])\n",
    "        result = make([][]int, rows)\n",
    "        for i := range result {\n",
    "            result[i] = make([]int, cols)\n",
    "        }\n",
    "\n",
    "        C := make(chan []int, rows)\n",
    "        numGoroutines := 4\n",
    "        rowsPerGoroutine := rows / numGoroutines\n",
    "\n",
    "        // Dividir la tarea en varias goroutines\n",
    "        for i := 0; i < numGoroutines; i++ {\n",
    "            startRow := i * rowsPerGoroutine\n",
    "            endRow := startRow + rowsPerGoroutine\n",
    "            if i == numGoroutines-1 {\n",
    "                endRow = rows\n",
    "            }\n",
    "            go multiplyMatrices(current, next, C, startRow, endRow)\n",
    "        }\n",
    "\n",
    "        // Recibir los resultados de todas las goroutines\n",
    "        for i := 0; i < rows; i++ {\n",
    "            result[i] = <-C\n",
    "        }\n",
    "        close(C)\n",
    "\n",
    "        // Actualizar la matriz actual con el resultado para la próxima multiplicación\n",
    "        matrices[m+1] = result\n",
    "    }\n",
    "\n",
    "    fmt.Println(\"Matriz resultante:\")\n",
    "    for _, row := range result {\n",
    "        fmt.Println(row)\n",
    "    }\n",
    "}\n",
    "\n",
    "main()\n"
   ]
  }
 ],
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