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‎homework/hw1/259359_hw1_2025_1/.ipynb_checkpoints/Tarea 1-checkpoint.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5ef22780-d8af-4dac-9fc2-7014ae48ea64",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Para crear el enviroment ----------------------------\n",
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"#--------------Creamos el enviroment\n",
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"# conda create -n Tarea1 python=3.11\n",
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"#-------------Lo activamos\n",
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"# conda activate Tarea1 \n",
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"#------------Vamos a la ruta del txt\n",
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"# cd Documents/GitHub/Data-Science-Python/homework/hw1/259359_hw1_2025_1\n",
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"#------------Instalamos\n",
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"# pip install -r requirements.txt "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "fbf681bd-2fb1-42f1-baeb-91c5821757bc",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Collecting webdriver-manager\n",
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" Downloading webdriver_manager-4.0.2-py2.py3-none-any.whl.metadata (12 kB)\n",
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"Requirement already satisfied: requests in c:\\users\\fabrizio\\anaconda3\\envs\\tarea1\\lib\\site-packages (from webdriver-manager) (2.32.3)\n",
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"Collecting python-dotenv (from webdriver-manager)\n",
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" Downloading python_dotenv-1.1.0-py3-none-any.whl.metadata (24 kB)\n",
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"Requirement already satisfied: packaging in c:\\users\\fabrizio\\anaconda3\\envs\\tarea1\\lib\\site-packages (from webdriver-manager) (24.2)\n",
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"Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\fabrizio\\anaconda3\\envs\\tarea1\\lib\\site-packages (from requests->webdriver-manager) (3.4.1)\n",
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"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\fabrizio\\anaconda3\\envs\\tarea1\\lib\\site-packages (from requests->webdriver-manager) (3.10)\n",
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"Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\fabrizio\\anaconda3\\envs\\tarea1\\lib\\site-packages (from requests->webdriver-manager) (2.3.0)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\fabrizio\\anaconda3\\envs\\tarea1\\lib\\site-packages (from requests->webdriver-manager) (2025.1.31)\n",
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"Downloading webdriver_manager-4.0.2-py2.py3-none-any.whl (27 kB)\n",
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"Downloading python_dotenv-1.1.0-py3-none-any.whl (20 kB)\n",
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"Installing collected packages: python-dotenv, webdriver-manager\n",
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"Successfully installed python-dotenv-1.1.0 webdriver-manager-4.0.2\n"
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]
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}
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],
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"source": [
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"!pip install webdriver-manager #instalo el driver"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "f11af34a-9478-4b18-8913-4bde935da04f",
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"metadata": {},
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"outputs": [],
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"source": [
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"#importo las librerías que se instalaron arriba\n",
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"from selenium import webdriver\n",
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"from selenium.webdriver.chrome.service import Service\n",
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"from webdriver_manager.chrome import ChromeDriverManager\n",
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"from selenium.webdriver.common.by import By\n",
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"from selenium.webdriver.support.ui import WebDriverWait\n",
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"from selenium.webdriver.support import expected_conditions as EC\n",
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"import time\n",
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"import re\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 53,
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"id": "b76f4fb9-d540-416c-9e67-d3447e871032",
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"metadata": {},
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"outputs": [],
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"source": [
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"##ejecuto el driver y abro la pagina de bumeran\n",
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"driver = webdriver.Chrome()\n",
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"url = \"https://www.bumeran.com.pe/empleos.html\"\n",
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"driver.get(url)\n",
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"driver.maximize_window()\n",
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"time.sleep(5) #esperamos a que se abra la pestaña\n",
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"driver.execute_script(\"document.body.style.zoom='100%'\") #ampliamos la ventana"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9e5051a4-ed60-489b-867d-adb48384d820",
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"metadata": {},
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"source": [
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"----------FILTROS------------------------"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b911f333-cdc5-43a8-a31f-6c84a942538d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Abriendo el filtro de fecha de publicación y seleccionando los últimos 15 días\n",
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"driver.find_element(By.NAME, 'icon-light-calendar').click()\n",
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"time.sleep(3)\n",
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"\n",
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"fecha_15_dias = driver.find_element(By.XPATH, \"//button[contains(text(), 'Menor a 15 días')]\")\n",
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"fecha_15_dias.click()\n",
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"time.sleep(3)\n",
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"\n",
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"# Entrando al menú de áreas laborales y eligiendo \"Tecnología, Sistemas y Telecomunicaciones\"\n",
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"driver.find_element(By.NAME, 'icon-light-cube').click()\n",
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"time.sleep(3)\n",
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"\n",
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"area_tecnologia = driver.find_element(By.XPATH, \"//button[contains(text(), 'Tecnología, Sistemas y Telecomunicaciones')]\")\n",
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"area_tecnologia.click()\n",
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"time.sleep(3)\n",
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"\n",
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"# Accediendo al menú de subáreas y seleccionando \"Programación\"\n",
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"driver.find_element(By.NAME, 'icon-light-layers').click()\n",
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"time.sleep(3)\n",
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"\n",
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"subarea_programacion = driver.find_element(By.XPATH, \"//button[contains(text(), 'Programación')]\")\n",
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"subarea_programacion.click()\n",
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"time.sleep(7)\n",
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"\n",
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"# Configurando el filtro de ubicación en \"Lima\"\n",
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"driver.find_element(By.XPATH, \"//button//i[@name='icon-light-location-pin']/..\").click()\n",
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"time.sleep(9)\n",
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"\n",
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"lima = driver.find_element(By.XPATH, \"//button[contains(text(), 'Lima')]\")\n",
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"lima.click()\n",
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"time.sleep(10)\n",
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"\n",
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"# Ajustando la preferencia de jornada laboral a \"Full-time\"\n",
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"driver.find_element(By.NAME, 'icon-light-bookmark').click()\n",
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"time.sleep(10)\n",
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"\n",
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"full_time = driver.find_element(By.XPATH, \"//button[contains(text(), 'Full-time')]\")\n",
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"full_time.click()\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e02a58e5-efb8-41f1-bac2-5abeb10f1614",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Esperar a que los botones con enlaces de empleo carguen en la página\n",
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"WebDriverWait(driver, 8).until(EC.presence_of_all_elements_located((By.CLASS_NAME, \"sc-zDqdV\")))\n",
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"# Buscar todos los botones que contienen los enlaces de las ofertas\n",
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"botones_enlaces = driver.find_elements(By.CLASS_NAME, \"sc-zDqdV\")\n",
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"# Extraer los enlaces de cada botón y guardarlos en una lista\n",
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"enlaces_empleos = [boton.get_attribute(\"href\") for boton in botones_enlaces]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "e2bf51cf-c22d-4384-b085-7da2eecf4a68",
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"metadata": {},
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"outputs": [],
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"source": [
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"enlaces_empleos # comprobamos"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b49ad877-824e-49af-950f-36a0aab6ee07",
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"metadata": {},
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"outputs": [],
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"source": [
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"#✅ Stage 2: Scrape Job Details\n",
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"# Iniciamos el navegador y lo maximizamos\n",
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"driver = webdriver.Chrome()\n",
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"driver.maximize_window()\n",
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"\n",
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"# Lista para almacenar la información\n",
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"datos_empleos = []\n",
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"\n",
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"# Función para obtener el distrito\n",
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"def obtener_distrito(driver):\n",
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" xpaths_distrito = [\n",
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" \"//div[contains(@class, 'ubicacion')]//h2\",\n",
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" \"//li[contains(@class, 'ubicacion')]//a\"\n",
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" ]\n",
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" for xpath in xpaths_distrito:\n",
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" elementos = driver.find_elements(By.XPATH, xpath)\n",
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" if elementos:\n",
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" return elementos[0].text.split(\",\")[0].strip() # Extraemos solo el distrito\n",
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" return \"Distrito no encontrado\"\n",
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"\n",
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"# Función para obtener la modalidad de trabajo\n",
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"def obtener_modalidad(driver):\n",
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" xpaths_modalidad = [\n",
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" \"//ul[contains(@class, 'modalidad')]//li/a\",\n",
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" \"//div[contains(@class, 'detalles')]//ul/li\"\n",
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" ]\n",
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" for xpath in xpaths_modalidad:\n",
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" elementos = driver.find_elements(By.XPATH, xpath)\n",
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" if elementos:\n",
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" return elementos[0].text.strip()\n",
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" return \"No especificado\"\n",
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"\n",
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"# Función para obtener la descripción del empleo\n",
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"def obtener_descripcion(driver):\n",
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" try:\n",
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" descripcion_completa = driver.find_element(By.ID, \"ficha-detalle\").text\n",
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" descripcion, _, _ = descripcion_completa.partition(\"Beneficios\") # Toma solo lo anterior a \"Beneficios\"\n",
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" return descripcion.strip()\n",
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" except:\n",
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" return \"Descripción no disponible\"\n",
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"\n",
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"# Recorremos los enlaces y extraemos la información\n",
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"for enlace in lista_enlaces:\n",
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" try:\n",
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" driver.get(enlace)\n",
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"\n",
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" # Extraer título\n",
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" titulo = WebDriverWait(driver, 8).until(\n",
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" EC.presence_of_element_located((By.TAG_NAME, 'h1'))\n",
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" ).text\n",
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"\n",
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" # Extraer información usando funciones\n",
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" distrito = obtener_distrito(driver)\n",
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" modalidad = obtener_modalidad(driver)\n",
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" descripcion = obtener_descripcion(driver)\n",
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"\n",
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" # Guardamos los datos\n",
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" datos_empleos.append([titulo, descripcion, distrito, modalidad, enlace])\n",
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"\n",
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" print(f\"Datos obtenidos de: {enlace}\")\n",
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"\n",
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" except Exception as e:\n",
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" print(f\"Error al procesar {enlace}: {e}\")\n",
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"\n",
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"# Cerrar navegador\n",
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"driver.quit()\n",
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"\n",
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"# Guardar en un archivo Excel\n",
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"df = pd.DataFrame(datos_empleos, columns=[\"Título\", \"Descripción\", \"Distrito\", \"Modalidad\", \"Enlace\"])\n",
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"df.to_csv(\"Trabajos_Bumeran.csv\", index=False, encoding=\"utf-8\", sep=\"|\")\n",
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"\n",
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"print(\"Extracción completada. Datos guardados en 'Trabajos_Bumeran.xlsx'.\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4b5c1235-1191-4c1b-b035-a5cfbfb5cd5c",
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"metadata": {},
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"outputs": [],
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"source": [
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"#Gracias :)))))"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python [conda env:Tarea1]",
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"language": "python",
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"name": "conda-env-Tarea1-py"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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