scripts/scrape_website.py

import json
import os
import time
from urllib.parse import urlparse

import openai
import pandas as pd
from bs4 import BeautifulSoup
from selenium import webdriver
from selenium.common.exceptions import (
    WebDriverException,
)
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.common.by import By
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from webdriver_manager.chrome import ChromeDriverManager

# Set up OpenAI API
openai.api_key = os.getenv("OPENAI")

# Initialize followup number
followup_number = 0

# Start with page 1
page_number = 4

# Get the current working directory
cwd = os.getcwd()

# Path to the CSV file
csv_file = os.path.join(cwd, "vacancies.csv")

while True:
    try:
        # Setup webdriver
        s = Service(ChromeDriverManager().install())
        driver = webdriver.Chrome(service=s)

        # The URL of the page with the buttons
        url = f"https://vacatures.jobfixers.be/zoek?page={page_number}&size=50&sortBy=updated:desc&initial=true"

        # Navigate to the page
        driver.get(url)

        # Wait for the page to load
        time.sleep(5)

        # Find the buttons
        buttons = WebDriverWait(driver, 10).until(
            EC.presence_of_all_elements_located(
                (
                    By.XPATH,
                    '//button[@mat-button and contains(@class, "mat-focus-indicator mat-button mat-button-base")]',
                )
            )
        )

        for i in range(len(buttons)):
            # Find the buttons again to avoid StaleElementReferenceException
            buttons = WebDriverWait(driver, 10).until(
                EC.presence_of_all_elements_located(
                    (
                        By.XPATH,
                        '//button[@mat-button and contains(@class, "mat-focus-indicator mat-button mat-button-base")]',
                    )
                )
            )

            # Click the button
            buttons[i].click()

            # Wait for the new page to load
            time.sleep(5)

            # Get the page source
            html = driver.page_source

            # Parse the HTML with BeautifulSoup
            soup = BeautifulSoup(html, "html.parser")

            # Extract relevant items related to the vacancy
            vacancy_detail = {}

            # Extracting the job position
            vacancy_detail["Position"] = soup.select_one(
                ".vacancy-detail__content__header__position"
            ).text.strip()

            # Extracting the location
            vacancy_detail["Location"] = soup.select_one(
                ".vacancy-detail__content__header__location a"
            ).text.strip()

            # Extracting the description
            description = soup.select_one(
                ".vacancy-detail__content__body__description__details"
            ).get_text(separator=" ")
            vacancy_detail["Description"] = description.strip()

            # Extracting the profile details
            profile_details = soup.select(
                ".vacancy-detail__content__body__profile__details li"
            )
            vacancy_detail["Profile"] = [
                detail.text.strip() for detail in profile_details
            ]

            # Extracting the list of competences
            competences = soup.select(
                ".vacancy-detail__content__body__competences__details li"
            )
            vacancy_detail["Competences"] = [
                competence.text.strip() for competence in competences
            ]

            # Extracting the offer details
            offer_details = soup.select(
                ".vacancy-detail__content__body__offer__details li"
            )
            vacancy_detail["Offer"] = [offer.text.strip() for offer in offer_details]

            # Add the webpage and followup number
            vacancy_detail["Webpage"] = driver.current_url
            vacancy_detail["Followup_Number"] = followup_number

            # Get the final part of the URL
            parsed_url = urlparse(driver.current_url)
            vacancy_detail["Vacancy_Id"] = os.path.basename(parsed_url.path)

            # Add the full URL of the webpage
            vacancy_detail["Full_URL"] = driver.current_url

            # Concatenate all the vacancy details into a single string
            vacancy_detail[
                "Vacancy"
            ] = f"Position: {vacancy_detail['Position']}\nLocation: {vacancy_detail['Location']}\nDescription: {vacancy_detail['Description']}\nProfile: {' '.join(vacancy_detail['Profile'])}\nCompetences: {' '.join(vacancy_detail['Competences'])}\nOffer: {' '.join(vacancy_detail['Offer'])}"

            # Add the entire dictionary as a JSON string to a new key "Vacancy_JSON"
            vacancy_detail["Vacancy_JSON"] = json.dumps(vacancy_detail)

            # Increment the followup number
            followup_number += 1

            # Print the vacancy detail, page number and follow-up number
            print(f"Page Number: {page_number}, Follow-up Number: {followup_number}")
            print(vacancy_detail)

            # Append the vacancy detail to the CSV file
            df = pd.DataFrame([vacancy_detail])
            df.to_csv(
                csv_file, mode="a", header=not os.path.exists(csv_file), index=False
            )

            # Go back to the list page
            driver.back()
            time.sleep(5)

        # Go to the next page
        page_number += 1

    except WebDriverException as e:
        print(
            f"WebDriverException occurred: {e}. Restarting the browser and waiting for 1 minute before trying the next page."
        )
        driver.quit()
        time.sleep(60)
        page_number += 1

    except Exception as e:
        print(
            f"Exception occurred: {e}. Waiting for 1 minute before trying the next page."
        )
        time.sleep(60)
        page_number += 1

# Close the driver
driver.quit()