ازگر کے ساتھ کریگ لسٹ کو کھرچنے کے لئے رہنما

pip install beautifulsoup4
pip install requests

import requests

# List of Craigslist URLs to scrape
urls = [
    "link",
    "link"
]

for url in urls:
    # Send a GET request to the URL
    response = requests.get(url)
    
    # Check if the request was successful (status code 200)
    if response.status_code == 200:
        # Extract HTML content from the response
        html_content = response.text
        
    else:
        # If the request failed, print an error message with the status code
        print(f"Failed to retrieve {url}. Status code: {response.status_code}")

from bs4 import BeautifulSoup

# Iterate through each URL in the list
for url in urls:
    # Send a GET request to the URL
    response = requests.get(url)
    
    # Check if the request was successful (status code 200)
    if response.status_code == 200:
        # Extract HTML content from the response
        html_content = response.text
        
        # Parse the HTML content using BeautifulSoup
        soup = BeautifulSoup(html_content, 'html.parser')
        
    else:
        # If the request failed, print an error message with the status code
        print(f"Failed to retrieve {url}. Status code: {response.status_code}")

from bs4 import BeautifulSoup

# Iterate through each URL in the list
for url in urls:
    # Send a GET request to the URL
    response = requests.get(url)
    
    # Check if the request was successful (status code 200)
    if response.status_code == 200:
        # Extract HTML content from the response
        html_content = response.text
        
        # Parse the HTML content using BeautifulSoup
        soup = BeautifulSoup(html_content, 'html.parser')
        
        # Extracting specific data points
        # Find the title of the listing
        title = soup.find('span', id='titletextonly').text.strip()
        
        # Find the price of the listing
        price = soup.find('span', class_='price').text.strip()
        
        # Find the description of the listing (may contain multiple paragraphs)
        description = soup.find('section', id='postingbody').find_all(text=True, recursive=False)
        
        # Print extracted data (for demonstration purposes)
        print(f"Title: {title}")
        print(f"Price: {price}")
        print(f"Description: {description}")
        
    else:
        # If the request fails, print an error message with the status code
        print(f"Failed to retrieve {url}. Status code: {response.status_code}")

import csv

# Define the CSV file path and field names
csv_file = 'craigslist_data.csv'
fieldnames = ['Title', 'Price', 'Description']

# Writing data to CSV file
try:
    # Open the CSV file in write mode with UTF-8 encoding
    with open(csv_file, mode='w', newline='', encoding='utf-8') as file:
        # Create a CSV DictWriter object with the specified fieldnames
        writer = csv.DictWriter(file, fieldnames=fieldnames)
        
        # Write the header row in the CSV file
        writer.writeheader()
        
        # Iterate through each item in the scraped_data list
        for item in scraped_data:
            # Write each item as a row in the CSV file
            writer.writerow(item)
        
    # Print a success message after writing data to the CSV file
    print(f"Data saved to {csv_file}")

except IOError:
    # Print an error message if an IOError occurs while writing to the CSV file
    print(f"Error occurred while writing data to {csv_file}")

proxies = {
    'http': 'http://your_proxy_ip:your_proxy_port',
    'https': 'https://your_proxy_ip:your_proxy_port'
}

response = requests.get(url, proxies=proxies)

import random

user_agents = [
    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
    # Add more user agents as needed
]

headers = {
    'User-Agent': random.choice(user_agents)
}

response = requests.get(url, headers=headers)

import requests
import urllib3
from bs4 import BeautifulSoup
import csv
import random
import ssl

ssl._create_default_https_context = ssl._create_stdlib_context
urllib3.disable_warnings()


# List of Craigslist URLs to scrape
urls = [
    "link",
    "link"
]

# User agents and proxies
user_agents = [
    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
    'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
]

proxies = [
    {'http': 'http://your_proxy_ip1:your_proxy_port1', 'https': 'https://your_proxy_ip1:your_proxy_port1'},
    {'http': 'http://your_proxy_ip2:your_proxy_port2', 'https': 'https://your_proxy_ip2:your_proxy_port2'},
]

# List to store scraped data
scraped_data = []

# Loop through each URL in the list
for url in urls:
    # Rotate user agent for each request to avoid detection
    headers = {
        'User-Agent': random.choice(user_agents)
    }

    # Use a different proxy for each request to avoid IP blocking
    proxy = random.choice(proxies)

    try:
        # Send GET request to the Craigslist URL with headers and proxy
        response = requests.get(url, headers=headers, proxies=proxy, timeout=30, verify=False)
        
        # Check if the request was successful (status code 200)
        if response.status_code == 200:
            # Parse HTML content of the response
            html_content = response.text
            soup = BeautifulSoup(html_content, 'html.parser')

            # Extract data from the parsed HTML
            title = soup.find('span', id='titletextonly').text.strip()
            price = soup.find('span', class_='price').text.strip()
            description = soup.find('section', id='postingbody').get_text(strip=True, separator='\n')  # Extracting description

            # Append scraped data as a dictionary to the list
            scraped_data.append({'Title': title, 'Price': price, 'Description': description})
            print(f"Data scraped for {url}")
        else:
            # Print error message if request fails
            print(f"Failed to retrieve {url}. Status code: {response.status_code}")
    except Exception as e:
        # Print exception message if an error occurs during scraping
        print(f"Exception occurred while scraping {url}: {str(e)}")

# CSV file setup for storing scraped data
csv_file = 'craigslist_data.csv'
fieldnames = ['Title', 'Price', 'Description']

# Writing scraped data to CSV file
try:
    with open(csv_file, mode='w', newline='', encoding='utf-8') as file:
        writer = csv.DictWriter(file, fieldnames=fieldnames)

        # Write header row in the CSV file
        writer.writeheader()

        # Iterate through scraped_data list and write each item to the CSV file
        for item in scraped_data:
            writer.writerow(item)

    # Print success message if data is saved successfully
    print(f"Data saved to {csv_file}")
except IOError:
    # Print error message if there is an IOError while writing to the CSV file
    print(f"Error occurred while writing data to {csv_file}")