Flask Proxy Server

In the upper right corner of the browser, click "Settings and Other", and then select the "Options" tab in the window that appears. Once the "General" window opens, locate the "Advanced" tab and click "Open proxy settings" in the menu that appears. Here, in the line "Use a proxy server", select "On". In the "Address" field, you must specify the IP address of the proxy, and in the "Port" field - the port of the proxy. The last thing to do is to click "Save".

In Windows 8 and later editions it is recommended to setup network proxy through Group Policy. To do this, run GPMC.msc (via "Run" or enter in the "Search"), then select the section with the users, from the list of parameters select "Internet Settings". Further settings are not different from the standard ones in Windows. You can set proxy, specify the start page, enter restrictions and so on.

When performing web scraping with authorization in Python, you typically need to simulate the login process of a user by sending the necessary authentication data (such as username and password) to the website. The exact steps depend on the authentication method used by the website, and there are several common approaches

Basic Authentication (using requests library)

If the website uses HTTP Basic Authentication, you can include the authentication credentials in the request headers using the requests library.

import requests

url = 'https://example.com/data'
username = 'your_username'
password = 'your_password'

response = requests.get(url, auth=(username, password))

if response.status_code == 200:
    # Successfully authenticated, you can now parse the content
    print(response.text)
else:
    print(f"Failed to authenticate. Status code: {response.status_code}")

Form-Based Authentication

For websites that use form-based authentication (login form), you need to send a POST request with the appropriate form data.

import requests

login_url = 'https://example.com/login'
data = {
    'username': 'your_username',
    'password': 'your_password',
}

# Use a session to persist the authentication across requests
with requests.Session() as session:
    response = session.post(login_url, data=data)

    if response.status_code == 200:
        # Authentication successful, continue with subsequent requests
        data_url = 'https://example.com/data'
        data_response = session.get(data_url)
        print(data_response.text)
    else:
        print(f"Failed to authenticate. Status code: {response.status_code}")

OAuth Authentication

For websites using OAuth, you might need to use an OAuth library like requests_oauthlib or oauthlib to handle the OAuth flow.

Handling Cookies

Sometimes, authentication is maintained using cookies. In such cases, you need to handle cookies in your requests.

import requests

login_url = 'https://example.com/login'
data = {
    'username': 'your_username',
    'password': 'your_password',
}

# Use a session to persist the authentication across requests
with requests.Session() as session:
    login_response = session.post(login_url, data=data)

    if login_response.status_code == 200:
        # Authentication successful, continue with subsequent requests
        data_url = 'https://example.com/data'
        data_response = session.get(data_url)
        print(data_response.text)
    else:
        print(f"Failed to authenticate. Status code: {login_response.status_code}")

To save the results of two Scrapy spiders into one JSON file, you can follow these general steps:

Run Both Spiders:
Run both Scrapy spiders separately to generate their respective output files. Let's assume you have two spiders named spider1 and spider2.

scrapy crawl spider1 -o output1.json
scrapy crawl spider2 -o output2.json

Merge JSON Files:
After running both spiders, you can merge the contents of the two JSON files into a single file using various methods. One way is to use a scripting language like Python.

import json

# Read the contents of both JSON files
with open('output1.json') as f1, open('output2.json') as f2:
    data1 = json.load(f1)
    data2 = json.load(f2)

# Combine the data from both spiders
combined_data = data1 + data2

# Write the combined data to a new JSON file
with open('combined_output.json', 'w') as combined_file:
    json.dump(combined_data, combined_file, indent=2)

Save this Python script (e.g., merge_json.py) in the same directory as the JSON files, and then run it:

python merge_json.py

This script reads the contents of both JSON files, combines the data, and writes the result into a new file (combined_output.json).

Verify the Result:
Check the combined_output.json file to ensure that it contains the merged data from both spiders.

A proxy pool is a database that includes addresses for multiple proxy servers. For example, each VPN service has one. And it "distributes" them in order to the connected users.