IP | Country | PORT | ADDED |
---|---|---|---|
50.223.246.239 | us | 80 | 51 minutes ago |
50.149.13.195 | us | 80 | 51 minutes ago |
50.172.150.134 | us | 80 | 51 minutes ago |
50.175.212.74 | us | 80 | 51 minutes ago |
50.171.187.52 | us | 80 | 51 minutes ago |
67.43.236.19 | ca | 17929 | 51 minutes ago |
128.140.113.110 | de | 3128 | 51 minutes ago |
50.219.249.54 | us | 80 | 51 minutes ago |
50.172.39.98 | us | 80 | 51 minutes ago |
50.149.13.197 | us | 80 | 51 minutes ago |
50.232.104.86 | us | 80 | 51 minutes ago |
50.223.246.238 | us | 80 | 51 minutes ago |
50.219.249.62 | us | 80 | 51 minutes ago |
103.24.4.23 | sg | 3128 | 51 minutes ago |
67.43.228.250 | ca | 8209 | 51 minutes ago |
50.171.187.50 | us | 80 | 51 minutes ago |
189.202.188.149 | mx | 80 | 51 minutes ago |
50.171.187.53 | us | 80 | 51 minutes ago |
50.223.246.226 | us | 80 | 51 minutes ago |
50.171.122.28 | us | 80 | 51 minutes ago |
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Parsing math expressions correctly involves converting mathematical expressions from their human-readable form into a format that a computer can understand and evaluate. A common approach is to use a parser or library designed for mathematical expressions.
In Python, you can use the sympy library, which provides powerful symbolic mathematics capabilities, including expression parsing and evaluation. Here's an example:
from sympy import sympify, symbols
# Define symbols
x, y = symbols('x y')
# Parse math expressions
expression1 = sympify("2*x + 3*y")
expression2 = sympify("sin(x) + cos(x)")
# Evaluate expressions
result1 = expression1.subs({x: 1, y: 2})
result2 = expression2.subs(x, 0)
print("Result 1:", result1)
print("Result 2:", result2)
In this example, sympify is used to parse the mathematical expressions. You can then substitute values for variables using the subs method.
If you need a more general-purpose parser, you can use the pyparsing library. Here's a basic example:
from pyparsing import Word, nums, operatorPrecedence, opAssoc
# Define grammar for basic math expressions
integer = Word(nums).setParseAction(lambda t: int(t[0]))
variable = Word("xy")
operand = integer | variable
expr = operatorPrecedence(
operand,
[
("+", 2, opAssoc.LEFT),
("-", 2, opAssoc.LEFT),
("*", 3, opAssoc.LEFT),
("/", 3, opAssoc.LEFT),
],
)
# Parse math expressions
expression1 = expr.parseString("2*x + 3*y")
expression2 = expr.parseString("sin(x) + cos(x)")
print("Parsed Expression 1:", expression1)
print("Parsed Expression 2:", expression2)
This example uses pyparsing to define a grammar for basic math expressions with addition, subtraction, multiplication, and division. You can customize the grammar based on your specific needs.
Choose the library that best fits your requirements, whether it's for symbolic mathematics (like sympy) or general-purpose expression parsing (like pyparsing). Always consider error handling and validation when working with user-inputted expressions.
To implement a constant scraping process, you can use a combination of a loop and a delay to periodically scrape data from a website. This process is often referred to as "web scraping with intervals" or "periodic scraping." Here's an example using Node.js and the axios library for making HTTP requests
Install Dependencies
Install the required npm packages:
npm install axios
Write the Scraping Script
Create a Node.js script (e.g., constant_scraping.js) with the following code:
const axios = require('axios');
async function scrapeData() {
try {
// Replace with your scraping logic
const response = await axios.get('https://example.com'); // Replace with the URL you want to scrape
console.log('Scraped data:', response.data);
// Add additional scraping logic as needed
// ...
} catch (error) {
console.error('Error during scraping:', error.message);
}
}
// Function to perform constant scraping with a specified interval
async function constantScraping(interval) {
while (true) {
await scrapeData();
await sleep(interval); // Sleep for the specified interval before the next scrape
}
}
// Function to introduce a delay using setTimeout
function sleep(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
// Set the interval (in milliseconds) for constant scraping
const scrapingInterval = 60000; // 60 seconds
// Start the constant scraping process
constantScraping(scrapingInterval);
Replace 'https://example.com' with the URL you want to scrape.
Adjust the scraping logic within the scrapeData function to meet your specific requirements.
Run the Script:
Run the script using Node.js:
node constant_scraping.js
This script defines a constantScraping function that continuously calls the scrapeData function at a specified interval using a loop and the sleep function. Adjust the interval (scrapingInterval) based on your scraping needs.
Create the first profile by specifying its name and selecting the desired configuration. The configuration is a non-repeating combination of different versions of the operating system and browser. After setting the language, open the "Network" tab and select the type of proxy (socks5 or https). Now it remains only to fill in the data in the highlighted fields to complete the installation of the proxy.
You need to go to "Settings", click on "WiFi", select the current network to which the smartphone is connected, tap on "Proxy settings". And then - deactivate the item.
To enable proxies in your MacBook, you need to go to "System Preferences" (from the "Apple" menu), then open "Network", then - specify the type of connection you are using. Then select "Advanced Settings" (can be named as "Advanced"), then click on "Proxy". And then - either set the parameters manually, or specify a configuration file.
What else…