What is the maximum number of concurrent requests that Goutte can handle?

Goutte is a screen scraping and web crawling library for PHP. It provides a nice API to crawl websites and extract data from the HTML/XML responses. Goutte itself is a wrapper around Guzzle, Symfony's BrowserKit, and DomCrawler components.

Goutte does not inherently provide concurrent requests functionality. It operates synchronously, which means it sends HTTP requests one after the other. If you want to handle multiple concurrent requests, you would typically integrate Goutte with Guzzle's asynchronous requests capabilities or use a multi-threading or multi-process approach in PHP (though PHP isn't traditionally the best language for this due to its single-threaded nature).

However, since you might be interested in sending concurrent requests, you can extend Goutte with Guzzle's Promises. Guzzle, the underlying HTTP client used by Goutte, supports concurrent requests using Promises and asynchronous requests.

Here's an example of how you could send concurrent requests with Guzzle, which you could integrate with Goutte for scraping tasks:

require 'vendor/autoload.php';

use GuzzleHttp\Client;
use GuzzleHttp\Promise;

$client = new Client();

// Initiate each request but do not block
$promises = [
    'image' => $client->getAsync('http://httpbin.org/image'),
    'png'   => $client->getAsync('http://httpbin.org/image/png'),
    'jpeg'  => $client->getAsync('http://httpbin.org/image/jpeg'),
    'webp'  => $client->getAsync('http://httpbin.org/image/webp')
];

// Wait on all of the requests to complete.
$results = Promise\Utils::unwrap($promises);

// You can access each result using the key provided in the promises array
$imageResponse = $results['image'];
$pngResponse = $results['png'];
// ...

// Parse the responses or pass them to Goutte for further processing.

Keep in mind that the number of concurrent requests you can handle effectively will depend on the resources available on the server running the PHP code and the limitations set by the target website (e.g., rate limits). It's important to respect the target website's terms of service and robots.txt file to avoid being blocked or banned due to abusive behavior.

In addition, when dealing with concurrent requests, you should be aware of the potential impact on the server you are scraping from. Sending too many requests in a short period of time can overload the server, which might be considered a denial-of-service attack.

If you are looking for high concurrency and parallel processing in web scraping, you might want to consider using a language and framework designed for concurrency, such as Python with the asyncio library or Node.js, which is inherently good at handling asynchronous operations.