Quaithe empowers you to execute multiple commands in parallel for blazing-fast performance.
🏗️ Installation
📚 Use Cases
⛏️ Usage
🔧 How it works?
git clone https://github.com/devanshbatham/Quaithe
cd Quaithe
chmod +x setup.sh
./setup.shSuppose you have a list of domain names in a file called domains.txt, and you want to run the subfinder tool on each domain to find subdomains. However, let's assume subfinder is a single-threaded tool, which means that running it on each domain one at a time can be slow and inefficient. You can use the Quaithe tool to execute subfinder on multiple domains in parallel, which can speed up the process significantly.
Here's an example command that demonstrates how to use Quaithe to run subfinder on each domain in parallel:
xargs -I {} -a domains.txt echo "subfinder -d {} -o {}.txt" | quaithe -workers 30 -silentIn this command, xargs reads each domain name from the domains.txt file and passes it to the echo command as an argument. The echo command then outputs a command string that runs subfinder on the domain and saves the output to a file with the same name as the domain.
The output of echo is then piped to quaithe, which runs each command in parallel with a maximum of 30 worker processes (-workers 30).
By using Quaithe to run subfinder on each domain in parallel, you can significantly speed up the process of finding subdomains and make better use of your system's resources.
The Quaithe tool takes a list of commands to execute on standard input (stdin). Each command should be on a separate line.
cat commands.txt | quaithe -workers 10 -silentIn this command, cat reads a list of commands from a file called commands.txt and passes them to Quaithe on standard input. Quaithe runs each command in parallel with a maximum of 10 worker processes (-workers 10). The -silent flag tells Quaithe not to print the output of each command to the console.
Note that each command should be a complete shell command, including any arguments or options.
Quaithe utilizes the concurrent.futures module in Python to execute multiple commands in parallel. It creates a thread pool with a configurable number of worker processes and submits each command to the thread pool as a separate task. The thread pool manages the execution of each task, and the progress bar displays the status of each task as it executes.