logging — Logging facility for Python

Python Sub-Processes

Sub-processes are independent processes that are spawned by the main process. In Python, the subprocess module is used to spawn new processes, connect to their input/output/error pipes, and obtain their return codes.

Using sub-processes in Python can be helpful when you want to execute a command-line tool or program from your Python script. This can be done by calling the subprocess.run() function, which runs a command with arguments and waits for it to complete.

For example, if you want to run the ls command in a Unix-like system from your Python script, you can do it like this:

import subprocess

result = subprocess.run(['ls', '-la'], stdout=subprocess.PIPE)
print(result.stdout)

This will run the ls -la command and print its output to the console.

Additionally, you can use the subprocess.Popen() function to spawn a new process and connect to its pipes without waiting for it to complete. This is useful when you need to run multiple processes simultaneously.

For example, if you want to run two commands in parallel and get their output, you can do it like this:

import subprocess

p1 = subprocess.Popen(['ls', '-la'], stdout=subprocess.PIPE)
p2 = subprocess.Popen(['ps', '-ef'], stdout=subprocess.PIPE)

output1, _ = p1.communicate()
output2, _ = p2.communicate()

print(output1)
print(output2)

This will run the ls -la and ps -ef commands in parallel and print their output to the console.

It is also possible to control the sub-processes through the subprocess module. For example, you can send input to the sub-processes, read their output, and terminate them if necessary.

Overall, sub-processes in Python provide a powerful way to interact with external processes and manage them from within a Python script.

When To Use Sub-Processes

There are several situations in which sub-processes can be helpful when coding programs in Python:

1. Running external programs or commands: Sub-processes can be used to execute external tools or programs from within a Python script. This is particularly useful when you need to leverage the functionality of an external program in your Python code.
2. Performing I/O operations: Sub-processes can be used to perform I/O operations that may block the main thread of your program. This can help reduce the amount of time your program spends waiting for I/O operations to complete.
3. Parallel processing: Sub-processes can be used to run multiple tasks in parallel. This can be useful when you need to perform several computations at the same time.
4. Running long tasks: Sub-processes can be used to run long tasks that may consume a lot of resources or take a long time to complete. By running these tasks in a separate process, you can ensure that your main program remains responsive.

Overall, sub-processes can be helpful when you need to perform tasks that may block the main thread of your program or when you need to run external programs or commands from within a Python script.