How to process large files efficiently with generators in Python without memory issues?

I’m working on a data processing pipeline in Python that needs to handle very large log files (several GBs). I want to avoid loading the entire file into memory, so I’m trying to use generators to process the file line-by-line.

Here’s a simplified version of what I’m doing:

def read_large_file(file_path):
    with open(file_path, 'r') as f:
        for line in f:
            yield process_line(line)

def process_line(line):
    # some complex processing logic here
    return line.strip()

for processed in read_large_file('huge_log.txt'):
    # write to output or further process
    pass

My questions are:

1. Is this the most memory-efficient way to handle large files in Python?

2. Would using mmap or Path(file).open() provide any performance benefit over a standard open() call?

3. Are there any Pythonic patterns or third-party libraries that better support this kind of stream processing with low overhead?

Would appreciate any advice on best practices for large-file processing in real-world scenarios.