Loading large files into memory can be a challenging task, as it can quickly consume all the available memory and cause the program to crash. To avoid this issue, you can use iterators in Python to process large files in smaller chunks.

An iterator is an object that can be iterated (looped) upon, meaning that you can traverse through its elements one by one. The iter() function in Python takes an iterable object and returns an iterator. The iterator's __next__() method returns the next value from the iterable, and it raises the StopIteration exception when there are no more elements to return.

Here's an example of how you can use an iterator to read a large file in smaller chunks:

with open('large_file.txt') as f:
    while True:
        chunk = f.read(1024)  # Read 1024 bytes at a time
        if not chunk:  # Break when no more bytes are left to read
            break
        # Do something with the chunk

In this example, we open the file using the with statement, which automatically closes the file after the block of code is executed. We then use a while loop to read the file in chunks of 1024 bytes at a time. When there are no more bytes left to read, the read() method returns an empty string, which evaluates to False and breaks out of the loop.

You can modify the chunk size based on your available memory and the size of the file you're reading. By processing the file in smaller chunks, you can avoid consuming too much memory and handle large files efficiently.