Read File In Chunks - RAM-usage, Reading Strings From Binary Files

I'd like to understand the difference in RAM-usage of this methods when reading a large file in python. Version 1, found here on stackoverflow: def read_in_chunks(file_object, chun

Solution 1:

yield is the keyword in python used for generator expressions. That means that the next time the function is called (or iterated on), the execution will start back up at the exact point it left off last time you called it. The two functions behave identically; the only difference is that the first one uses a tiny bit more call stack space than the second. However, the first one is far more reusable, so from a program design standpoint, the first one is actually better.

EDIT: Also, one other difference is that the first one will stop reading once all the data has been read, the way it should, but the second one will only stop once either f.read() or process_data() throws an exception. In order to have the second one work properly, you need to modify it like so:

f = open(file, 'rb')
while True:
    piece = f.read(1024)  
    if not piece:
        break
    process_data(piece)
f.close()

Solution 2:

starting from python 3.8 you might also use an assignment expression (the walrus-operator):

with open('file.name', 'rb') as file:
    while chunk := file.read(1024):
        process_data(chunk)

the last chunk may be smaller than CHUNK_SIZE.

as read() will return b"" when the file has been read the while loop will terminate.

Solution 3:

I think probably the best and most idiomatic way to do this would be to use the built-in iter() function along with its optional sentinel argument to create and use an iterable as shown below. Note that the last chunk might be less that the requested chunk size if the file size isn't an exact multiple of it.

from functools import partial

CHUNK_SIZE = 1024
filename = 'testfile.dat'

with open(filename, 'rb') as file:
    for chunk in iter(partial(file.read, CHUNK_SIZE), b''):
        process_data(chunk)

Update: Don't know when it was added, but almost exactly what's above is in now shown as an example in the official documentation of the iter() function.