The short version is: The efficient way to use readlines() is to not use it. Ever.
I read some doc notes on
readlines(), where people has claimed that thisreadlines()reads whole file content into memory and hence generally consumes more memory compared to readline() or read().
The documentation for readlines() explicitly guarantees that it reads the whole file into memory, and parses it into lines, and builds a list full of strings out of those lines.
But the documentation for read() likewise guarantees that it reads the whole file into memory, and builds a string, so that doesn't help.
On top of using more memory, this also means you can't do any work until the whole thing is read. If you alternate reading and processing in even the most naive way, you will benefit from at least some pipelining (thanks to the OS disk cache, DMA, CPU pipeline, etc.), so you will be working on one batch while the next batch is being read. But if you force the computer to read the whole file in, then parse the whole file, then run your code, you only get one region of overlapping work for the entire file, instead of one region of overlapping work per read.
You can work around this in three ways:
readlines(sizehint), read(size), or readline().mmap the file, which allows you to treat it as a giant string without first reading it in.For example, this has to read all of foo at once:
with open('foo') as f:
lines = f.readlines()
for line in lines:
pass
But this only reads about 8K at a time:
with open('foo') as f:
while True:
lines = f.readlines(8192)
if not lines:
break
for line in lines:
pass
And this only reads one line at a time—although Python is allowed to (and will) pick a nice buffer size to make things faster.
with open('foo') as f:
while True:
line = f.readline()
if not line:
break
pass
And this will do the exact same thing as the previous:
with open('foo') as f:
for line in f:
pass
Meanwhile:
but should the garbage collector automatically clear that loaded content from memory at the end of my loop, hence at any instant my memory should have only the contents of my currently processed file right ?
Python doesn't make any such guarantees about garbage collection.
The CPython implementation happens to use refcounting for GC, which means that in your code, as soon as file_content gets rebound or goes away, the giant list of strings, and all of the strings within it, will be freed to the freelist, meaning the same memory can be reused again for your next pass.
However, all those allocations, copies, and deallocations aren't free—it's much faster to not do them than to do them.
On top of that, having your strings scattered across a large swath of memory instead of reusing the same small chunk of memory over and over hurts your cache behavior.
Plus, while the memory usage may be constant (or, rather, linear in the size of your largest file, rather than in the sum of your file sizes), that rush of mallocs to expand it the first time will be one of the slowest things you do (which also makes it much harder to do performance comparisons).
Putting it all together, here's how I'd write your program:
for filename in os.listdir(input_dir):
with open(filename, 'rb') as f:
if filename.endswith(".gz"):
f = gzip.open(fileobj=f)
words = (line.split(delimiter) for line in f)
... my logic ...
Or, maybe:
for filename in os.listdir(input_dir):
if filename.endswith(".gz"):
f = gzip.open(filename, 'rb')
else:
f = open(filename, 'rb')
with contextlib.closing(f):
words = (line.split(delimiter) for line in f)
... my logic ...