Eating memory in Python the easy way

July 15, 2015

As a system administrator, every so often I need to put a machine under the stress of having a lot of its memory used. Sometimes this is for testing how things respond to this before it happens during live usage; sometimes this is because putting a system under memory stress can cause it to do important things it doesn't otherwise do (such as reclaim extra memory). The traditional way to do this is with a memory eater program, something that just allocates a controlled amount of memory and then (usually) puts actual data in it.

(If you merely allocate memory but don't use it, many systems don't consider themselves to be under memory stress. Generally you have to make them use up actual RAM.)

In the old days, memory eater programs tended to be one-off things written in C; you'd malloc() some amount of memory then carefully write data into it to force the system to give you RAM. People who needed this regularly might keep around a somewhat more general program for it. As it turns out, these days I don't need to go to all of that work because interactive Python will do just fine:

$ /usr/bin/amd64/python2.6
>>> GB = 1024*1024*1024
>>> a = "a" * (10 * GB)

Voila, 10 GB eaten. Doing this interactively gives me great flexibility; for instance, I can easily eat memory in smaller chunks, say 1 GB at a time, so that I have more control over exactly when the system gets pushed hard (instead of perhaps throwing it well out of its comfort zone all at once).

There are some minor quibbles you can make here; for example I'm not using only exactly 10 GB of memory, since Python has some small overhead for objects and so on. And you probably want to specifically use bytestrings in Python 3, not the default Unicode strings.

In practice I don't care about the quibbles because this is close enough for me and it's really convenient (and flexible), far more so than writing a C program or re-finding the last one I wrote for this.

(If CPython allocates much additional internal memory to create this 10 GB string, it's not enough to be visible on the scale of GBytes of RAM usage. I tried a smaller test and didn't see more than perhaps a megabyte or two of surprising memory usage, but in general if you need really fine control over memory eating you're not going to want to use Python for it.)

PS: It makes me unreasonably happy to able to use Python interactively for things like this, especially when they're things I might have had to write a C program for in the past. It's just so neat to be able to just type this stuff out on the fly, whether it's eating memory or testing UDP behavior.

Written on 15 July 2015.
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Last modified: Wed Jul 15 23:01:16 2015
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