Why not always use psyco for Python code?

Question

psyco seems to be quite helpful in optimizing Python code, and it does it in a very non-intrusive way.

Therefore, one has to wonder. Assuming you're always on a x86 architecture (which is where most apps run these days), why not just always use psyco for all Python code? Does it make mistakes sometimes and ruins the correctness of the program? Increases the runtime for some weird cases?

Have you had any negative experiences with it? My most negative experience so far was that it made my code faster by only 15%. Usually it's better.

Naturally, using psyco is not a replacement for efficient algorithms and coding. But if you can improve the performance of your code for the cost of two lines (importing and calling psyco), I see no good reason not to.

Answer 1

1) The memory overhead is the main one, as described in other answers. You also pay the compilation cost, which can be prohibitive if you aren't selective. From the user reference:

Compiling everything is often overkill for medium- or large-sized applications. The drawbacks of compiling too much are in the time spent compiling, plus the amount of memory that this process consumes. It is a subtle balance to keep.

2) Performance can actually be harmed by Psyco compilation. Again from the user guide ("known bugs" section):

There are also performance bugs: situations in which Psyco slows down the code instead of accelerating it. It is difficult to make a complete list of the possible reasons, but here are a few common ones:

• The built-in map and filter functions must be avoided and replaced by list comprehension. For example, map(lambda x: x*x, lst) should be replaced by the more readable but more recent syntax [x*x for x in lst].
• The compilation of regular expressions doesn't seem to benefit from Psyco. (The execution of regular expressions is unaffected, since it is C code.) Don't enable Psyco on this module; if necessary, disable it explicitely, e.g. by calling psyco.cannotcompile(re.compile).

3) Finally, there are some relatively obscure situations where using Psyco will actually introduce bugs. Some of them are listed here.

Answer 2

Psyco currently uses a lot of memory. It only runs on Intel 386-compatible processors (under any OS) right now. There are some subtle semantic differences (i.e. bugs) with the way Python works; they should not be apparent in most programs.

See also the caveats section. For a hard example, I noticed that my web app with Cheetah-generated templates and DB I/O gained no appreciable speedup.