A quick and easy to use python caching system.
You can install quick_cache via
pip install --user quick_cacheand import it in python using:
from quick_cache import QuickCacheCreate the cache object as follows:
def msg(message, *args, **kwargs):
print(message.format(*args, **kwargs), file=sys.stderr)
cache = QuickCache(base_file, quota=500, ram_quota=100, warnings=msg)where base_file is an optional file whose content invalidates the
cache (ie., when the content of the file changes the cache is
invalidated; for large files it might be desirable to use the mtime in
the cache object below) and msg is an optional formatting function
that prints warnings (by default it's None which doesn't print
anything; warnings are emitted when the actual computation is faster
than reading the results from the cache or if other exceptional
situations occur). quota and ram_quota are optional maximal
cache sizes, both in RAM and on disk, in MB.
The caching functionality can then be used via:
with cache.get_hnd({
# object identifying the task to cache
# can be any combination of keys and values
"param_a": 5,
"input_file_c": os.path.getmtime(input_file_c), # for file change time
...
}) as hnd:
if not hnd.has():
res = hnd.write(do_compute()) # compute your result here
else:
res = hnd.read()
# your result is in resThe cache object used for creating the handle uniquely defines the task. The object should contain all parameters of the task and the task computation itself should be deterministic.