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ORPA-pyOpenRPA/WPy32-3720/python-3.7.2/Lib/site-packages/dask/cache.py

67 lines
2.0 KiB

from __future__ import absolute_import, division, print_function
from .callbacks import Callback
from timeit import default_timer
from numbers import Number
import sys
overhead = sys.getsizeof(1.23) * 4 + sys.getsizeof(()) * 4
class Cache(Callback):
""" Use cache for computation
Examples
--------
>>> cache = Cache(1e9) # doctest: +SKIP
The cache can be used locally as a context manager around ``compute`` or
``get`` calls:
>>> with cache: # doctest: +SKIP
... result = x.compute()
You can also register a cache globally, so that it works for all
computations:
>>> cache.register() # doctest: +SKIP
>>> cache.unregister() # doctest: +SKIP
"""
def __init__(self, cache, *args, **kwargs):
try:
import cachey
except ImportError as ex:
raise ImportError('Cache requires cachey, "{ex}" problem '
'importing'.format(ex=str(ex)))
self._nbytes = cachey.nbytes
if isinstance(cache, Number):
cache = cachey.Cache(cache, *args, **kwargs)
else:
assert not args and not kwargs
self.cache = cache
self.starttimes = dict()
def _start(self, dsk):
self.durations = dict()
overlap = set(dsk) & set(self.cache.data)
for key in overlap:
dsk[key] = self.cache.data[key]
def _pretask(self, key, dsk, state):
self.starttimes[key] = default_timer()
def _posttask(self, key, value, dsk, state, id):
duration = default_timer() - self.starttimes[key]
deps = state['dependencies'][key]
if deps:
duration += max(self.durations.get(k, 0) for k in deps)
self.durations[key] = duration
nb = self._nbytes(value) + overhead + sys.getsizeof(key) * 4
self.cache.put(key, value, cost=duration / nb / 1e9, nbytes=nb)
def _finish(self, dsk, state, errored):
self.starttimes.clear()
self.durations.clear()