1
0
forked from VimPlug/jedi
Files
jedi-fork/jedi/cache.py
2013-01-08 13:02:06 +01:00

147 lines
4.5 KiB
Python

import time
import settings
# memoize caches will be deleted after every action
memoize_caches = []
time_caches = []
star_import_cache = {}
# for fast_parser, should not be deleted
parser_cache = {}
# should also not be deleted
module_cache = {}
def clear_caches(delete_all=False):
""" Jedi caches many things, that should be completed after each completion
finishes.
:param delete_all: Deletes also the cache that is normally not deleted,
like parser cache, which is important for faster parsing.
"""
global memoize_caches, time_caches
# memorize_caches must never be deleted, because the dicts will get lost in
# the wrappers.
for m in memoize_caches:
m.clear()
if delete_all:
time_caches = []
star_import_cache.clear()
parser_cache.clear()
module_cache.clear()
else:
# normally just kill the expired entries, not all
for tc in time_caches:
# check time_cache for expired entries
for key, (t, value) in list(tc.items()):
if t < time.time():
# delete expired entries
del tc[key]
def memoize_default(default=None, cache=memoize_caches):
""" This is a typical memoization decorator, BUT there is one difference:
To prevent recursion it sets defaults.
Preventing recursion is in this case the much bigger use than speed. I
don't think, that there is a big speed difference, but there are many cases
where recursion could happen (think about a = b; b = a).
"""
def func(function):
memo = {}
cache.append(memo)
def wrapper(*args, **kwargs):
key = (args, frozenset(kwargs.items()))
if key in memo:
return memo[key]
else:
memo[key] = default
rv = function(*args, **kwargs)
memo[key] = rv
return rv
return wrapper
return func
class CachedMetaClass(type):
""" This is basically almost the same than the decorator above, it just
caches class initializations. I haven't found any other way, so I do it
with meta classes.
"""
@memoize_default()
def __call__(self, *args, **kwargs):
return super(CachedMetaClass, self).__call__(*args, **kwargs)
def time_cache(time_add_setting):
""" This decorator works as follows: Call it with a setting and after that
use the function with a callable that returns the key.
But: This function is only called if the key is not available. After a
certain amount of time (`time_add_setting`) the cache is invalid.
"""
def _temp(key_func):
dct = {}
time_caches.append(dct)
def wrapper(optional_callable, *args, **kwargs):
key = key_func(*args, **kwargs)
value = None
if key in dct:
expiry, value = dct[key]
if expiry > time.time():
return value
value = optional_callable()
time_add = getattr(settings, time_add_setting)
if key is not None:
dct[key] = time.time() + time_add, value
return value
return wrapper
return _temp
@time_cache("get_in_function_call_validity")
def cache_get_in_function_call(stmt):
module_path = stmt.get_parent_until().path
return None if module_path is None else (module_path, stmt.start_pos)
def cache_star_import(func):
def wrapper(scope, *args, **kwargs):
try:
mods = star_import_cache[scope]
if mods[0] + settings.star_import_cache_validity > time.time():
return mods[1]
except KeyError:
pass
# cache is too old and therefore invalid or not available
invalidate_star_import_cache(scope)
mods = func(scope, *args, **kwargs)
star_import_cache[scope] = time.time(), mods
return mods
return wrapper
def invalidate_star_import_cache(module, only_main=False):
""" Important if some new modules are being reparsed """
try:
t, mods = star_import_cache[module]
del star_import_cache[module]
for m in mods:
invalidate_star_import_cache(m, only_main=True)
except KeyError:
pass
if not only_main:
# We need a list here because otherwise the list is being changed
# during the iteration in py3k: iteritems -> items.
for key, (t, mods) in list(star_import_cache.items()):
if module in mods:
invalidate_star_import_cache(key)