""" This caching is very important for speed and memory optimizations. There's nothing really spectacular, just some decorators. The following cache types are available: - module caching (`load_parser` and `save_parser`), which uses pickle and is really important to assure low load times of modules like ``numpy``. - ``time_cache`` can be used to cache something for just a limited time span, which can be useful if there's user interaction and the user cannot react faster than a certain time. This module is one of the reasons why |jedi| is not thread-safe. As you can see there are global variables, which are holding the cache information. Some of these variables are being cleaned after every API usage. """ import time from jedi import settings from jedi.parser.utils import parser_cache from jedi.parser.utils import underscore_memoization _time_caches = {} def clear_time_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 _time_caches if delete_all: for cache in _time_caches.values(): cache.clear() parser_cache.clear() else: # normally just kill the expired entries, not all for tc in _time_caches.values(): # 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 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. If the given key is None, the function will not be cached. """ def _temp(key_func): dct = {} _time_caches[time_add_setting] = dct def wrapper(*args, **kwargs): generator = key_func(*args, **kwargs) key = next(generator) try: expiry, value = dct[key] if expiry > time.time(): return value except KeyError: pass value = next(generator) 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 def memoize_method(method): """A normal memoize function.""" def wrapper(self, *args, **kwargs): dct = self.__dict__.setdefault('_memoize_method_dct', {}) key = (args, frozenset(kwargs.items())) try: return dct[key] except KeyError: result = method(self, *args, **kwargs) dct[key] = result return result return wrapper def memoize_function(obj): """ A normal memoize function for memoizing free functions. """ cache = obj.cache = {} def memoizer(*args, **kwargs): key = str(args) + str(kwargs) if key not in cache: cache[key] = obj(*args, **kwargs) return cache[key] return memoizer def cache_star_import(func): @time_cache("star_import_cache_validity") def wrapper(self): yield self.base # The cache key yield func(self) return wrapper def _invalidate_star_import_cache_module(module, only_main=False): """ Important if some new modules are being reparsed """ try: t, modules = _time_caches['star_import_cache_validity'][module] except KeyError: pass else: del _time_caches['star_import_cache_validity'][module] # This stuff was part of load_parser. However since we're most likely # not going to use star import caching anymore, just ignore it. #else: # In case there is already a module cached and this module # has to be reparsed, we also need to invalidate the import # caches. # _invalidate_star_import_cache_module(parser_cache_item.parser.module) def invalidate_star_import_cache(path): """On success returns True.""" try: parser_cache_item = parser_cache[path] except KeyError: pass else: _invalidate_star_import_cache_module(parser_cache_item.parser.module)