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import sys
import threading
from random import random
from funcy import select_keys, cached_property, once, once_per, monkey, wraps, walk, chain
from funcy import lmap, lcat, join_with
from django.utils.encoding import force_str
from django.core.exceptions import ImproperlyConfigured, EmptyResultSet
from django.db import DEFAULT_DB_ALIAS, connections, models
from django.db.models.manager import BaseManager
from django.db.models.query import MAX_GET_RESULTS
from django.db.models.signals import pre_save, post_save, post_delete, m2m_changed
from django.db.transaction import atomic
from .conf import model_profile, settings, ALL_OPS
from .utils import monkey_mix, stamp_fields, get_cache_key, cached_view_fab, family_has_profile
from .utils import md5
from .getset import cache_thing, getting
from .sharding import get_prefix
from .tree import dnfs
from .invalidation import invalidate_obj, invalidate_dict, skip_on_no_invalidation
from .transaction import transaction_states
from .signals import cache_read
__all__ = ('cached_as', 'cached_view_as', 'install_cacheops')
_local_get_cache = {}
def cached_as(*samples, timeout=None, extra=None, lock=None, keep_fresh=False):
"""
Caches results of a function and invalidates them same way as given queryset(s).
NOTE: Ignores queryset cached ops settings, always caches.
If keep_fresh is True, this will prevent caching if the given querysets are
invalidated during the function call. This prevents prolonged caching of
stale data.
"""
if not samples:
raise TypeError('Pass a queryset, a model or an object to cache like')
# If we unexpectedly get list instead of queryset return identity decorator.
# Paginator could do this when page.object_list is empty.
if len(samples) == 1 and isinstance(samples[0], list):
return lambda func: func
def _get_queryset(sample):
if isinstance(sample, models.Model):
queryset = sample.__class__.objects.filter(pk=sample.pk)
elif isinstance(sample, type) and issubclass(sample, models.Model):
queryset = sample.objects.all()
else:
queryset = sample
queryset._require_cacheprofile()
return queryset
querysets = lmap(_get_queryset, samples)
dbs = list({qs.db for qs in querysets})
cond_dnfs = join_with(lcat, map(dnfs, querysets)) # TODO: use cached version?
qs_keys = [qs._cache_key(prefix=False) for qs in querysets]
if timeout is None:
timeout = min(qs._cacheprofile['timeout'] for qs in querysets)
if lock is None:
lock = any(qs._cacheprofile['lock'] for qs in querysets)
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
if not settings.CACHEOPS_ENABLED or transaction_states.is_dirty(dbs):
return func(*args, **kwargs)
prefix = get_prefix(func=func, _cond_dnfs=cond_dnfs, dbs=dbs)
extra_val = extra(*args, **kwargs) if callable(extra) else extra
cache_key = prefix + 'as:' + get_cache_key(func, args, kwargs, qs_keys, extra_val)
with getting(cache_key, cond_dnfs, prefix, lock=lock) as cache_data:
cache_read.send(sender=None, func=func, hit=cache_data is not None)
if cache_data is not None:
return settings.CACHEOPS_SERIALIZER.loads(cache_data)
else:
precall_key = ''
expected_checksum = ''
if keep_fresh and settings.CACHEOPS_INSIDEOUT:
# The conj stamps should not be dropped while we calculate the function.
# But being filled in concurrently is a normal concurrent cache write.
# However, if they are filled in and then dropped, we cannot detect that.
# Unless we fill them ourselves and get expected checksum now. We also need
# to fill in schemes, so we just reuse the cache_thing().
expected_checksum = cache_thing(prefix, cache_key, '', cond_dnfs, timeout,
dbs=dbs, expected_checksum='never match')
elif keep_fresh:
# We call this "asp" for "as precall" because this key is
# cached before the actual function is called. We randomize
# the key to prevent falsely thinking the key was not
# invalidated when in fact it was invalidated and the
# function was called again in another process.
suffix = get_cache_key(func, args, kwargs, qs_keys, extra_val, random())
precall_key = prefix + 'asp:' + suffix
# Cache a precall_key to watch for invalidation during
# the function call. Its value does not matter. If and
# only if it remains valid before, during, and after the
# call, the result can be cached and returned.
cache_thing(prefix, precall_key, 'PRECALL', cond_dnfs, timeout, dbs=dbs)
result = func(*args, **kwargs)
cache_thing(prefix, cache_key, result, cond_dnfs, timeout, dbs=dbs,
precall_key=precall_key, expected_checksum=expected_checksum)
return result
return wrapper
return decorator
def cached_view_as(*samples, **kwargs):
return cached_view_fab(cached_as)(*samples, **kwargs)
class QuerySetMixin(object):
@cached_property
def _cacheprofile(self):
profile = model_profile(self.model)
return profile.copy() if profile else None
@cached_property
def _cloning(self):
return 1000
def _require_cacheprofile(self):
if self._cacheprofile is None:
raise ImproperlyConfigured(
'Cacheops is not enabled for %s.%s model.\n'
'If you don\'t want to cache anything by default '
'you can configure it with empty ops.'
% (self.model._meta.app_label, self.model._meta.model_name))
def _cache_key(self, prefix=True):
"""
Compute a cache key for this queryset
"""
md = md5()
md.update('%s.%s' % (self.__class__.__module__, self.__class__.__name__))
# Vary cache key for proxy models
md.update('%s.%s' % (self.model.__module__, self.model.__name__))
# Protect from field list changes in model
md.update(stamp_fields(self.model))
# Use query SQL as part of a key
try:
sql, params = self.query.get_compiler(self.db).as_sql()
try:
sql_str = sql % params
except UnicodeDecodeError:
sql_str = sql % walk(force_str, params)
md.update(force_str(sql_str))
except EmptyResultSet:
pass
# If query results differ depending on database
if self._cacheprofile and not self._cacheprofile['db_agnostic']:
md.update(self.db)
# Iterable class pack results differently
it_class = self._iterable_class
md.update('%s.%s' % (it_class.__module__, it_class.__name__))
cache_key = 'q:%s' % md.hexdigest()
return self._prefix + cache_key if prefix else cache_key
@cached_property
def _prefix(self):
return get_prefix(_queryset=self)
@cached_property
def _cond_dnfs(self):
return dnfs(self)
def _cache_results(self, cache_key, results):
cache_thing(self._prefix, cache_key, results,
self._cond_dnfs, self._cacheprofile['timeout'], dbs=[self.db])
def _should_cache(self, op):
# If cache and op are enabled and not within write or dirty transaction
return settings.CACHEOPS_ENABLED \
and self._cacheprofile and op in self._cacheprofile['ops'] \
and not self._for_write \
and not transaction_states[self.db].is_dirty()
def cache(self, ops=None, timeout=None, lock=None):
"""
Enables caching for given ops
ops - a subset of {'get', 'fetch', 'count', 'exists', 'aggregate'},
ops caching to be turned on, all enabled by default
timeout - override default cache timeout
lock - use lock to prevent dog-pile effect
NOTE: you actually can disable caching by omitting corresponding ops,
.cache(ops=[]) disables caching for this queryset.
"""
self._require_cacheprofile()
if ops is None or ops == 'all':
ops = ALL_OPS
if isinstance(ops, str):
ops = {ops}
self._cacheprofile['ops'] = set(ops)
if timeout is not None:
self._cacheprofile['timeout'] = timeout
if lock is not None:
self._cacheprofile['lock'] = lock
return self
def nocache(self):
"""
Convinience method, turns off caching for this queryset
"""
# cache profile not present means caching is not enabled for this model
if self._cacheprofile is None:
return self
else:
return self.cache(ops=[])
def cloning(self, cloning=1000):
self._cloning = cloning
return self
def inplace(self):
return self.cloning(0)
def _clone(self, **kwargs):
if self._cloning:
return self.clone(**kwargs)
else:
self.__dict__.update(kwargs)
return self
def clone(self, **kwargs):
clone = self._no_monkey._clone(self, **kwargs)
clone._cloning = self._cloning - 1 if self._cloning else 0
# NOTE: need to copy profile so that clone changes won't affect this queryset
if self.__dict__.get('_cacheprofile'):
clone._cacheprofile = self._cacheprofile.copy()
return clone
def _fetch_all(self):
# If already fetched or should pass by then fall back
if self._result_cache is not None or not self._should_cache('fetch'):
return self._no_monkey._fetch_all(self)
cache_key = self._cache_key()
lock = self._cacheprofile['lock']
with getting(cache_key, self._cond_dnfs, self._prefix, lock=lock) as cache_data:
cache_read.send(sender=self.model, func=None, hit=cache_data is not None)
if cache_data is not None:
self._result_cache = settings.CACHEOPS_SERIALIZER.loads(cache_data)
else:
self._result_cache = list(self._iterable_class(self))
self._cache_results(cache_key, self._result_cache)
return self._no_monkey._fetch_all(self)
def count(self):
if self._should_cache('count'):
# Optmization borrowed from overridden method:
# if queryset cache is already filled just return its len
if self._result_cache is not None:
return len(self._result_cache)
return cached_as(self)(lambda: self._no_monkey.count(self))()
else:
return self._no_monkey.count(self)
def aggregate(self, *args, **kwargs):
if self._should_cache('aggregate'):
# Apply all aggregates the same way original .aggregate() does, but do not perform sql.
# This code is mostly taken from QuerySet.aggregate().
normalized_kwargs = kwargs.copy()
for arg in args:
try:
normalized_kwargs[arg.default_alias] = arg
except (AttributeError, TypeError):
# Let Django raise a proper error
return self._no_monkey.aggregate(*args, **kwargs)
# Simulate Query.get_aggregation() preparations, this adds proper joins to qs.query
if not normalized_kwargs:
return {}
qs = self._clone()
aggregates = {}
for alias, aggregate_expr in normalized_kwargs.items():
aggregate = aggregate_expr.resolve_expression(
qs.query, allow_joins=True, reuse=None, summarize=True
)
if not aggregate.contains_aggregate:
raise TypeError("%s is not an aggregate expression" % alias)
aggregates[alias] = aggregate
# Use resulting qs as a ref, aggregates still contain names, etc
func = lambda: self._no_monkey.aggregate(self, *args, **kwargs)
return cached_as(qs, extra=aggregates)(func)()
else:
return self._no_monkey.aggregate(self, *args, **kwargs)
def get(self, *args, **kwargs):
# .get() uses the same ._fetch_all() method to fetch data,
# so here we add 'fetch' to ops
if self._should_cache('get'):
# NOTE: local_get=True enables caching of simple gets in local memory,
# which is very fast, but not invalidated.
# Don't bother with Q-objects, select_related and previous filters,
# simple gets - thats what we are really up to here.
#
# TODO: this checks are far from adequate, at least these are missed:
# - self._fields (values, values_list)
# - annotations
# - ...
# TODO: don't distinguish between pk, pk__exaxt, id, id__exact
# TOOD: work with .filter(**kwargs).get() ?
if self._cacheprofile['local_get'] \
and not args \
and not self.query.select_related \
and not self.query.where.children:
# NOTE: We use simpler way to generate a cache key to cut costs.
# Some day it could produce same key for different requests.
key = (self.__class__, self.model) + tuple(sorted(kwargs.items()))
try:
return _local_get_cache[key]
except KeyError:
_local_get_cache[key] = self._no_monkey.get(self, *args, **kwargs)
return _local_get_cache[key]
except TypeError:
# If some arg is unhashable we can't save it to dict key,
# we just skip local cache in that case
pass
if 'fetch' in self._cacheprofile['ops']:
qs = self
else:
qs = self._clone().cache()
else:
qs = self
return qs._no_monkey.get(qs, *args, **kwargs)
def first(self):
if self._should_cache('get'):
return self._no_monkey.first(self._clone().cache())
return self._no_monkey.first(self)
def last(self):
if self._should_cache('get'):
return self._no_monkey.last(self._clone().cache())
return self._no_monkey.last(self)
def exists(self):
if self._should_cache('exists'):
if self._result_cache is not None:
return bool(self._result_cache)
return cached_as(self)(lambda: self._no_monkey.exists(self))()
else:
return self._no_monkey.exists(self)
def bulk_create(self, objs, *args, **kwargs):
objs = self._no_monkey.bulk_create(self, objs, *args, **kwargs)
if family_has_profile(self.model):
for obj in objs:
invalidate_obj(obj, using=self.db)
return objs
def invalidated_update(self, **kwargs):
clone = self._clone().nocache().select_related(None)
clone._for_write = True # affects routing
with atomic(using=clone.db):
objects = list(clone.select_for_update())
rows = clone.update(**kwargs)
# TODO: do not refetch objects but update with kwargs in simple cases?
# We use clone database to fetch new states, as this is the db they were written to.
# Using router with new_objects may fail, using self may return slave during lag.
pks = {obj.pk for obj in objects}
new_objects = self.model.objects.filter(pk__in=pks).using(clone.db)
for obj in chain(objects, new_objects):
invalidate_obj(obj, using=clone.db)
return rows
def connect_first(signal, receiver, sender):
old_receivers = signal.receivers
signal.receivers = []
signal.connect(receiver, sender=sender, weak=False)
signal.receivers += old_receivers
# We need to stash old object before Model.save() to invalidate on its properties
_old_objs = threading.local()
class ManagerMixin(object):
@once_per('cls')
def _install_cacheops(self, cls):
# Set up signals
connect_first(pre_save, self._pre_save, sender=cls)
connect_first(post_save, self._post_save, sender=cls)
connect_first(post_delete, self._post_delete, sender=cls)
# Install auto-created models as their module attributes to make them picklable
module = sys.modules[cls.__module__]
if not hasattr(module, cls.__name__):
setattr(module, cls.__name__, cls)
# This is probably still needed if models are created dynamically or imported late
def contribute_to_class(self, cls, name):
self._no_monkey.contribute_to_class(self, cls, name)
# NOTE: we check it here rather then inside _install_cacheops()
# because we don't want @once_per() and family_has_profile() memory to hold refs.
# Otherwise, temporary classes made for migrations might hoard lots of memory.
if cls.__module__ != '__fake__' and family_has_profile(cls):
self._install_cacheops(cls)
@skip_on_no_invalidation
def _pre_save(self, sender, instance, using, **kwargs):
if instance.pk is not None and not instance._state.adding:
try:
# TODO: do not fetch non-serializable fields
_old_objs.__dict__[sender, instance.pk] \
= sender.objects.using(using).get(pk=instance.pk)
except sender.DoesNotExist:
pass
@skip_on_no_invalidation
def _post_save(self, sender, instance, using, **kwargs):
# Invoke invalidations for both old and new versions of saved object
old = _old_objs.__dict__.pop((sender, instance.pk), None)
if old:
invalidate_obj(old, using=using)
invalidate_obj(instance, using=using)
invalidate_o2o(sender, old, instance, using=using)
# We run invalidations but skip caching if we are dirty
if transaction_states[using].is_dirty():
return
# NOTE: it's possible for this to be a subclass, e.g. proxy, without cacheprofile,
# but its base having one. Or vice versa.
# We still need to invalidate in this case, but cache on save better be skipped.
cacheprofile = model_profile(instance.__class__)
if not cacheprofile:
return
# Enabled cache_on_save makes us write saved object to cache.
# Later it can be retrieved with .get(<cache_on_save_field>=<value>)
# <cache_on_save_field> is pk unless specified.
# This sweet trick saves a db request and helps with slave lag.
cache_on_save = cacheprofile.get('cache_on_save')
if cache_on_save:
# HACK: We get this object "from field" so it can contain
# some undesirable attributes or other objects attached.
# RelatedField accessors do that, for example.
#
# So we strip down any _*_cache attrs before saving
# and later reassign them
unwanted_dict = select_keys(r'^_.*_cache$', instance.__dict__)
for k in unwanted_dict:
del instance.__dict__[k]
key = 'pk' if cache_on_save is True else cache_on_save
cond = {key: getattr(instance, key)}
qs = sender.objects.inplace().using(using).filter(**cond).order_by()
# Mimic Django .get() logic
if MAX_GET_RESULTS and (
not qs.query.select_for_update
or connections[qs.db].features.supports_select_for_update_with_limit):
qs.query.set_limits(high=MAX_GET_RESULTS)
qs._cache_results(qs._cache_key(), [instance])
# Reverting stripped attributes
instance.__dict__.update(unwanted_dict)
def _post_delete(self, sender, instance, using, **kwargs):
"""
Invalidation upon object deletion.
"""
# NOTE: this will behave wrong if someone changed object fields
# before deletion (why anyone will do that?)
invalidate_obj(instance, using=using)
# NOTE: this is needed because m2m_changed is not sent on such deletion:
# https://code.djangoproject.com/ticket/17688
invalidate_m2o(sender, instance, using)
def inplace(self):
return self.get_queryset().inplace()
def cache(self, *args, **kwargs):
return self.get_queryset().cache(*args, **kwargs)
def nocache(self):
return self.get_queryset().nocache()
def invalidated_update(self, **kwargs):
return self.get_queryset().inplace().invalidated_update(**kwargs)
def invalidate_o2o(sender, old, instance, using=DEFAULT_DB_ALIAS):
"""Invoke invalidation for o2o reverse queries"""
o2o_fields = [f for f in sender._meta.fields if isinstance(f, models.OneToOneField)]
for f in o2o_fields:
old_value = getattr(old, f.attname, None)
value = getattr(instance, f.attname)
if old_value != value:
rmodel, rfield = f.related_model, f.remote_field.field_name
if old:
invalidate_dict(rmodel, {rfield: old_value}, using=using)
invalidate_dict(rmodel, {rfield: value}, using=using)
def invalidate_m2o(sender, instance, using=DEFAULT_DB_ALIAS):
"""Invoke invalidation for m2o and m2m queries to a deleted instance"""
all_fields = sender._meta.get_fields(include_hidden=True, include_parents=True)
m2o_fields = [f for f in all_fields if isinstance(f, models.ManyToOneRel)]
fk_fields_names_map = {
f.name: f.attname
for f in all_fields if isinstance(f, models.ForeignKey)
}
for f in m2o_fields:
attr = fk_fields_names_map.get(f.field_name, f.field_name)
value = getattr(instance, attr)
rmodel, rfield = f.related_model, f.remote_field.attname
invalidate_dict(rmodel, {rfield: value}, using=using)
def invalidate_m2m(sender=None, instance=None, model=None, action=None, pk_set=None, reverse=None,
using=DEFAULT_DB_ALIAS, **kwargs):
"""
Invoke invalidation on m2m changes.
"""
# Skip this machinery for explicit through tables,
# since post_save and post_delete events are triggered for them
if not sender._meta.auto_created:
return
if action not in ('pre_clear', 'post_add', 'pre_remove'):
return
m2m = next(m2m for m2m in instance._meta.many_to_many + model._meta.many_to_many
if m2m.remote_field.through == sender)
instance_column, model_column = m2m.m2m_column_name(), m2m.m2m_reverse_name()
if reverse:
instance_column, model_column = model_column, instance_column
# TODO: optimize several invalidate_objs/dicts at once
if action == 'pre_clear':
objects = sender.objects.using(using).filter(**{instance_column: instance.pk})
for obj in objects:
invalidate_obj(obj, using=using)
elif action in ('post_add', 'pre_remove'):
# NOTE: we don't need to query through objects here,
# cause we already know all their meaningful attributes.
for pk in pk_set:
invalidate_dict(sender, {
instance_column: instance.pk,
model_column: pk
}, using=using)
@once
def install_cacheops():
"""
Installs cacheops by numerous monkey patches
"""
monkey_mix(BaseManager, ManagerMixin)
monkey_mix(models.QuerySet, QuerySetMixin)
# Use app registry to introspect used apps
from django.apps import apps
# Install profile and signal handlers for any earlier created models
for model in apps.get_models(include_auto_created=True):
if family_has_profile(model):
if not isinstance(model._default_manager, BaseManager):
raise ImproperlyConfigured("Can't install cacheops for %s.%s model:"
" non-django model class or manager is used."
% (model._meta.app_label, model._meta.model_name))
model._default_manager._install_cacheops(model)
# Bind m2m changed handlers
m2ms = (f for f in model._meta.get_fields(include_hidden=True) if f.many_to_many)
for m2m in m2ms:
rel = m2m if hasattr(m2m, 'through') else m2m.remote_field
opts = rel.through._meta
m2m_changed.connect(invalidate_m2m, sender=rel.through,
dispatch_uid=(opts.app_label, opts.model_name))
# Turn off caching in admin
if apps.is_installed('django.contrib.admin'):
from django.contrib.admin.options import ModelAdmin
@monkey(ModelAdmin)
def get_queryset(self, request):
return get_queryset.original(self, request).nocache()
# Make buffers/memoryviews pickleable to serialize binary field data
import copyreg
copyreg.pickle(memoryview, lambda b: (memoryview, (bytes(b),)))
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