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Airflow python callable with arguments
Airflow python callable with arguments











airflow python callable with arguments

How do I cache method calls? for more details on how this differs from cached_property().īerubah pada versi 3.12: Prior to Python 3.12, cached_property included an undocumented lock toĮnsure that in multi-threaded usage the getter function was guaranteed to Stacking property() on top of lru_cache(). If a mutable mapping is not available or if space-efficient key sharing isĭesired, an effect similar to cached_property() can also be achieved by (as such classes don't provide a _dict_ attribute at all). _slots_ without including _dict_ as one of the defined slots Read-only proxies for the class namespace), and those that specify Metaclasses (since the _dict_ attributes on type instances are This means it will not work with some types, such as This means that instance dictionariesĪlso, this decorator requires that the _dict_ attribute on each instanceīe a mutable mapping. Note, this decorator interferes with the operation of PEP 412 Locking inside the decorated getter function or around the cached property If synchronization is needed, implement the necessary Property is idempotent or otherwise not harmful to run more than once on an Same instance, with the latest run setting the cached value. The getter function could run more than once on the The cached_property does not prevent a possible race condition in ThisĪllows the cached_property method to run again. The cached value can be cleared by deleting the attribute. Method and it works like a normal attribute. SubsequentĪttribute reads and writes take precedence over the cached_property When it does run, theĬached_property writes to the attribute with the same name. The cached_property decorator only runs on lookups and only when anĪttribute of the same name doesn't exist. In contrast, a cached_property allows writes. A regular property blocks attribute writes unless a The mechanics of cached_property() are somewhat different from _data = tuple ( sequence_of_numbers ) def stdev ( self ): return statistics. Class DataSet : def _init_ ( self, sequence_of_numbers ): self.













Airflow python callable with arguments