U /eX@sddlmZddlZddlmZmZddlmZmZddl m Z ddl m Z m Z m Z ddlmZe rddlZddlmZdd lmZGd d d ZGd d d ZdS)) annotationsN) AsyncIteratorIterator)asynccontextmanagercontextmanager)datetime) TYPE_CHECKINGAnycast)PeriodicCallback)Client) Schedulerc@seZdZUdZded<ddZd#dddd d d d d ddddZed dd d ddddZe d dd d ddddZ dddddddZ dddddd d!d"Z dS)$ MemorySampleravSample cluster-wide memory usage every seconds. **Usage** .. code-block:: python client = Client() ms = MemorySampler() with ms.sample("run 1"): with ms.sample("run 2"): ... ms.plot() or with an asynchronous client: .. code-block:: python client = await Client(asynchronous=True) ms = MemorySampler() async with ms.sample("run 1"): async with ms.sample("run 2"): ... ms.plot() "dict[str, list[tuple[float, int]]]samplescCs i|_dSN)r)selfrJ/tmp/pip-unpacked-wheel-g426oqom/distributed/diagnostics/memory_sampler.py__init__6szMemorySampler.__init__Nprocessg?clientmeasureintervalz str | Nonez Client | Nonestrfloatr )labelrrrreturncCs@|sddlm}|}|jr,|||||S|||||SdS)a:Context manager that records memory usage in the cluster. This is synchronous if the client is synchronous and asynchronous if the client is asynchronous. The samples are recorded in ``self.samples[