def __init__(self, monitor_pid, interval, pipe, *args, include_children=False, **kw):
super().__init__(*args, **kw)
self.monitor_pid = monitor_pid
self.interval = interval
self.pipe = pipe
self.include_children = include_children
try:
self.backend = choose_backend('psutil_uss')
except KeyError:
self.backend = choose_backend()
def memory_profiler(_function=None,
name='',
print_res=True,
stream=None,
precision=1,
backend='psutil'):
"""
内存分析器装饰器
:param _function: 被封装的对象，由解释器自动传入，不需关心
:type _function: types.FunctionType or types.MethodType
:param str name: 关键字参数，被装饰方法所使用的内存分析器名称，默认为使用被装饰方法的方法名
:param bool print_res: 是否在被装饰对象退出后立刻打印分析结果，默认为 True 。
当需要将多次调用结果聚集后输出时，可设为 False ，并通过 Mixin 中的 memory_profiler 进行结果输出
:param object stream: 输出方式，默认为 stdout ，可指定为文件
:param int precision: 精度，默认为 1
:param str backend: 内存监控的 backend ，默认为 'psutil'
:return: 装饰后的函数或方法
:rtype: types.FunctionType or types.MethodType
"""
invoked = bool(_function and callable(_function))
if invoked:
func = _function # type: types.FunctionType or types.MethodType
backend = choose_backend(backend)
if backend == 'tracemalloc' and has_tracemalloc: # pragma: no cover
if not tracemalloc.is_tracing(): # pragma: no cover
tracemalloc.start() # pragma: no cover
def wrapper(func):
"""
装饰器封装函数
"""
@wraps(func)
def inner(*args, **kwargs):
"""
将被封装方法使用 LineProfiler 进行封装
"""
if not (args and base.is_instance_or_subclass(
args[0], MemoryProfilerMixin)):
# 若当前被装饰的方法未继承 MemoryProfilerMixin ，则将其作为普通函数装饰
lp = MemoryProfiler(backend=backend)
else:
self_or_cls = args[0] # type: MemoryProfilerMixin
_name = name or func
lp = self_or_cls.memory_profiler(_name, raise_except=False)
profiler_wrapper = lp(func)
res = profiler_wrapper(*args, **kwargs)
if print_res:
lp.print_stats(stream=stream, precision=precision)
return res
return inner
return wrapper if not invoked else wrapper(func)
def my_profiler(func=None, stream=None, precision=1, backend='psutil'):
backend = memory_profiler.choose_backend(backend)
@wraps(func)
def wrapper(*args, **kwargs):
prof = memory_profiler.LineProfiler(backend=backend)
prof(func)(*args, **kwargs)
return prof
return wrapper
def __enter__(self):
backend = choose_backend()
self.child_conn, self.parent_conn = Pipe() # this will store MemTimer's results
self.p = MemTimer(os.getpid(), self.interval, self.child_conn, self.filename,
backend=backend, timestamps=self.timestamps, max_usage=self.max_usage,
include_children=self.include_children)
self.p.start()
self.parent_conn.recv() # wait until memory logging in subprocess is ready
return self
def _process_backend(backend='psutil'):
"""
处理内存分析器的后端
:param str backend: 内存监控的 backend ，默认为 'psutil'
:return: 处理后的后端名称
:rtype: str
"""
backend = choose_backend(backend)
if backend == 'tracemalloc' and has_tracemalloc and \
not tracemalloc.is_tracing(): # pragma: no cover
tracemalloc.start()
return backend