deflimit_execution_count(max_count):defdecorator(func):count=0defwrapper(*args,**kwargs):nonlocalcount count+=1# 执行函数的其他操作ifcount>max_count:print("函数已达到执行次数限制,中止函数的执行")# 中止函数的执行returnreturnfunc(*args,**k
t = Timer()# Use 1: Explicit start/stopt.start() countdown(1000000) t.stop()print(t.elapsed)# 0.058305625# Use 2: As a context managerwitht: countdown(1000000)print(t.elapsed)# 0.11482683300000004withTimer()ast2: countdown(1000000)print(t2.elapsed)# 0.056095916999999995 如同前面所展示的,...
# apply execution count as first sorting value and save first10unique queries to file. # In addition, remember last input file position and statistics. php mysql_filter_slow_log.php -T=3-eu=root --no-duplicates --sort-execution-count --top=10--incremental linux-slow.log > mysql-slow-qu...
get_execution_time() same as get_execution_timestamp() returns a floating points with seconds as unit. get_delta_time() returns the time difference between the current call (start(), tick() or stop()) and the last call. get_execution_count() returns the number of times the codelet has...
# 生成器函数 def countdown(num): while num > 0: yield num num -= 1 3、利用装饰器简化重复性工作 装饰器是Python中用于修改函数行为的强大工具,如日志记录、性能测量和权限检查。# 装饰器示例 def my_decorator(func): def wrapper(*args, **kwargs): print("Before function execution") result = ...
importtimefromfunctoolsimportwrapsdeftimethis(func):'''Decorator that reports the execution time.'''@wraps(func)defwrapper(*args,**kwargs):start=time.perf_counter()result=func(*args,**kwargs)end=time.perf_counter()print(func.__name__,end-start)returnresultreturnwrapper@timethisdefcountdown(...
在这个 Counter 类中,我们有一个.count实例属性来跟踪当前计数。然后,你有一个.increment()方法,每次调用它时都将计数加 1。最后,添加一个.__call__()方法。在这个示例中,.__call__()返回到调用.increment(),为运行递增操作提供了快捷方式。 看看该类产品在实践中是如何工作的: ...
start_time_2=time.time()withconcurrent.futures.ProcessPoolExecutor(max_workers=5)asexecutor:futures=[executor.submit(count,item)foriteminnumber_list]forfutureinconcurrent.futures.as_completed(futures):print(future.result())print("Process pool execution in "+str(time.time()-start_time_2),"seconds...
count() 300 您也可以使用map-only的map_reduce,该操作与axis=1的apply操作是等价的。 >>> iris.map_reduce(mapper=handle).count() 300 如果您想调用MaxCompute上已经存在的UDTF,函数指定为函数名即可。 >>> iris['name', 'sepallength'].apply('your_func', axis=1, names=['name2', 'sepal...
Over time, however, the advocate count grew, and the comp.lang.python usenet group was founded in 1994. Unlike GNU, Python was originally released completely “free;” no stated or implied license accompanied it. Just as with almost every other scripting language, one of the main goals of ...