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 = ...
active_count()函数:获取当前活动线程的数量。 3. 代码实战:多线程下载图片 下面通过一个实例来演示多线程的应用,我们将使用多线程来下载一系列图片。 import threading import requests from queue import Queue class ImageDownloader: def __init__(self, urls): self.urls = urls self.queue = Queue() def...
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...
>>>importtime>>>defcount():...start=time.perf_counter()...n=0...whilen<1000000000:...n+=1...print(f"Completed Execution in {time.perf_counter() - start} seconds")...>>>count()Completed Executionin44.67635616599998seconds 如您所见,我使用 Python 代码,整个计算过程花了惊人的 44.67 秒...
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 ...
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...