And after a few attempts this is the code that got TLE in 3rd test: https://codeforces.com/contest/1334/submission/209278732 However after adding the lines: import sys input = sys.stdin.buffer.readline The same code got accepted and was pretty quick. https://codeforces.com/contest/1334/sub...
import time time.sleep(2) print("测试代码执行完成") '''# 测量代码执行时间execution_time=timeit.timeit(stmt=code,number=1)print(f"执行时间:{execution_time}秒") 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 在上述代码中,我们定义了一个字符串code,其中包含我们要测试的代码。然后,我们...
importtimeit# 需要测量执行时间的代码code_to_be_measured=''' for i in range(1000000): pass '''# 测量代码执行时间execution_time=timeit.timeit(code_to_be_measured,number=10)/10print("代码执行时间:",execution_time,"秒") 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 在上面的示例中...
"""timer=timeit.Timer(stmt=code_to_measure)execution_time=timer.timeit(number=1000)# 执行代码1000次print(f"代码执行平均时间:{execution_time / 1000} 秒") 1. 2. 3. 4. 5. 6. 7. 8. 9. 3. 使用 cProfile 模块进行性能分析 Python 的 cProfile模块用于执行代码的性能分析。它会生成一个分析...
code = "sum(range(1000))" execution_time = timeit.timeit(code, number=10000) # 运行10000次 print(f"平均耗时: {execution_time / 10000:.6f}秒") # 输出: 平均耗时: 0.000012秒 适用场景 算法性能对比、代码优化测试。 3. calendar 模块(Python内置) ...
start = time.perf_counter()try:yieldfinally: end = time.perf_counter()print("{} : {}".format(label, end - start)) 下面这个例子演示了这个上下文管理器是如何工作的: withtimeblock("counting"): n =10000000whilen >0: n -=1 控制台打印输出如下所示: ...
When you stop code execution in the debugger, you can inspect and modify the values of variables. You can also use theWatchwindow to monitor individual variables and custom expressions. For more information, seeInspect variables. To view a value by using theDataTipsfeature during debugging, hover...
However, if you need to run the input code many times, then using a string as an argument will make the function run the parsing and compilation steps every time. This behavior can make your code inefficient in terms of execution speed....
execution_time = end_time - start_time print(f"代码执行时间:{execution_time} 秒") time.perf_counter() time.perf_counter()函数返回一个高精度的性能计数器,通常用于测量较小代码块的执行时间。 import time start_time = time.perf_counter() # 执行你的代码 end_time = time.perf_counter() execut...
1) 输入(input):通过键盘、文件、或其他设备获取数据。 2) 输出(output):在显示屏展示数据或发送数据至文件或其他设备。 3) 数学(math):执行基本的数学运算:加减乘除。 4)条件执行(conditional execution):根据相应条件执行适当的代码。 5) 重复(repetition):重复执行,通常在出现某些变量。