Python无限循环随着时间的推移而变慢

Question

我有一个函数，它是一个更大的无穷大的一部分。我发现该函数将循环减慢到最终我的计算机将完全冻结的程度。

import numpy as np
from time import time
 
  
def make_fps(d, F, df_f, state, t_start, PHASE, run_num):
    F += 1
    if F < 100:
        fps = np.NaN
        fps_average = np.NaN
    else:
        fps = round(F / (time() - t_start), 2)
        fps_average = np.NaN
    if F > 200:
        fps_average = round(df_f["fps"].mean(), 2)
    df = {'frame number': [F], 'fps': [
        fps], 'fps average': [fps_average], 'state': [state],  'run number': [run_num]}
    df_new = pd.DataFrame(data=df)
    df_f = df_f.append(df_new)
    print("frame number", F, "fps", fps, "average fps",
            fps_average,  "run number", run_num)
    return df_f, F, fps, run_num, fps_average

df_f = pd.DataFrame()
state = "this is a test"
t_start = time()
d, F, PHASE, run_num = 0,0, 0, 0       

while True:
    df_f, F, fps, run_num, fps_average = make_fps(d, F, df_f, state, t_start, PHASE, run_num)
    print (F, fps, fps_average)

我认为构建 DataFrame 会导致问题。另外，这个功能会从实现生成器中受益吗？我是 python 新手，不清楚如何正确应用生成器。

谢谢！

Answer 1

看起来你一遍又一遍地传递相同的参数。 我想不出为什么这可能是个好主意。 但是关于生成器的问题，把return换成yield就行了

祝你好运！