Hello, I just thought of comparing the speeds of two methods to double a number in python but didn't got a precise result. Can anyone help me improving this testing?

importtime,randommainscores=[[],[]]fordigitsinrange(15):print('Calculations with %s digit numbers are going on...'%(digits+1))scoreplus=0scoremultiply=0forminrange(100):timebyaplusa=0timebyatimestwo=0whiletimebyaplusa==timebyatimestwo:a=random.randint((10**digits),(10**(digits+1))-1)starttime=time.time()b1=a+atimebyaplusa+=time.time()-starttimestarttime=time.time()b2=a*2timebyatimestwo+=time.time()-starttimeifb1!=b2:print('Error')iftimebyaplusa>timebyatimestwo:scoremultiply+=1else:scoreplus+=1mainscores[0].append(scoreplus)mainscores[1].append(scoremultiply)

Don't know anything about Python, but my guess is that only 1 trial per an \( n \) digit number won't tell you much, since both methods have comparable times and the random factors obfuscate any differences in the short term.

If you want to see a difference, try more trials (1000?) and average them out instead of just one trial.

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TopNewestDon't know anything about Python, but my guess is that only 1 trial per an \( n \) digit number won't tell you much, since both methods have comparable times and the random factors obfuscate any differences in the short term.

If you want to see a difference, try more trials (1000?) and average them out instead of just one trial.

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Good idea! Let me try that out.

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Well, for 10k calculations, for \(n\) digit numbers, \(n\in \{1,2,3,\cdots,20\}\), the results were as follows:

while with 1m calculations, the results were:

Seems like '+' wins in case of bigger numbers.

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