from datetime import datetime
import time
for i in range(1000):
curr_time = datetime.now()
print(curr_time)
time.sleep(0.0001)
I was testing the resolution of datetime.now()
. Since it supposes to output in microsecond, I expected that each print will be different.
However, I always get something like that.
...
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.212073
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
2015-07-10 22:38:47.213074
...
Why does that happen? Is there any way that I can get an accurate timestamp down to the microsecond? Actually I don't need microseconds, but it would be nice to get 0.1ms resolution.
=== UPDATE ====
I compared it with using time.perf_counter() and adding to the starting datetime
from datetime import datetime, timedelta
import time
datetime0 = datetime.now()
t0 = time.perf_counter()
for i in range(1000):
print('datetime.now(): ', datetime.now())
print('time.perf_counter(): ', datetime0 + timedelta(0, time.perf_counter()-t0))
print('\n')
time.sleep(0.000001)
I am not sure how 'accurate' it really is, but the resolution is at least higher.... it doesn't seems to matter as my computer cannot even print at a speed that high. For my purpose, which I simply need different timestamps to distinguish different entries, this is good enough for me.
...
datetime.now(): 2015-07-10 23:24:18.010377
time.perf_counter(): 2015-07-10 23:24:18.010352
datetime.now(): 2015-07-10 23:24:18.010377
time.perf_counter(): 2015-07-10 23:24:18.010545
datetime.now(): 2015-07-10 23:24:18.010377
time.perf_counter(): 2015-07-10 23:24:18.010745
datetime.now(): 2015-07-10 23:24:18.011377
time.perf_counter(): 2015-07-10 23:24:18.010961
datetime.now(): 2015-07-10 23:24:18.011377
time.perf_counter(): 2015-07-10 23:24:18.011155
datetime.now(): 2015-07-10 23:24:18.011377
time.perf_counter(): 2015-07-10 23:24:18.011369
datetime.now(): 2015-07-10 23:24:18.011377
time.perf_counter(): 2015-07-10 23:24:18.011596
datetime.now(): 2015-07-10 23:24:18.012379
time.perf_counter(): 2015-07-10 23:24:18.011829
datetime.now(): 2015-07-10 23:24:18.012379
time.perf_counter(): 2015-07-10 23:24:18.012026
datetime.now(): 2015-07-10 23:24:18.012379
time.perf_counter(): 2015-07-10 23:24:18.012232
datetime.now(): 2015-07-10 23:24:18.012379
time.perf_counter(): 2015-07-10 23:24:18.012424
datetime.now(): 2015-07-10 23:24:18.012379
time.perf_counter(): 2015-07-10 23:24:18.012619
datetime.now(): 2015-07-10 23:24:18.013380
time.perf_counter(): 2015-07-10 23:24:18.012844
datetime.now(): 2015-07-10 23:24:18.013380
time.perf_counter(): 2015-07-10 23:24:18.013044
datetime.now(): 2015-07-10 23:24:18.013380
time.perf_counter(): 2015-07-10 23:24:18.013242
datetime.now(): 2015-07-10 23:24:18.013380
time.perf_counter(): 2015-07-10 23:24:18.013437
datetime.now(): 2015-07-10 23:24:18.013380
time.perf_counter(): 2015-07-10 23:24:18.013638
datetime.now(): 2015-07-10 23:24:18.014379
time.perf_counter(): 2015-07-10 23:24:18.013903
datetime.now(): 2015-07-10 23:24:18.014379
time.perf_counter(): 2015-07-10 23:24:18.014125
datetime.now(): 2015-07-10 23:24:18.014379
time.perf_counter(): 2015-07-10 23:24:18.014328
datetime.now(): 2015-07-10 23:24:18.014379
time.perf_counter(): 2015-07-10 23:24:18.014526
datetime.now(): 2015-07-10 23:24:18.014379
time.perf_counter(): 2015-07-10 23:24:18.014721
datetime.now(): 2015-07-10 23:24:18.015381
time.perf_counter(): 2015-07-10 23:24:18.014919
...
This may be a limitation of
time.sleep
on your system, rather thandatetime.now()
... or possibly both. What OS and what version and distribution of Python are you running on?Your system may not offer the "subsecond precision" mentioned in the
time.sleep
docs:On Linux 3.x on amd64 with CPython 2.7, I get something pretty close to the 0.0001 time steps that you intended: