cleantimer
Track progress of long-running scripts, without cluttering your code with log statements.
cleantimer is a minimal wrapper around a couple of my favorite packages for timing scripts - contexttimer and tqdm. It merges their most useful features in a clean API based simply on the way I've found I like to use them. Hopefully you find it simply useful. 😊
Installation
pip install cleantimer
Import:
from cleantimer import CTimer
Use cases
A basic timer with a message for what you're timing:
with CTimer("Waking up"):
sleep(4)Waking up (3:22PM)...done. (4.0s)
Print with varying precision:
with CTimer("Waking up", 3):
sleep(4.123456)Waking up (3:22PM)...done. (4.123s)
Sub-timers
with CTimer("Making breakfast") as timer:
sleep(2)
with timer.child("cooking eggs") as eggtimer:
sleep(3)
with timer.child("pouring juice"):
sleep(1)Making breakfast (3:22PM)...
cooking eggs (3:22PM)...done. (3.0s)
pouring juice (3:23PM)...done. (1.0s)
done. (6.0s)
Progress meter on a Pandas apply
df = pd.DataFrame({"A": list(range(10000))})
def times2(row): return row["A"] * 2
with CTimer("Computing doubles") as timer:
df["2A"] = timer.progress_apply(df, times2)Computing doubles (3:22PM)...
: 100% ██████████████████████████ 10000/10000 [00:07<00:00, 135869it/s]
done. (7.4s)
Segmented progress meter
df = pd.DataFrame({"A": list(range(10000)), "type": [1]*5000 + [2]*5000})
def times2(row): return row["A"] * 2
with CTimer("Computing doubles") as timer:
df["2A"] = timer.progress_apply(df, times2, split_col="type", message="part {}")Computing doubles (3:22PM)...
part 1: 100% ██████████████████████████ 5000/5000 [00:07<00:00, 135869it/s]
part 2: 100% ██████████████████████████ 5000/5000 [00:07<00:00, 122854it/s]
done. (8.2s)
