Python library for Data Science
Project description
ProgressBar
Let us consider a few examples explaining how to use the ProgressBar
class from the module progress
:
from deeppy.progress import ProgressBar
from time import sleep
bar = ProgressBar(max=20, width=50, elapsed=True)
for i in range(10):
sleep(1)
bar.next()
bar.finish()
print()
for i in range(15):
sleep(1)
bar.next()
Out:
Processing: [######################### ] 50% [elapsed: 10s; ETA: 10s]
Processing: [##################################### ] 75% [elapsed: 15s; ETA: 5s]
The class supports the context management protocol and can be used with the with
statement. Alternative bar formats are also available:
with ProgressBar("Charging", max=20, width=50) as bar:
for i in range(10):
sleep(1)
bar.next()
print()
with ProgressBar("FillingSquares", max=20, width=50) as bar:
for i in range(15):
sleep(1)
bar.next()
Out:
Processing: [█████████████████████████∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙∙] 50% [ETA: 10s]
Processing: [▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▣▢▢▢▢▢▢▢▢▢▢▢▢▢] 75% [ETA: 5s]
Note that the next
method can be replaced by the show
method with index
argument supplied:
with ProgressBar("FillingCircles", max=20, width=50, eta=False) as bar:
for i in range(10):
sleep(1)
bar.show(i + 1)
Out:
Processing: [◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◉◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯◯] 50%
ProgressSpinner
The following examples explain how to use the ProgressSpinner
class from the module progress
:
from deeppy.progress import ProgressSpinner
from time import sleep, time
spinner = ProgressSpinner()
since = time()
while True:
# Do some work
sleep(0.2)
spinner.next()
if time() - since > 5:
break
Alternative spinner formats are also available:
with ProgressSpinner("Pie") as spinner:
since = time()
while True:
sleep(0.2)
spinner.next()
if time() - since > 5:
break
print()
with ProgressSpinner("Moon") as spinner:
since = time()
while True:
sleep(0.2)
spinner.next()
if time() - since > 5:
break
print()
with ProgressSpinner("Pixel") as spinner:
since = time()
while True:
sleep(0.2)
spinner.next()
if time() - since > 5:
break
Out:
Processing: ◷
Processing: ◐
Processing: ⣷
Installation
Download from PyPI:
pip install deep-py
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