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This library provides a simple interface to register different workloads and visualize their progress with either a plain text progress bar or a jupyter widget, depending on the current environment.
It optionally depends on Jupyter widgets to draw nice progress bars in the interactive Jupyter notebook environment.
pip install progress_reporter
If you use IPython/Jupyter, you are strongly encourage to also install the jupyter widgets:
pip install ipywidgets
Image you have a class doing some heavy calculations, which are split into several jobs/tasks/threads etc.
In order to visualize the progress, one just needs to derive the worker class from progress_reporter.ProgressReporter and invoke the _progress_register method to tell the reporter how many pieces of work have to be done. Then the reporter is instructed by _progress_update(n) how many of pieces of work have been dispatched.
Note that these are “private” to use this class as a mixin class and not polute the public interface.
from progress_reporter import ProgressReporter import time class ExampleWorker(ProgressReporter): def __init__(self, n_jobs=100): self.n_jobs = n_jobs """ register the amount of work with the given description """ self._progress_register(n_jobs, description='Dispatching jobs') def work(self): """ do some fake work (sleep) and update the progress via the reporter """ for job in (lambda: time.sleep(0.1) for _ in range(self.n_jobs)): job() # indicate we've finished one job, to update the progress bar self._progress_update(1)
It also supports multi-stage sequential work loads by setting the parameter stage. This is just the dictionary key to the underlying process:
class MultiStageWorker(ProgressReporter): def __init__(self, n_jobs_init, n_jobs): self.n_jobs_init = n_jobs_init self.n_jobs = n_jobs """ register an expensive initialization routine """ self._progress_register(self.n_jobs_init, description='initializing', stage=0) """ register the main computation """ self._progress_register(self.n_jobs, description='main computation', stage=1) def work(self): """ do the initialization """ for job in (lambda: time.sleep(0.1) for _ in range(self.n_jobs_init)): job() self._progress_update(1, stage=0) """ perform the next stage of the algorithm """ for job in (lambda: time.sleep(0.2) for _ in range(self.n_jobs)): job() self._progress_update(1, stage=1)
Since version 2.0 there is also a version of the this class suitable for compositions.
from progress_reporter import ProgressReporter_ class Estimator(object): def fit(self, X, y=None): pg = ProgressReporter_() pg.register(100, description='work') with pg.context(): # ensure progress bars are closed if an exception occurs. pg.update(50) # ...