Fastprogress

1.1.5 · active · verified Sat Apr 11

Fastprogress is a Python library providing fast and simple progress bars for Jupyter Notebooks and console applications. It features nested progress bars and plotting options, often used within the fastai ecosystem. The library is actively maintained with frequent minor releases, most recently v1.1.5, and has a cadence of several updates per year.

Warnings

breaking Version 1.1.0 introduced a breaking change by converting to `fasthtml` for modernization. This change may affect internal behavior and can introduce a dependency on `python-fasthtml` which has been reported to cause installation issues on some platforms due to SQLite C bindings.
Fix: Ensure `python-fasthtml` (and its underlying dependencies like SQLite development headers if building from source) can be installed in your environment. Consider pinning to a version <1.1.0 if `fasthtml` integration causes issues.
gotcha If `total` is not explicitly passed to `progress_bar` or `master_bar` for an iterator of unknown length, the progress bar may not display correctly, or it might warn if the generator is empty. `fastprogress` does not auto-infer `total` for all iterables.
Fix: Always provide the `total` argument if the length of your iterable is known (e.g., `range(N)` or `len(my_list)`). For truly unknown lengths, you might explicitly pass `total='noinfer'` (supported since 1.0.3) or handle the display logic manually.
gotcha In non-interactive environments (e.g., CI/CD pipelines, scripts with redirected `stdout`), the progress bars will not render visually. Only output generated by `mb.write()` will be captured.
Fix: Design your scripts to rely on `mb.write()` for critical logging messages that need to be captured in non-interactive contexts. For debugging, ensure you run in a true TTY or Jupyter environment.
gotcha Users have reported `ModuleNotFoundError: No module named 'IPython'` or issues with progress bars not displaying correctly in certain Jupyter environments (e.g., VS Code Jupyter notebooks, specific `ipywidgets` configurations). This can lead to progress bars falling back to console behavior.
Fix: Ensure `IPython` and `ipywidgets` are correctly installed and configured in your environment (`pip install ipython ipywidgets`). For problematic environments, try explicitly using `ConsoleMasterBar` and `ConsoleProgressBar` or investigate `ipywidgets` installation troubleshooting steps.

Install

pip install fastprogress Install with pip

Imports

master_bar

from fastprogress.fastprogress import master_bar

progress_bar

from fastprogress.fastprogress import progress_bar

ConsoleMasterBar
```
from fastprogress.fastprogress import ConsoleMasterBar
```
Use for explicit console-only progress bars, bypassing notebook detection.
ConsoleProgressBar
```
from fastprogress.fastprogress import ConsoleProgressBar
```
Use for explicit console-only progress bars, bypassing notebook detection.

Quickstart

This example demonstrates a nested progress bar. `master_bar` handles the outer loop, and `progress_bar` handles the inner loop, linked via the `parent` argument. Comments can be updated, and `mb.write()` adds persistent messages.

from fastprogress.fastprogress import master_bar, progress_bar
import time

mb = master_bar(range(10))
mb.write('Starting main loop...')
for i in mb:
    mb.main_bar.comment = f'Processing outer item {i+1}/10'
    for j in progress_bar(range(100), parent=mb):
        time.sleep(0.01) # Simulate some work
    mb.child.comment = f'Inner loop for item {i+1} complete'
    mb.write(f'Finished outer loop iteration {i+1}.')
mb.write('All loops complete.')

view raw JSON →