brewbar 2.0.0

A progress bar for Python — tqdm-compatible API plus extras (predictive ETA, memory/CPU monitoring, sparklines, hooks, multi-bar groups, logging integration)

🍺 brewbar

A serious progress bar for Python — with beer. Drop-in compatible with the tqdm API, with extras tqdm doesn't have. Beer-themed by default; turn it off with brew=False if you need plain blocks.

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The look

Working: 100% |🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺| 50/50 [00:00<00:00, 839.06it/s] cheers 🍻
Half:     50% |🍺🍺🍺🍺🍺🍺🍺🍺🍺🍺··········| 50/100 [00:00<00:00, 18.9it/s] fermenting

The bar walks through brew stages as it fills: mashing → boiling → fermenting → conditioning → cheers 🍻. Want clean Unicode blocks instead? bar(..., brew=False).

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Why brewbar?

If you've used tqdm, brewbar will feel immediately familiar — same kwargs, same methods, same iterator protocol. The difference is what brewbar adds:

Feature	tqdm	brewbar
Iterator-based bars	✅	✅
Manual update() mode	✅	✅
Nested / multi bars	✅	✅
Postfix / descriptions	✅	✅
Dynamic miniters auto-tune	✅	✅
pandas integration	✅	✅
Predictive ETA (regression-based)	❌	✅
ETA confidence intervals	❌	✅
Memory monitoring built-in	❌	✅
CPU monitoring built-in	❌	✅
Rate trend sparkline	❌	✅
Pause / resume timing	❌	✅
Auto-color (green/yellow/red)	❌	✅
Time budget tracking	❌	✅
Hooks (on_update / on_complete / on_interval)	❌	✅
Metric tracking (min/max/avg)	❌	✅
Logging integration	partial	✅
Multi-bar group manager	❌	✅

Zero hard dependencies. Optional extras: psutil (memory/CPU), pandas.

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Install

pip install brewbar              # core only
pip install brewbar[monitoring]  # + memory/CPU
pip install brewbar[pandas]      # + pandas .progress_apply
pip install brewbar[all]         # everything

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Drop-in tqdm replacement

# from tqdm import tqdm, trange
from brewbar import BrewBar as tqdm, trange

for x in tqdm(range(100), desc="Training"):
    ...

for i in trange(100):
    ...

Or use brewbar's native names:

from brewbar import bar, trange, BrewBar

for x in bar(range(100), desc="Working"):
    ...

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Basic usage

from brewbar import bar
import time

for _ in bar(range(100), desc="Processing"):
    time.sleep(0.05)

Processing:  47% |██████████████████▍                    | 47/100 [00:02<00:02, 18.9it/s]

Manual mode

from brewbar import BrewBar

with BrewBar(total=1024, unit="B", unit_scale=True, desc="Download") as pbar:
    for chunk in download():
        pbar.update(len(chunk))

Description + postfix (training loops)

pbar = bar(range(epochs), desc="Train")
for epoch in pbar:
    loss = train_one_epoch()
    pbar.set_postfix(loss=loss, lr=0.001, acc=0.95)

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Features tqdm doesn't have

1. Predictive ETA with confidence

Standard progress bars show ETA based on average rate. brewbar uses linear regression over recent samples, and can show a confidence window:

bar(range(1000), eta_confidence=True)

Working:  42% |████████████▌                | 420/1000 [00:21<00:30±00:05, 19.8it/s]

The ±00:05 tells you how confident the estimate is. Wider window = less stable rate.

2. Memory / CPU monitoring

Requires pip install brewbar[monitoring].

bar(range(1000), show_memory=True, show_cpu=True)

Working:  42% |████████████▌      | 420/1000 [00:21<00:30, 19.8it/s] mem=1.24GiB cpu=87%

3. Rate trend sparkline

See whether your throughput is climbing or collapsing at a glance:

bar(range(1000), show_sparkline=True)

 42% |████████████▌      | 420/1000 [00:21<00:30, 19.8it/s] ▁▂▃▅▆▇█▇

4. Auto-color

Color the bar by pace, no manual logic:

bar(range(1000), auto_color=True)
# green when rate is steady/improving
# yellow when it drops
# red when it tanks

Combine with a time budget:

bar(range(1000), auto_color=True, eta_budget=60)
# green if projected completion < 60s, yellow near limit, red if over

5. Pause / resume timing

I/O waits or user interaction shouldn't count against your throughput. Pause the timer:

pbar = bar(range(100))
for i in pbar:
    process(i)
    with pbar.paused():
        input("Press enter to continue...")

Time inside paused() is excluded from elapsed/rate/ETA.

6. Hooks

def log_progress(b):
    print(f"At {b.n}/{b.total}, rate={b._avg_rate:.1f}/s")

bar(range(1000),
    on_update=lambda b: ...,                    # every render
    on_complete=lambda b: ...,                  # when done
    on_interval=(5.0, log_progress))            # every 5 seconds

7. Metric tracking

Track stats over the lifetime of the bar:

pbar = bar(range(epochs), track_metrics=["loss", "acc"])
for epoch in pbar:
    pbar.set_postfix(loss=loss(), acc=acc())

print(pbar.metric_summary())
# {'loss': {'min': 0.12, 'max': 2.30, 'avg': 0.87, 'last': 0.12, 'count': 100},
#  'acc':  {'min': 0.41, 'max': 0.96, 'avg': 0.82, 'last': 0.96, 'count': 100}}

8. Multi-bar groups

from brewbar import BarGroup

with BarGroup() as group:
    download = group.add(total=100, desc="Download")
    process  = group.add(total=100, desc="Process")
    upload   = group.add(total=100, desc="Upload")

    for i in range(100):
        download.update(); process.update(); upload.update()

9. Logging integration

Route log records through brewbar so they don't shred your bars:

import logging
from brewbar import bar, redirect_logging

redirect_logging(level=logging.INFO)
log = logging.getLogger(__name__)

for i in bar(range(100), desc="Work"):
    if i % 10 == 0:
        log.info(f"checkpoint {i}")   # appears above the bar cleanly

10. write() without breaking bars

from brewbar import bar, write

pbar = bar(range(100))
for i in pbar:
    if some_condition:
        write(f"  >> noteworthy event at {i}")   # or pbar.write(...)

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Full API reference

BrewBar(iterable=None, *, ...)

All tqdm-compatible kwargs:

desc, total, leave, file, ncols, mininterval, maxinterval, miniters, ascii, disable, unit, unit_scale, unit_divisor, dynamic_ncols, smoothing, bar_format, initial, position, postfix, delay, colour / color

brewbar extras:

brew (default True — 🍺 fill glyphs and brew stage labels), show_stage, auto_color, show_memory, show_cpu, show_sparkline, sparkline_width, eta_confidence, eta_budget, on_update, on_complete, on_interval, track_metrics

Methods

.update(n=1), .refresh(), .reset(total=None), .clear(), .close(), .set_description(desc), .set_description_str(desc), .set_postfix(...), .set_postfix_str(s), .display(), .pause(), .resume(), .paused(), .metric_summary(), .write(msg)

Class methods

BrewBar.get_lock(), BrewBar.set_lock(lock), BrewBar.write(msg), BrewBar.pandas(**kw)

Module functions

bar(...), trange(...), track(...), write(...), redirect_logging(...)

bar_format fields

{n} {n_fmt} {total} {total_fmt} {percentage} {rate} {rate_fmt} {elapsed} {elapsed_fmt} {remaining} {remaining_fmt} {remaining_conf_fmt} {desc} {postfix} {unit} {bar} {memory} {cpu} {sparkline}

Example:

bar(range(100),
    bar_format="{desc} {percentage:3.0f}% [{bar}] {n_fmt}/{total_fmt} • {rate_fmt} • ETA {remaining_fmt}",
    ncols=20)

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Pandas

from brewbar import BrewBar
import pandas as pd

BrewBar.pandas(desc="Computing")
df["squared"] = df["x"].progress_apply(lambda x: x * x)

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Compatibility

• Python 3.8 — 3.13
• Linux, macOS, Windows (Windows Terminal recommended)
• TTY-aware: silently disables in CI, pipes, and redirected output (override with disable=False)
• NO_COLOR and FORCE_COLOR env vars honored

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License

MIT