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RunScope

A progress bar that doesn't lie. Calibrated ETAs and completion intelligence for long-running Python jobs.

from runscope import trange           # drop-in for tqdm

for i in trange(48000, key="terrain_analysis"):
    process(tile(i))
terrain_analysis  ▕████████░░░░░░░░░░░░▏ 38%  17,492/48,000
  47m elapsed · about 1h 20m left · done ~10:42 PM
  likely 1h 12m–1h 31m · confidence high

Ordinary progress bars assume the rest of your job looks like the part that already ran. That assumption breaks exactly when it matters — when the expensive work is at the end. RunScope gives you an honest range instead of a fake exact number, and it learns your recurring jobs so each run's estimate gets better than the last.


Install

pip install runscope        # free, local, zero dependencies

Use it

1. Wrap any loop

import runscope

for item in runscope.track(items, key="my_job"):
    process(item)

2. Drop-in for tqdm

from runscope import trange
for i in trange(10000, key="my_job"):
    ...

3. Tell it how "big" each item is (stronger estimates)

for path in runscope.track(files, key="ingest", weight=lambda p: p.stat().st_size):
    process(path)

4. Peek at the future for known-heterogeneous jobs

# checks a tiny representative sample of the REMAINING work up front, so a
# back-loaded job can't ambush you with a 3x longer runtime at the end
for item in runscope.track(items, key="my_job", weight=size_of, measure=True):
    process(item)

5. Instrument an existing script without editing it

runscope run train.py        # transparently upgrades tqdm bars in the script

How it works (you never have to think about this)

Three layers combine automatically:

Layer What it does When it kicks in
Now size-weighted estimate from the current run always
Memory learns how this job actually behaves and calibrates after ~3 runs of the same key
Peek samples a little of the remaining work to catch heavy tails measure=True

The key is what ties runs of the same job together so RunScope can learn. Use a stable name for recurring jobs (key="nightly_terrain").

The three modes (you never pick — it uses the best it can)

mode what it does cost
Padawan estimate from the current run free forever
Master learns a recurring job after ~3 runs and calibrates free forever
Jedi measure=True — samples a little of the upcoming work to predict heavy/uneven jobs accurately free through Sep 30, 2026, then Pro

Padawan and Master are automatic and always free. Jedi is opt-in — the first time you use measure=True, RunScope asks once (and remembers). Jedi is free for everyone through September 30, 2026 while we test.

Pricing (after the free period)

Padawan + Master stay free, forever, offline. Jedi becomes part of RunScope Pro:

  • Pro — $9/month (or $90/year): unlimited Jedi, cloud run history across machines, and job-finished / ETA-blowout alerts.
  • Pay-as-you-go Jedi — $0.002 per measured job for occasional users who don't want a subscription.

(Introductory pricing, subject to change. Nothing you can do today with Padawan or Master will ever be gated.)

What it's good at (and what it isn't)

RunScope is for enumerable work — loops over files, records, images, tiles, simulations, parameter grids, API calls. That covers a huge amount of scientific and data-processing work.

It does not try to predict the runtime of an arbitrary opaque operation with no sub-steps and no history. When there isn't enough information to estimate honestly, it tells you so instead of inventing a number. That restraint is on purpose.

The science

RunScope's estimators are not heuristics someone made up. They come from a research program (ETA-Proto) that tested dozens of ETA methods against a simple baseline under preregistered pass/fail gates and kept only what won by a required margin. The core finding: for enumerable jobs, a size-weighted estimate is very hard to beat — except by measuring a small sample of the unexecuted work, which cut remaining-time error 40–90% on hard, heterogeneous workloads. That measurement is the measure=True mode.

License

Apache-2.0.

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