Install & Compatibility
Where this runs
tested against v0.0.2 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.910 runs
installs and imports cleanly · install 0.0s · import 0.000s · 253.4MB
glibcpy 3.10–3.910 runs
installs and imports cleanly · install 12.4s · import 0.000s · 242MB
256MB installed
● package 256MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
bootstrap
✓ import bootstrapped
✗ import bootstrapped.bootstrap as bs
This quickstart demonstrates how to generate sample data and then compute a 95% confidence interval for the mean using the `bootstrap` function from `bootstrapped.bootstrap` and the `mean` statistic function from `bootstrapped.stats_functions`.
import numpy as np
import bootstrapped.bootstrap as bs
import bootstrapped.stats_functions as sf
# Generate some data
data = np.random.normal(loc=100, scale=10, size=100)
# Calculate 95% confidence interval for the mean
lower_bound, upper_bound = bs.bootstrap(data, stat_func=sf.mean, alpha=0.05, num_iterations=1000)
print(f"Mean 95% CI: [{lower_bound:.2f}, {upper_bound:.2f}]")
Debug
Known issues
breakingThis library has not been updated since September 2017. It is highly likely to have compatibility issues with newer versions of Python (e.g., Python 3.8+), NumPy, or SciPy, and may contain unpatched security vulnerabilities.fixIt is strongly recommended to migrate to actively maintained modern statistical libraries such as `scipy.stats.bootstrap` (available since SciPy 1.6.0) or `arch` for bootstrap methods, which offer similar or enhanced functionality with active development and broader compatibility.
affects: 0.0.2 and earlier
gotchaThe `bootstrapped` package's `num_iterations` parameter refers to the number of bootstrap resamples, not actual iterations of an algorithm. A higher number typically yields more stable results for confidence intervals.fixEnsure `num_iterations` is set to a sufficiently large number (e.g., 1000 or 10000) for reliable confidence intervals, understanding it controls the number of resamples rather than convergence of an iterative process.
affects: 0.0.2
gotchaThe library is maintained under `facebookincubator`, which implies it was an experimental project and not necessarily a fully supported product. This further emphasizes its abandoned status and lack of official support.fixUsers should be aware that this project is not actively maintained or supported by Meta (Facebook) and should not be relied upon for production systems or critical analyses without significant independent validation.
affects: 0.0.2
Upgrade
Version history
0.0.2latest on PyPI · released Oct 17, 2018
Audit
Dependencies
numpyrequiredCore array operations and numerical computations.
scipyrequiredStatistical functions and underlying numerical routines.