{"id":9557,"library":"bootstrapped","title":"Bootstrapped Percentile Bootstrap","description":"The `bootstrapped` library provides implementations of percentile-based bootstrap methods for statistical analysis, primarily focusing on confidence intervals. It is currently at version 0.0.2, with its last release in September 2017, indicating a stalled or abandoned release cadence.","status":"abandoned","version":"0.0.2","language":"en","source_language":"en","source_url":"https://github.com/facebookincubator/bootstrapped","tags":["statistics","bootstrap","data science","confidence intervals","facebook"],"install":[{"cmd":"pip install bootstrapped","lang":"bash","label":"Install stable version"}],"dependencies":[{"reason":"Core array operations and numerical computations.","package":"numpy","optional":false},{"reason":"Statistical functions and underlying numerical routines.","package":"scipy","optional":false}],"imports":[{"note":"`bootstrap` is a submodule, not directly available under the top-level package.","wrong":"import bootstrapped as bs; bs.bootstrap(...)","symbol":"bootstrap","correct":"import bootstrapped.bootstrap as bs"},{"note":"Common practice is to import as `sf` for convenience, but direct import also works.","wrong":"from bootstrapped import stats_functions","symbol":"stats_functions","correct":"import bootstrapped.stats_functions as sf"}],"quickstart":{"code":"import numpy as np\nimport bootstrapped.bootstrap as bs\nimport bootstrapped.stats_functions as sf\n\n# Generate some data\ndata = np.random.normal(loc=100, scale=10, size=100)\n\n# Calculate 95% confidence interval for the mean\nlower_bound, upper_bound = bs.bootstrap(data, stat_func=sf.mean, alpha=0.05, num_iterations=1000)\n\nprint(f\"Mean 95% CI: [{lower_bound:.2f}, {upper_bound:.2f}]\")\n","lang":"python","description":"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`."},"warnings":[{"fix":"It 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.","message":"This 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.","severity":"breaking","affected_versions":"0.0.2 and earlier"},{"fix":"Ensure `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.","message":"The `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.","severity":"gotcha","affected_versions":"0.0.2"},{"fix":"Users 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.","message":"The 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.","severity":"gotcha","affected_versions":"0.0.2"}],"env_vars":null,"last_verified":"2026-04-17T00:00:00.000Z","next_check":"2026-07-16T00:00:00.000Z","problems":[{"fix":"pip install bootstrapped","cause":"The 'bootstrapped' package is not installed in the current Python environment.","error":"ModuleNotFoundError: No module named 'bootstrapped'"},{"fix":"This often indicates a fundamental incompatibility with modern Python environments. It's recommended to try to replicate the original environment (e.g., Python 3.6, NumPy 1.12.x) or, preferably, migrate to `scipy.stats.bootstrap` or another actively maintained library.","cause":"This error or similar type-related issues can occur due to strict type checking or implicit conversion changes in newer Python or NumPy versions, conflicting with the old code base of 'bootstrapped'.","error":"TypeError: 'numpy.float64' object cannot be interpreted as an integer"},{"fix":"Use `import bootstrapped.bootstrap as bs` and then call `bs.bootstrap(...)`.","cause":"The `bootstrap` function is located within the `bootstrapped.bootstrap` submodule, not directly in the top-level `bootstrapped` package.","error":"AttributeError: module 'bootstrapped' has no attribute 'bootstrap'"}]}