⚠️ WIP: All 0.1.x releases are unstable. 0.2.0 will be the first stable, production-ready release.
Releases >0.1.3 are functional and ready for testing, but the API is still subject to change.
frameworthy
Lightweight statistical validation library for data changes. Built for engineers and scientists who need to validate data changes with statistical rigor. Works in data validation pipelines, in tests with assertions, or in exploratory settings with easily inspectable results.
Getting Started
Installation
Available on PyPI, use pip or your preferred package manager.
pip install frameworthy
# or
uv add frameworthy
Examples
See scripts/examples.py for a few quick examples.
import frameworthy as fw
import polars as pl # or pandas
# load your data if necessary
before_df = pl.read_csv("before.csv")
after_df = pl.read_csv("after.csv")
# run a check
result = (
fw.check(after_df, before=before_df)
.mean("column_name")
.equivalent(within=0.1)
)
# inspect the results
print(result)
# or raise an exception on failure
result.assert_passed()
Usage
Bring your data: two pandas/polars DataFrames (before and after / pre and post).
A standard frameworthy check looks like this:
fw.check(after_df, before_df).mean("column_name").equivalent(within=0.1)
- Start a check with
fw.check(after_df, before_df) - Specify the metric to check, with
.mean("column_name") - Make a claim about the change, using
.equivalent(),.change_greater_than(), or.change_less_than() - Examine the results or assert that the check passed with
.assert_passed()for testing
Methodology
These are the most important notes to be aware of for correct usage. For further details, see the more extensive docs.
Confidence Intervals
The parameter alpha is a one-sided significance level everywhere; .equivalent()'s displayed CI is (1-2α), not (1-α). This is to maintain consistency with the TOST (Two One-Sided Tests) equivalence testing method.
Examples:
.equivalent()alpha=0.05→ 90% CIalpha=0.025→ 95% CI
.change_greater_than()and.change_less_than()alpha=0.1→ 90% CIalpha=0.05→ 95% CI
Development
To run the tests:
make test
To run the examples:
uv run scripts/examples.py
License
MIT, but attribution is appreciated.
Metadata
Release files for frameworthy 0.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| frameworthy-0.1.5.tar.gz | 19.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| frameworthy-0.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 44.3 kB
Release files / frameworthy-0.1.5.tar.gz
| Download URL | frameworthy-0.1.5.tar.gz |
|---|---|
| Size | 19.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / frameworthy-0.1.5-py3-none-any.whl
| Download URL | frameworthy-0.1.5-py3-none-any.whl |
|---|---|
| Size | 24.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 11, 2026.
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