Registry / ai-ml / facets-overview

facets-overview

library1.1.1pypypi✓ verified 86d ago

Facets Overview is a Python library that generates interactive visualizations for analyzing machine learning datasets. It processes data into protobufs, which are then rendered by front-end web components (Polymer). The library is currently at version 1.1.1, with the last release in 2017, indicating it is no longer actively maintained.

ai-ml data serialization

pip install facets-overview

github ↗package ↗

INSTALL

IMPORT

SIG · FACETS-OVERVIEW

facets-overview

ai-mlpythonv1.1.1

Install

8.1s avg

Import

1113ms

Disk

166MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.1.1 · 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

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 1.274s · 166.4MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 8.1s · import 0.951s · 159MB

166MB installed

● package 166MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

GenericFeatureStatisticsGenerator

✓ from facets_overview.generic_feature_statistics_generator import GenericFeatureStatisticsGenerator

Main class for generating feature statistics protobufs.

FeatureStatisticsList

✓ from facets_overview.feature_statistics_pb2 import FeatureStatisticsList

Protobuf definition for feature statistics.

This quickstart demonstrates how to generate and display a Facets Overview visualization within a Jupyter Notebook. It uses `pandas` for data handling and `IPython.display` to render the interactive HTML. Note that this requires the `facets_overview` Jupyter nbextension to be enabled and an environment compatible with Polymer 2.

import pandas as pd from facets_overview.generic_feature_statistics_generator import GenericFeatureStatisticsGenerator from IPython.display import display, HTML # Example data data = [ {'feature1': 1, 'feature2': 'cat'}, {'feature1': 2, 'feature2': 'dog'}, {'feature1': 3, 'feature2': 'cat'} ] df = pd.DataFrame(data) # Create the FeatureStatisticsList proto for Facets Overview. gfsg = GenericFeatureStatisticsGenerator() overview_proto = gfsg.CreateFeatureStatisticsListFromDataFrame(df) protostr = overview_proto.SerializeToString().decode('utf-8') # Display the Facets Overview UI (requires Jupyter Notebook and nbextension enabled) HTML_TEMPLATE = """<link rel="import" href="/nbextensions/facets_overview/facets-overview.html"> <facets-overview id="facets-overview"></facets-overview> <script> document.querySelector("#facets-overview").protoInput = "{protostr}"; </script>""" html_output = HTML_TEMPLATE.format(protostr=protostr) display(HTML(html_output))

Debug

Known issues

breakingThe v1.0.0 release updated the underlying web component technology from Polymer 1 to Polymer 2. This can break existing display mechanisms or require browser environment updates.

fix

Ensure your Jupyter environment and browser are compatible with Polymer 2. Running old notebooks may require adjustments or specific browser versions.

affects: >=1.0.0

deprecatedFacets Overview is an abandoned library, with the last release in 2017. It relies on deprecated front-end technologies (Polymer 1/2) and older Python practices, making it largely incompatible with modern web browsers, JupyterLab, and newer Python versions (3.8+).

fix

Consider migrating to actively maintained data exploration and visualization libraries such as `pandas-profiling`, `sweetviz`, `explori`, or `TensorFlow Data Validation` (the spiritual successor by Google).

affects: all

gotchaThe display mechanism is tightly coupled to Jupyter Notebooks via nbextensions. It does not natively support JupyterLab or other Python environments without significant workarounds.

fix

Ensure you are running in a classic Jupyter Notebook environment with the `facets_overview` nbextension enabled. For JupyterLab, manual configuration or alternative rendering methods would be required, which are not officially supported.

affects: all

gotchaFacets Overview uses Google Protobuf for data serialization. There are known compatibility issues with newer `protobuf` library versions, leading to `DecodeError` or `TypeError` exceptions.

fix

Pin the `protobuf` library to an older, compatible version (e.g., `pip install protobuf<3.20`). Experimentation may be required to find a working version for your specific setup.

affects: all

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'facets_overview'

The `facets-overview` package is not installed in your current Python environment.

fix

Run `pip install facets-overview` to install the library.

google.protobuf.message.DecodeError: Error parsing message

This error often indicates a version mismatch between the `protobuf` library installed in your environment and the `protobuf` version used to compile the `.proto` definitions within `facets-overview`.

fix

Try installing an older version of the `protobuf` library: `pip install protobuf<3.20` (or `protobuf==3.19.0` for a specific version known to work with older Google libraries).

Javascript errors in browser console related to '<link rel="import">' or Polymer

Facets Overview relies on deprecated Web Components v0 APIs (Polymer 1/2 and HTML Imports). Modern browsers have removed support for these features.

fix

This is a fundamental limitation of an abandoned library. There is no simple fix for modern browsers. You might need to use an older browser version or a specific environment where these legacy web components are still supported.

AttributeError: 'HTML' object has no attribute '_repr_html_' (or similar non-rendering behavior in JupyterLab)

The visualization relies on Jupyter Notebook nbextensions for rendering and does not have native support or an easy integration path for JupyterLab or other environments.

fix

Ensure you are running in a classic Jupyter Notebook and that the `facets_overview` nbextension is enabled (`jupyter nbextension enable --py facets_overview`). For JupyterLab, consider using alternative libraries.

Upgrade

Version history

1.1.1latest on PyPI · released May 24, 2023

Audit

Dependencies

No dependency data recorded yet.

Agent activity

9 hits · last 30 days

node

OpenAI (training)

Resources

githubhttp://github.com/pair-code/facets ↗

packagehttps://pypi.org/project/facets-overview/ ↗