Metadata-Version: 2.1
Name: hover
Version: 0.2.2
Summary: Data annotation done right: easy, fun, hyper-productive, and inducing insight.
Home-page: https://github.com/phurwicz/hover
Author: Pavel
Author-email: pavelhurwicz@gmail.com
License: UNKNOWN
Description: # Hover
        
        [![PyPI Stage](https://img.shields.io/pypi/status/hover?style=for-the-badge)](https://pypi.org)
        [![PyPI Version](https://img.shields.io/pypi/v/hover?style=for-the-badge)](https://pypi.org)
        [![Travis CI](https://img.shields.io/travis/com/phurwicz/hover/main?style=for-the-badge)](https://travis-ci.com)
        [![Codacy Grade](https://img.shields.io/codacy/grade/689827d9077b43ac8721c7658d122d1a?style=for-the-badge)](https://www.codacy.com)
        [![Codacy Coverage](https://img.shields.io/codacy/coverage/689827d9077b43ac8721c7658d122d1a/main?style=for-the-badge)](https://www.codacy.com)
        
        [![Demo](docs/images/app-linked-annotator.gif)
        
        ----
        
        `Hover` is a **machine teaching** library that enables intuitive and effecient supervision. In other words, it provides a map where you _hover_ over and label your data... differently. For instance, you can:
        
        -   [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/phurwicz/hover-binder/master?urlpath=/proxy/5006/app-simple-annotator) :seedling: annotate an intuitively selected group of data points at a time
        -   [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/phurwicz/hover-binder/master?urlpath=/proxy/5006/app-snorkel-annotator) :whale: cross-check with Snorkel-based distant supervision
        -   [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/phurwicz/hover-binder/master?urlpath=/proxy/5006/app-active-annotator) :ferris_wheel: **UPCOMING** throw a model in the loop and take advantage of active learning
        
        Check out [@phurwicz/hover-binder](https://github.com/phurwicz/hover-binder) for a complete list of demo apps.
        
        ## Features
        
        Here we attempt a quick comparison with a few other packages that do machine teaching:
        
        Package        | `Hover`                               | `Prodigy`                               | `Snorkel`
        -------------- | ------------------------------------- | --------------------------------------- | -------------------------
        Core idea      | supervise like painting a picture     | scriptable active learning              | programmatic distant supervision
        Annotates per  | batch of just the size you find right | piece predicted to be the most valuable | the whole dataset as long as it fits in
        Supports       | all classification (text only atm)    | text & images, audio, vidio, & more     | text classification (for the most part)
        Status         | open-source                           | proprietary                             | open-source
        Devs           | indie                                 | Explosion AI                            | Stanford / Snorkel AI
        Related        | many imports of the awesome `Bokeh`   | builds on the `Thinc`/`SpaCy` stack     | Variants: `Snorkel Drybell`, `MeTaL`, `DeepDive`
        Vanilla usage  | define a vectorizer and annotate away | choose a base model and annotate away   | define labeling functions and apply away
        Advanced usage | combine w/ active learning & snorkel  | patterns / transformers / custom models | transforming / slicing functions
        Hardcore usage | exploit `hover.core` templates        | custom @prodigy.recipe                  | the upcoming `Snorkel Flow`
        
        `Hover` claims the best deal of scale vs. precision thanks to
        
        -   the flexibility to use, or not use, any technique beyond annotating on a "map";
        -   the speed, or coarseness, of annotation being _literally at your fingertips_;
        -   the interaction between multiple "maps" that each serves a different but connected purpose.
        
        ## Installation
        
        To get the latest release version, you can use `pip`:
        
        ```bash
        pip install hover
        ```
        
        Installation through `conda` is not yet supported.
        
        ## Resources
        
        -   [Documentation](https://phurwicz.github.io/hover/)
        
        ## Dependencies
        
        -   `./requirements.txt` lists the dependencies for installation.
        -   `./requirements-test.txt` lists additional dependencies for the test suite.
        -   `./requirements-dev.txt` lists the packages for developers.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6, <3.9
Description-Content-Type: text/markdown
