Skip to main content

searching for software promises in grant applications

Project description

soft-search

Build Status Documentation

searching for software promises in grant applications


Installation

Stable Release: pip install soft-search
Development Head: pip install git+https://github.com/PugetSoundClinic-PIT/soft-search.git

Quickstart

Apply our Pre-trained Transformer

from soft_search import constants, nsf
from soft_search.label import transformer
df = nsf.get_nsf_dataset(
    "2016-01-01",
    "2017-01-01",
    dataset_fields=[constants.NSFFields.abstractText],
)
predicted = transformer.label(
    df,
    apply_column=constants.NSFFields.abstractText,
)

Documentation

For full package documentation please visit PugetSoundClinic-PIT.github.io/soft-search.

Development

See CONTRIBUTING.md for information related to developing the code.

MIT License

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

soft-search-0.2.0.tar.gz (100.4 kB view hashes)

Uploaded Source

Built Distribution

soft_search-0.2.0-py3-none-any.whl (97.0 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page