piedomains 0.0.1

Predict categories based domain names and it's content

This package used Shallalist dataset to train the model. Scrapped homepages of the domains mentioned in above dataset. This package predicts the category based on the domain name and its content.

Install

We strongly recommend installing piedomains inside a Python virtual environment (see venv documentation)

pip install piedomains

General API

1. domain.pred_shalla_cat will take array of domains and predicts category.

Examples

from piedomains import domain
domains = [
    "yahoo.com",
    "forbes.com",
    "xvideos.com",
    "last.fm",
    "facebook.com",
    "bellesa.co",
    "marketwatch.com"
]
result = domain.pred_shalla_cat(domains)
print(result)

Output -

              name pred_label  label_prob                                   all_domain_probs
0        yahoo.com       news    0.020277  {'adv': 0.01923918, 'aggressive': 0.018240146,...
1       forbes.com       news    0.024546  {'adv': 0.019166455, 'aggressive': 0.018233137...
2      xvideos.com       porn    0.023876  {'adv': 0.021233741, 'aggressive': 0.018176464...
3          last.fm      music    0.021811  {'adv': 0.018456697, 'aggressive': 0.018200265...
4     facebook.com       news    0.020649  {'adv': 0.018711654, 'aggressive': 0.01822204,...
5       bellesa.co       porn    0.021210  {'adv': 0.019019566, 'aggressive': 0.018217055...
6  marketwatch.com    finance    0.024212  {'adv': 0.018773649, 'aggressive': 0.018179242...

Functions

We expose 1 function, which will take array of domains and predicts category.

• domain.pred_shalla_cat(input)

  • What it does:

    • predicts category based on domain and its content

  • Output

    • Returns panda dataframe with label and probabilities

Authors

Rajashekar Chintalapati and Gaurav Sood

Contributor Code of Conduct

The project welcomes contributions from everyone! In fact, it depends on it. To maintain this welcoming atmosphere, and to collaborate in a fun and productive way, we expect contributors to the project to abide by the Contributor Code of Conduct.

License

The package is released under the MIT License.