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"""
Cannabis Licenses
Copyright (c) 2022 Cannlytics
Authors:
Keegan Skeate <https://github.com/keeganskeate>
Candace O'Sullivan-Sutherland <https://github.com/candy-o>
Created: 9/29/2022
Updated: 9/29/2022
License: <https://huggingface.co/datasets/cannlytics/cannabis_licenses/blob/main/LICENSE>
"""
# Standard imports.
import json
# External imports.
import datasets
import pandas as pd
# Constants.
_VERSION = '1.0.0'
_HOMEPAGE = 'https://huggingface.co/datasets/cannlytics/cannabis_licenses'
_LICENSE = "https://opendatacommons.org/licenses/by/4-0/"
_DESCRIPTION = """\
Cannabis Licenses (https://cannlytics.com/data/licenses) is a
dataset of curated cannabis license data. The dataset consists of 16
sub-datasets for each state with permitted adult-use cannabis, as well
as a sub-dataset that includes all licenses.
"""
_CITATION = """\
@inproceedings{cannlytics2022cannabis_licenses,
author = {Skeate, Keegan and O'Sullivan-Sutherland, Candace},
title = {Cannabis Licenses},
booktitle = {Cannabis Data Science},
month = {September},
year = {2022},
address = {United States of America},
publisher = {Cannlytics}
}
"""
# Dataset fields.
FIELDS = datasets.Features({
'id': datasets.Value(dtype='string'),
'license_number': datasets.Value(dtype='string'),
'license_status': datasets.Value(dtype='string'),
'license_status_date': datasets.Value(dtype='string'),
'license_term': datasets.Value(dtype='string'),
'license_type': datasets.Value(dtype='string'),
'issue_date': datasets.Value(dtype='string'),
'expiration_date': datasets.Value(dtype='string'),
'licensing_authority_id': datasets.Value(dtype='string'),
'licensing_authority': datasets.Value(dtype='string'),
'business_legal_name': datasets.Value(dtype='string'),
'business_dba_name': datasets.Value(dtype='string'),
'business_owner_name': datasets.Value(dtype='string'),
'business_structure': datasets.Value(dtype='string'),
'activity': datasets.Value(dtype='string'),
'premise_street_address': datasets.Value(dtype='string'),
'premise_city': datasets.Value(dtype='string'),
'premise_state': datasets.Value(dtype='string'),
'premise_county': datasets.Value(dtype='string'),
'premise_zip_code': datasets.Value(dtype='string'),
'business_email': datasets.Value(dtype='string'),
'business_phone': datasets.Value(dtype='string'),
'parcel_number': datasets.Value(dtype='string'),
'premise_latitude': datasets.Value(dtype='float'),
'premise_longitude': datasets.Value(dtype='float'),
'data_refreshed_date': datasets.Value(dtype='string'),
})
# Read dataset subsets.
with open('subsets.json', 'r') as f:
SUBSETS = json.loads(f.read())
class CannabisLicensesConfig(datasets.BuilderConfig):
"""BuilderConfig for Cannabis Licenses."""
def __init__(self, name, **kwargs):
"""BuilderConfig for Cannabis Licenses.
Args:
name (str): Configuration name that determines setup.
**kwargs: Keyword arguments forwarded to super.
"""
description = _DESCRIPTION
description += f'This configuration is for the `{name}` subset.'
super().__init__(name=name, description=description, **kwargs)
class CannabisLicenses(datasets.GeneratorBasedBuilder):
"""The Cannabis Licenses dataset."""
VERSION = datasets.Version(_VERSION)
BUILDER_CONFIG_CLASS = CannabisLicensesConfig
BUILDER_CONFIGS = [CannabisLicensesConfig(s) for s in SUBSETS.keys()]
DEFAULT_CONFIG_NAME = 'ca'
def _info(self):
"""Returns the dataset metadata."""
return datasets.DatasetInfo(
features=FIELDS,
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
description=_DESCRIPTION,
license=_LICENSE,
version=_VERSION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
config_name = self.config.name
data_url = SUBSETS[config_name]['data_url']
urls = {config_name: data_url}
downloaded_files = dl_manager.download_and_extract(urls)
filepath = downloaded_files[config_name]
params = {'filepath': filepath}
return [datasets.SplitGenerator(name='data', gen_kwargs=params)]
def _generate_examples(self, filepath):
"""Returns the examples in raw text form."""
with open(filepath) as f:
df = pd.read_csv(filepath)
for index, row in df.iterrows():
obs = row.to_dict()
yield index, obs
# === Test ===
if __name__ == '__main__':
from datasets import load_dataset
# Load the dataset.
dataset = load_dataset('cannabis_licenses.py', 'ca')
data = dataset['data']
assert len(data) > 0
print('Read %i licenses.' % len(data))
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