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"""
Cannabis Licenses | Get Rhode Island 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: 10/3/2022
License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
Description:
Collect Rhode Island cannabis license data.
Data Source:
- Rhode Island
URL: <https://dbr.ri.gov/office-cannabis-regulation/compassion-centers/licensed-compassion-centers>
"""
# Standard imports.
from datetime import datetime
import os
from typing import Optional
# External imports.
from bs4 import BeautifulSoup
from cannlytics.data.gis import geocode_addresses
from dotenv import dotenv_values
import pandas as pd
import requests
# Specify where your data lives.
DATA_DIR = '../data/ri'
ENV_FILE = '../.env'
# Specify state-specific constants.
STATE = 'RI'
RHODE_ISLAND = {
'licensing_authority_id': 'RIDBH',
'licensing_authority': 'Rhode Island Department of Business Regulation',
'retailers': {
'url': 'https://dbr.ri.gov/office-cannabis-regulation/compassion-centers/licensed-compassion-centers',
'columns': [
'license_number',
'business_legal_name',
'address',
'business_phone',
'license_designation',
],
}
}
def get_licenses_ri(
data_dir: Optional[str] = None,
env_file: Optional[str] = '.env',
):
"""Get Rhode Island cannabis license data."""
# Get the licenses webpage.
url = RHODE_ISLAND['retailers']['url']
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
# Parse the table data.
data = []
columns = RHODE_ISLAND['retailers']['columns']
table = soup.find('table')
rows = table.find_all('tr')
for row in rows[1:]:
cells = row.find_all('td')
obs = {}
for i, cell in enumerate(cells):
column = columns[i]
obs[column] = cell.text
data.append(obs)
# Optional: It's possible to download the certificate to get it's `issue_date`.
# Standardize the license data.
retailers = pd.DataFrame(data)
retailers['id'] = retailers['license_number']
retailers['licensing_authority_id'] = RHODE_ISLAND['licensing_authority_id']
retailers['licensing_authority'] = RHODE_ISLAND['licensing_authority']
retailers['premise_state'] = STATE
retailers['license_type'] = 'Commercial - Retailer'
retailers['license_status'] = 'Active'
retailers['license_status_date'] = None
retailers['license_term'] = None
retailers['issue_date'] = None
retailers['expiration_date'] = None
retailers['business_owner_name'] = None
retailers['business_structure'] = None
retailers['business_email'] = None
retailers['activity'] = None
retailers['parcel_number'] = None
retailers['business_image_url'] = None
retailers['business_website'] = None
# Correct `license_designation`.
coding = dict(Yes='Adult Use and Cultivation', No='Adult Use')
retailers['license_designation'] = retailers['license_designation'].map(coding)
# Correct `business_dba_name`.
criterion = retailers['business_legal_name'].str.contains('D/B/A')
retailers['business_dba_name'] = retailers['business_legal_name']
retailers.loc[criterion, 'business_dba_name'] = retailers['business_legal_name'].apply(
lambda x: x.split('D/B/A')[1].strip() if 'D/B/A' in x else x
)
retailers.loc[criterion, 'business_legal_name'] = retailers['business_legal_name'].apply(
lambda x: x.split('D/B/A')[0].strip()
)
criterion = retailers['business_legal_name'].str.contains('F/K/A')
retailers.loc[criterion, 'business_dba_name'] = retailers['business_legal_name'].apply(
lambda x: x.split('F/K/A')[1].strip() if 'D/B/A' in x else x
)
retailers.loc[criterion, 'business_legal_name'] = retailers['business_legal_name'].apply(
lambda x: x.split('F/K/A')[0].strip()
)
# Get the refreshed date.
par = soup.find_all('p')[-1]
date = par.text.split('updated on ')[-1].split('.')[0]
retailers['data_refreshed_date'] = pd.to_datetime(date).isoformat()
# Geocode the licenses.
config = dotenv_values(env_file)
google_maps_api_key = config['GOOGLE_MAPS_API_KEY']
retailers = geocode_addresses(
retailers,
api_key=google_maps_api_key,
address_field='address',
)
retailers['premise_street_address'] = retailers['formatted_address'].apply(
lambda x: x.split(',')[0]
)
retailers['premise_city'] = retailers['formatted_address'].apply(
lambda x: x.split(', ')[1].split(',')[0]
)
retailers['premise_zip_code'] = retailers['formatted_address'].apply(
lambda x: x.split(', ')[2].split(',')[0].split(' ')[-1]
)
drop_cols = ['state', 'state_name', 'address', 'formatted_address']
retailers.drop(columns=drop_cols, inplace=True)
gis_cols = {
'county': 'premise_county',
'latitude': 'premise_latitude',
'longitude': 'premise_longitude'
}
retailers.rename(columns=gis_cols, inplace=True)
# Save and return the data.
if data_dir is not None:
if not os.path.exists(data_dir): os.makedirs(data_dir)
timestamp = datetime.now().isoformat()[:19].replace(':', '-')
retailers.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False)
return retailers
if __name__ == '__main__':
# Support command line usage.
import argparse
try:
arg_parser = argparse.ArgumentParser()
arg_parser.add_argument('--d', dest='data_dir', type=str)
arg_parser.add_argument('--data_dir', dest='data_dir', type=str)
arg_parser.add_argument('--env', dest='env_file', type=str)
args = arg_parser.parse_args()
except SystemExit:
args = {'d': DATA_DIR, 'env_file': ENV_FILE}
# Get licenses, saving them to the specified directory.
data_dir = args.get('d', args.get('data_dir'))
env_file = args.get('env_file')
data = get_licenses_ri(data_dir, env_file=env_file)
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