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"""
Cannabis Licenses | Get Vermont 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: 10/7/2022
License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
Description:
Collect Vermont cannabis license data.
Data Source:
- Vermont
URL: <https://ccb.vermont.gov/licenses>
"""
# 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/vt'
ENV_FILE = '../.env'
# Specify state-specific constants.
STATE = 'VT'
VERMONT = {
'licensing_authority_id': 'VTCCB',
'licensing_authority': 'Vermont Cannabis Control Board',
'licenses_url': 'https://ccb.vermont.gov/licenses',
'licenses': {
'licensedcultivators': {
'columns': [
'business_legal_name',
'license_type',
'address',
'license_designation',
],
},
'outdoorcultivators': {
'columns': [
'business_legal_name',
'license_type',
'premise_city',
'license_designation',
],
},
'mixedcultivators': {
'columns': [
'business_legal_name',
'license_type',
'premise_city',
'license_designation',
],
},
'testinglaboratories': {
'columns': [
'business_legal_name',
'license_type',
'premise_city',
'license_designation',
'address'
],
},
'integrated': {
'columns': [
'business_legal_name',
'license_type',
'premise_city',
'license_designation',
],
},
'retailers': {
'columns': [
'business_legal_name',
'license_type',
'address',
'license_designation',
],
},
'manufacturers': {
'columns': [
'business_legal_name',
'license_type',
'premise_city',
'license_designation',
],
},
'wholesalers': {
'columns': [
'business_legal_name',
'license_type',
'premise_city',
'license_designation',
],
},
},
}
def get_licenses_vt(
data_dir: Optional[str] = None,
env_file: Optional[str] = '.env',
):
"""Get Vermont cannabis license data."""
# Get the licenses from the webpage.
url = VERMONT['licenses_url']
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
# Parse the various table types.
data = []
for license_type, values in VERMONT['licenses'].items():
columns = values['columns']
table = block = soup.find(attrs={'id': f'block-{license_type}'})
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)
# Standardize the licenses.
licenses = pd.DataFrame(data)
licenses['id'] = licenses.index
licenses['license_number'] = None # FIXME: It would be awesome to find these!
licenses['licensing_authority_id'] = VERMONT['licensing_authority_id']
licenses['licensing_authority'] = VERMONT['licensing_authority']
licenses['license_designation'] = 'Adult-Use'
licenses['premise_state'] = STATE
licenses['license_status'] = None
licenses['license_status_date'] = None
licenses['license_term'] = None
licenses['issue_date'] = None
licenses['expiration_date'] = None
licenses['business_owner_name'] = None
licenses['business_structure'] = None
licenses['activity'] = None
licenses['parcel_number'] = None
licenses['business_phone'] = None
licenses['business_email'] = None
licenses['business_image_url'] = None
licenses['business_website'] = None
# Separate the `license_designation` from `license_type` if (Tier x).
criterion = licenses['license_type'].str.contains('Tier ')
licenses.loc[criterion, 'license_designation'] = licenses.loc[criterion]['license_type'].apply(
lambda x: 'Tier ' + x.split('(Tier ')[1].rstrip(')')
)
licenses.loc[criterion, 'license_type'] = licenses.loc[criterion]['license_type'].apply(
lambda x: x.split('(Tier ')[0].strip()
)
# Separate labs' `business_email` and `business_phone` from the `address`.
criterion = licenses['license_type'] == 'Testing Lab'
licenses.loc[criterion, 'business_email'] = licenses.loc[criterion]['address'].apply(
lambda x: x.split('Email: ')[-1].rstrip('\n') if isinstance(x, str) else x
)
licenses.loc[criterion, 'business_phone'] = licenses.loc[criterion]['address'].apply(
lambda x: x.split('Phone: ')[-1].split('Email: ')[0].rstrip('\n') if isinstance(x, str) else x
)
licenses.loc[criterion, 'address'] = licenses.loc[criterion]['address'].apply(
lambda x: x.split('Phone: ')[0].replace('\n', ' ').strip() if isinstance(x, str) else x
)
# Split any DBA from the legal name.
splits = [';', 'DBA - ', '(DBA)', 'DBA ', 'dba ']
licenses['business_dba_name'] = licenses['business_legal_name']
for split in splits:
criterion = licenses['business_legal_name'].str.contains(split)
licenses.loc[criterion, 'business_dba_name'] = licenses.loc[criterion]['business_legal_name'].apply(
lambda x: x.split(split)[1].replace(')', '').strip() if split in x else x
)
licenses.loc[criterion, 'business_legal_name'] = licenses.loc[criterion]['business_legal_name'].apply(
lambda x: x.split(split)[0].replace('(', '').strip()
)
licenses.loc[licenses['business_legal_name'] == '', 'business_legal_name'] = licenses['business_dba_name']
# Get the refreshed date.
licenses['data_refreshed_date'] = datetime.now().isoformat()
# Geocode the licenses.
# FIXME: There are some wonky addresses that are output!
config = dotenv_values(env_file)
google_maps_api_key = config['GOOGLE_MAPS_API_KEY']
licenses = geocode_addresses(
licenses,
api_key=google_maps_api_key,
address_field='address',
)
licenses['premise_street_address'] = licenses['formatted_address'].apply(
lambda x: x.split(',')[0] if STATE in str(x) else x
)
licenses['premise_city'] = licenses['formatted_address'].apply(
lambda x: x.split(', ')[1].split(',')[0] if STATE in str(x) else x
)
licenses['premise_zip_code'] = licenses['formatted_address'].apply(
lambda x: x.split(', ')[2].split(',')[0].split(' ')[-1] if STATE in str(x) else x
)
drop_cols = ['state', 'state_name', 'address', 'formatted_address']
licenses.drop(columns=drop_cols, inplace=True)
gis_cols = {
'county': 'premise_county',
'latitude': 'premise_latitude',
'longitude': 'premise_longitude'
}
licenses.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 = licenses.loc[licenses['license_type'] == 'Retail']
licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False)
retailers.to_csv(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
return licenses
# === Test ===
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_vt(data_dir, env_file=env_file)
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