""" Cannabis Licenses | Get Vermont Licenses Copyright (c) 2022 Cannlytics Authors: Keegan Skeate Candace O'Sullivan-Sutherland Created: 9/29/2022 Updated: 10/7/2022 License: Description: Collect Vermont cannabis license data. Data Source: - Vermont URL: """ # 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)