""" Cannabis Licenses | Get Maine Licenses Copyright (c) 2022 Cannlytics Authors: Keegan Skeate Candace O'Sullivan-Sutherland Created: 9/29/2022 Updated: 10/7/2022 License: Description: Collect Maine cannabis license data. Data Source: - Maine Office of Cannabis Policy 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/me' ENV_FILE = '../.env' # Specify state-specific constants. STATE = 'ME' MAINE = { 'licensing_authority_id': 'MEOCP', 'licensing_authority': 'Maine Office of Cannabis Policy', 'licenses': { 'url': 'https://www.maine.gov/dafs/ocp/open-data/adult-use', 'key': 'Adult_Use_Establishments_And_Contacts', 'columns': { 'LICENSE': 'license_number', 'LICENSE_CATEGORY': 'license_type', 'LICENSE_TYPE': 'license_designation', 'LICENSE_NAME': 'business_legal_name', 'DBA': 'business_dba_name', 'LICENSE_STATUS': 'license_status', 'LICENSE_CITY': 'premise_city', 'WEBSITE': 'business_website', 'CONTACT_NAME': 'business_owner_name', 'CONTACT_TYPE': 'contact_type', 'CONTACT_CITY': 'contact_city', 'CONTACT_DESCRIPTION': 'contact_description', }, } } def get_licenses_me( data_dir: Optional[str] = None, env_file: Optional[str] = '.env', ): """Get Maine cannabis license data.""" # Create the necessary directories. file_dir = f'{data_dir}/.datasets' if not os.path.exists(data_dir): os.makedirs(data_dir) if not os.path.exists(file_dir): os.makedirs(file_dir) # Get the download link. licenses_url = None licenses_key = MAINE['licenses']['key'] url = MAINE['licenses']['url'] response = requests.get(url) soup = BeautifulSoup(response.content, 'html.parser') links = soup.find_all('a') for link in links: try: href = link['href'] except KeyError: continue if licenses_key in href: licenses_url = href break # Download the licenses workbook. filename = licenses_url.split('/')[-1].split('?')[0] licenses_source_file = os.path.join(file_dir, filename) response = requests.get(licenses_url) with open(licenses_source_file, 'wb') as doc: doc.write(response.content) # Extract the data from the license workbook. licenses = pd.read_excel(licenses_source_file) licenses.rename(columns=MAINE['licenses']['columns'], inplace=True) licenses = licenses.assign( licensing_authority_id=MAINE['licensing_authority_id'], licensing_authority=MAINE['licensing_authority'], license_designation='Adult-Use', premise_state=STATE, license_status_date=None, license_term=None, issue_date=None, expiration_date=None, business_structure=None, business_email=None, business_phone=None, activity=None, parcel_number=None, premise_street_address=None, id=licenses['license_number'], business_image_url=None, ) # Remove duplicates. licenses.drop_duplicates(subset='license_number', inplace=True) # Replace null DBA with legal name. criterion = licenses['business_dba_name'].isnull() licenses.loc[criterion,'business_dba_name'] = licenses['business_legal_name'] # Convert certain columns from upper case title case. cols = ['business_legal_name', 'business_dba_name', 'business_owner_name'] for col in cols: licenses[col] = licenses[col].apply( lambda x: x.title().strip() if isinstance(x, str) else x ) # Get the refreshed date. date = licenses_source_file.split('\\')[-1].split('.')[0].replace(licenses_key, '') date = date.replace('%20', '') date = '-'.join([date[:2], date[2:4], date[4:]]) licenses['data_refreshed_date'] = pd.to_datetime(date).isoformat() # Geocode licenses to get `premise_latitude` and `premise_longitude`. config = dotenv_values(env_file) api_key = config['GOOGLE_MAPS_API_KEY'] cols = ['premise_city', 'premise_state'] licenses['address'] = licenses[cols].apply( lambda row: ', '.join(row.values.astype(str)), axis=1, ) licenses = geocode_addresses(licenses, address_field='address', api_key=api_key) drop_cols = ['state', 'state_name', 'address', 'formatted_address', 'contact_type', 'contact_city', 'contact_description'] gis_cols = { 'county': 'premise_county', 'latitude': 'premise_latitude', 'longitude': 'premise_longitude', } licenses['premise_zip_code'] = licenses['formatted_address'].apply( lambda x: x.split(', ')[2].split(',')[0].split(' ')[-1] if STATE in str(x) else x ) licenses.drop(columns=drop_cols, inplace=True) licenses.rename(columns=gis_cols, inplace=True) # Save and return the data. if data_dir is not None: timestamp = datetime.now().isoformat()[:19].replace(':', '-') licenses.to_csv(f'{data_dir}/licenses-{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_me(data_dir, env_file=env_file)