""" Cannabis Licenses | Get Colorado Licenses Copyright (c) 2022 Cannlytics Authors: Keegan Skeate Candace O'Sullivan-Sutherland Created: 9/29/2022 Updated: 9/20/2023 License: Description: Collect Colorado cannabis license data. Data Source: - Colorado Department of Revenue | Marijuana Enforcement Division URL: """ # Standard imports. from datetime import datetime import os from time import sleep from typing import Optional # External imports. from bs4 import BeautifulSoup from cannlytics.data.data import load_google_sheet from cannlytics.data.gis import search_for_address from dotenv import dotenv_values import pandas as pd import requests # Specify where your data lives. DATA_DIR = '../data/co' ENV_FILE = '../../../.env' # Specify state-specific constants. STATE = 'CO' COLORADO = { 'licensing_authority_id': 'MED', 'licensing_authority': 'Colorado Marijuana Enforcement Division', 'licenses_url': 'https://sbg.colorado.gov/med/licensed-facilities', 'licenses': { 'columns': { 'LicenseNumber': 'license_number', 'FacilityName': 'business_legal_name', 'DBA': 'business_dba_name', 'City': 'premise_city', 'ZipCode': 'premise_zip_code', 'DateUpdated': 'data_refreshed_date', 'Licensee Name ': 'business_legal_name', 'License # ': 'license_number', 'City ': 'premise_city', 'Zip': 'premise_zip_code', }, 'drop_columns': [ 'FacilityType', # This causes an error with `license_type`. 'Potency', 'Solvents', 'Microbial', 'Pesticides', 'Mycotoxin', 'Elemental Impurities', 'Water Activity' ] } } def get_licenses_co( data_dir: Optional[str] = None, env_file: Optional[str] = '.env', ): """Get Colorado cannabis license data.""" # Get the licenses webpage. url = COLORADO['licenses_url'] response = requests.get(url) soup = BeautifulSoup(response.content, 'html.parser') # Get the Google Sheets for each license type. docs = {} links = soup.find_all('a') for link in links: try: href = link['href'] except KeyError: pass if 'docs.google' in href: docs[link.text] = href # Download each "Medical" and "Retail" Google Sheet. licenses = pd.DataFrame() license_designations = ['Medical', 'Retail'] columns=COLORADO['licenses']['columns'] drop_columns=COLORADO['licenses']['drop_columns'] for license_type, doc in docs.items(): for license_designation in license_designations: license_data = load_google_sheet(doc, license_designation) license_data['license_type'] = license_type license_data['license_designation'] = license_designation license_data.rename(columns=columns, inplace=True) license_data.drop(columns=drop_columns, inplace=True, errors='ignore') licenses = pd.concat([licenses, license_data]) sleep(0.22) # Standardize the license data. licenses = licenses.assign( id=licenses['license_number'], license_status=None, licensing_authority_id=COLORADO['licensing_authority_id'], licensing_authority=COLORADO['licensing_authority'], license_designation='Adult-Use', premise_state=STATE, license_status_date=None, license_term=None, issue_date=None, expiration_date=None, business_owner_name=None, business_structure=None, activity=None, parcel_number=None, business_phone=None, business_email=None, business_image_url=None, ) # Fill empty DBA names and strip trailing whitespace. licenses.loc[licenses['business_dba_name'] == '', 'business_dba_name'] = licenses['business_legal_name'] licenses.business_dba_name.fillna(licenses.business_legal_name, inplace=True) licenses.business_legal_name.fillna(licenses.business_dba_name, inplace=True) licenses = licenses.loc[~licenses.business_dba_name.isna()] licenses.business_dba_name = licenses.business_dba_name.apply(lambda x: x.strip()) licenses.business_legal_name = licenses.business_legal_name.apply(lambda x: x.strip()) # Optional: Turn all capital case to title case. # Clean zip code column. licenses['premise_zip_code'] = licenses['premise_zip_code'].apply( lambda x: str(round(x)) if pd.notnull(x) else x ) licenses.loc[licenses['premise_zip_code'].isnull(), 'premise_zip_code'] = '' # Search for address for each retail license. # Only search for a query once, then re-use the response. # Note: There is probably a much, much more efficient way to do this!!! config = dotenv_values(env_file) api_key = config['GOOGLE_MAPS_API_KEY'] cols = ['business_dba_name', 'premise_city', 'premise_state', 'premise_zip_code'] retailers = licenses.loc[licenses['license_type'] == 'Stores'].copy() retailers['query'] = retailers.loc[:, cols].apply( lambda row: ', '.join(row.values.astype(str)), axis=1, ) queries = {} fields = [ 'formatted_address', 'formatted_phone_number', 'geometry/location/lat', 'geometry/location/lng', 'website', ] retailers = retailers.reset_index(drop=True) retailers = retailers.assign( premise_street_address=None, premise_county=None, premise_latitude=None, premise_longitude=None, business_website=None, business_phone=None, ) for index, row in retailers.iterrows(): query = row['query'] gis_data = queries.get(query) if gis_data is None: try: gis_data = search_for_address(query, api_key=api_key, fields=fields) except: gis_data = {} queries[query] = gis_data retailers.iat[index, retailers.columns.get_loc('premise_street_address')] = gis_data.get('street') retailers.iat[index, retailers.columns.get_loc('premise_county')] = gis_data.get('county') retailers.iat[index, retailers.columns.get_loc('premise_latitude')] = gis_data.get('latitude') retailers.iat[index, retailers.columns.get_loc('premise_longitude')] = gis_data.get('longitude') retailers.iat[index, retailers.columns.get_loc('business_website')] = gis_data.get('website') retailers.iat[index, retailers.columns.get_loc('business_phone')] = gis_data.get('formatted_phone_number') # Clean-up after getting GIS data. retailers.drop(columns=['query'], inplace=True) # TODO: Merge retailer fields with licenses. new_fields = [ 'license_number', 'premise_street_address', 'premise_county', 'premise_latitude', 'premise_longitude', 'business_website', 'business_phone' ] licenses = pd.merge(licenses, retailers[new_fields], how='left', on='license_number') licenses.loc[licenses['business_phone_y'].notna(), 'business_phone_x'] = licenses['business_phone_y'] licenses.drop(columns=['business_phone_y'], inplace=True) licenses.rename(columns={'business_phone_x': 'business_phone'}, 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(':', '-') licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False) licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-latest.csv', index=False) retailers.to_csv(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.csv', index=False) return licenses # === Test === # [✓] Tested: 2023-09-20 by Keegan Skeate 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_co(data_dir, env_file=env_file)