pr/kls-1 (#3)

- Added all `.csv` files os of 2022-10-08 (4ba708a833a2064337b3e487eb5e0dfc21a1d2e5)
- Initial 🌲📜`cannabis_licenses` data algorithms 🤖 (37c1d7cb64442f232c4aa2fd7c36425b09ace75b)

.gitattributes

@@ -50,3 +50,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
 *.xlsx filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -12,3 +12,6 @@
 
 # Ignore VS Code settings.
 *.vscode
+
+# Ignore PyCache
+*__pycache__

README.md

@@ -14,10 +14,15 @@ tags:
   - cannabis
   - licenses
   - licensees
+  - retail
 ---
 
 # Cannabis Licenses, Curated by Cannlytics
 
+<div align="center" style="text-align:center; margin-top:1rem; margin-bottom: 1rem;">
+  <img style="max-height:365px;width:100%;max-width:720px;" alt="" src="analysis/figures/cannabis-licenses-map.png">
+</div>
+
 ## Table of Contents
 - [Table of Contents](#table-of-contents)
 - [Dataset Description](#dataset-description)
@@ -49,58 +54,55 @@ tags:
 
 ### Dataset Summary
 
-This dataset is a collection of cannabis license data for the licensees that have been permitted in the United States.
+**Cannabis Licenses** is a collection of cannabis license data for each state with permitted adult-use cannabis. The dataset also includes a sub-dataset, `all`, that includes all licenses.
 
 ## Dataset Structure
 
-The dataset is partitioned into subsets for each state.
-
-
-| State | Licenses |
-|-------|----------|
-|  [Alaska](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ak) |  |
-|  [Arizona](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/az) |  |
-|  [California](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ca) | ✅ |
-|  [Colorado](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/co) |  |
-|  [Connecticut](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ct) |  |
-|  [Illinois](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/il) |  |
-|  [Maine](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/me) | ✅ |
-|  [Massachusetts](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ma) |  |
-|  [Michigan](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/mi) |  |
-|  [Montana](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/mt) |  |
-|  [Nevada](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/nv) | ✅ |
-|  [New Jersey](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/nj) | ✅ |
-|  [New Mexico](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/nm) |  |
-|  [Oregon](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/or) | ✅  |
-|  [Rhode Island](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ri) |  |
-|  [Vermont](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/vt) |  |
-|  [Washington](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/wa) | ✅ |
-
-Coming Soon (2):
+The dataset is partitioned into 18 subsets for each state and the aggregate.
+
+| State | Code | Status |
+|-------|------|--------|
+|  [All](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/all) |  `all` | ✅ |
+|  [Alaska](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ak) |  `ak` | ✅ |
+|  [Arizona](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/az) | `az` | ✅ |
+|  [California](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ca) | `ca`  | ✅ |
+|  [Colorado](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/co) | `co`  | ✅ |
+|  [Connecticut](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ct) | `ct`  | ✅ |
+|  [Illinois](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/il) | `il`  | ✅ |
+|  [Maine](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/me) | `me`  | ✅ |
+|  [Massachusetts](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ma) | `ma`  | ✅ |
+|  [Michigan](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/mi) | `mi`  | ✅ |
+|  [Montana](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/mt) | `mt`  | ✅ |
+|  [Nevada](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/nv) | `nv`  | ✅ |
+|  [New Jersey](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/nj) | `nj`  | ✅ |
+| New York | `ny` | ⏳ Expected 2022 Q4 |
+|  [New Mexico](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/nm) | `nm`  | ⚠️ Under development |
+|  [Oregon](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/or) | `or`  | ✅  |
+|  [Rhode Island](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/ri) | `ri`  | ✅ |
+|  [Vermont](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/vt) | `vt`  | ✅ |
+| Virginia | `va` | ⏳ Expected 2024 |
+|  [Washington](https://huggingface.co/datasets/cannlytics/cannabis_licenses/tree/main/data/wa) | `wa`  | ✅ |
+
+The following (18) states have issued medical cannabis licenses, but are not (yet) included in the dataset:
 
-- New York
-- Virginia
-
-Medical (18):
-
-- District of Columbia (D.C.)
-- Utah
-- Oklahoma
-- North Dakota
-- South Dakota
-- Minnesota
-- Missouri
+- Alabama
 - Arkansas
+- Delaware
+- District of Columbia (D.C.)
+- Florida
 - Louisiana
+- Maryland
+- Minnesota
 - Mississippi
-- Alabama
-- Florida
+- Missouri
+- New Hampshire
+- North Dakota
 - Ohio
-- West Virginia
+- Oklahoma
 - Pennsylvania
-- Maryland
-- Delaware
-- New Hampshire
+- South Dakota
+- Utah
+- West Virginia
 
 ### Data Instances
 
@@ -122,33 +124,34 @@ Below is a non-exhaustive list of fields, used to standardize the various data t
 
 | Field | Example | Description |
 |-------|-----|-------------|
-| `id` | `"1046"` |  |
-| `license_number` | `"C10-0000423-LIC"` |  |
-| `license_status` | `"Active"` |  |
-| `license_status_date` | `""` |  |
-| `license_term` | `"Provisional"` |  |
-| `license_type` | `"Commercial -  Retailer"` |  |
-| `license_designation` | `"Adult-Use and Medicinal"` |  |
-| `issue_date` | `"2019-07-15T00:00:00"` |  |
-| `expiration_date` | `"2023-07-14T00:00:00"` |  |
-| `licensing_authority_id` | `"BCC"` |  |
-| `licensing_authority` | `"Bureau of Cannabis Control (BCC)"` |  |
-| `business_legal_name` | `"Movocan"` |  |
-| `business_dba_name` | `"Movocan"` |  |
-| `business_owner_name` | `"redacted"` |  |
-| `business_structure` | `"Corporation"` |  |
-| `activity` | `""` |  |
-| `premise_street_address` | `"1632 Gateway Rd"` |  |
-| `premise_city` | `"Calexico"` |  |
-| `premise_state` | `"CA"` |  |
-| `premise_county` | `"Imperial"` |  |
-| `premise_zip_code` | `"92231"` |  |
-| `business_email` | `"redacted@gmail.com"` |  |
-| `business_phone` | `"(555) 555-5555"` |  |
-| `parcel_number` | `""` |  |
-| `premise_latitude` | `32.69035693` |  |
-| `premise_longitude` | `-115.38987552` |  |
-| `data_refreshed_date` | `"2022-09-21T12:16:33.3866667"` |  |
+| `id` | `"1046"` | A state-unique ID for the license. |
+| `license_number` | `"C10-0000423-LIC"` | A unique license number. |
+| `license_status` | `"Active"` | The status of the license. Only licenses that are active are included. |
+| `license_status_date` | `"2022-04-20T00:00"` | The date the status was assigned, an ISO-formatted date if present. |
+| `license_term` | `"Provisional"` | The term for the license. |
+| `license_type` | `"Commercial - Retailer"` | The type of business license. |
+| `license_designation` | `"Adult-Use and Medicinal"` | A state-specific classification for the license. |
+| `issue_date` | `"2019-07-15T00:00:00"` | An issue date for the license, an ISO-formatted date if present. |
+| `expiration_date` | `"2023-07-14T00:00:00"` | An expiration date for the license, an ISO-formatted date if present. |
+| `licensing_authority_id` | `"BCC"` | A unique ID for the state licensing authority. |
+| `licensing_authority` | `"Bureau of Cannabis Control (BCC)"` | The state licensing authority. |
+| `business_legal_name` | `"Movocan"` | The legal name of the business that owns the license. |
+| `business_dba_name` | `"Movocan"` | The name the license is doing business as. |
+| `business_owner_name` | `"redacted"` | The name of the owner of the license. |
+| `business_structure` | `"Corporation"` | The structure of the business that owns the license. |
+| `activity` | `"Pending Inspection"` | Any relevant license activity. |
+| `premise_street_address` | `"1632 Gateway Rd"` | The street address of the business. |
+| `premise_city` | `"Calexico"` | The city of the business. |
+| `premise_state` | `"CA"` | The state abbreviation of the business. |
+| `premise_county` | `"Imperial"` | The county of the business. |
+| `premise_zip_code` | `"92231"` | The zip code of the business. |
+| `business_email` | `"redacted@gmail.com"` | The business email of the license. |
+| `business_phone` | `"(555) 555-5555"` | The business phone of the license. |
+| `business_website` | `"cannlytics.com"` | The business website of the license. |
+| `parcel_number` | `"A42"` | An ID for the business location. |
+| `premise_latitude` | `32.69035693` | The latitude of the business. |
+| `premise_longitude` | `-115.38987552` | The longitude of the business. |
+| `data_refreshed_date` | `"2022-09-21T12:16:33.3866667"` | An ISO-formatted time when the license data was updated. |
 
 ### Data Splits
 
@@ -176,12 +179,12 @@ Data about organizations operating in the cannabis industry for each state is va
 |  Alaska | <https://www.commerce.alaska.gov/abc/marijuana/Home/licensesearch> |
 |  Arizona | <https://azcarecheck.azdhs.gov/s/?licenseType=null> |
 |  California | <https://search.cannabis.ca.gov/> |
-|  Colorado |  |
+|  Colorado | <https://sbg.colorado.gov/med/licensed-facilities> |
 |  Connecticut | <https://portal.ct.gov/DCP/Medical-Marijuana-Program/Connecticut-Medical-Marijuana-Dispensary-Facilities> |
-|  Illinois |  |
+|  Illinois | <https://www.idfpr.com/LicenseLookup/AdultUseDispensaries.pdf> |
 |  Maine | <https://www.maine.gov/dafs/ocp/open-data/adult-use> |
-|  Massachusetts |  |
-|  Michigan |  |
+|  Massachusetts | <https://masscannabiscontrol.com/open-data/data-catalog/> |
+|  Michigan | <https://michigan.maps.arcgis.com/apps/webappviewer/index.html?id=cd5a1a76daaf470b823a382691c0ff60> |
 |  Montana | <https://mtrevenue.gov/cannabis/#CannabisLicenses> |
 |  Nevada | <https://ccb.nv.gov/list-of-licensees/> |
 |  New Jersey | <https://data.nj.gov/stories/s/ggm4-mprw> |
@@ -191,7 +194,7 @@ Data about organizations operating in the cannabis industry for each state is va
 |  Vermont | <https://ccb.vermont.gov/licenses> |
 |  Washington | <https://lcb.wa.gov/records/frequently-requested-lists> |
 
-#### Data Collection and Normalization
+### Data Collection and Normalization
 
 In the `algorithms` directory, you can find the algorithms used for data collection. You can use these algorithms to recreate the dataset. First, you will need to clone the repository:
 
@@ -241,7 +244,7 @@ The data is for adult-use cannabis licenses. It would be valuable to include med
 ### Dataset Curators
 
 Curated by [🔥Cannlytics](https://cannlytics.com)<br>
-<dev@cannlytics.com>
+<contact@cannlytics.com>
 
 ### License
 
@@ -267,7 +270,7 @@ Please cite the following if you use the code examples in your research:
 ```bibtex
 @misc{cannlytics2022,
   title={Cannabis Data Science},
-  author={Skeate, Keegan},
+  author={Skeate, Keegan and O'Sullivan-Sutherland, Candace},
   journal={https://github.com/cannlytics/cannabis-data-science},
   year={2022}
 }
@@ -275,4 +278,4 @@ Please cite the following if you use the code examples in your research:
 
 ### Contributions
 
-Thanks to [🔥Cannlytics](https://cannlytics.com), [@candy-o](https://github.com/candy-o), [@keeganskeate](https://github.com/keeganskeate), and the entire [Cannabis Data Science Team](https://meetup.com/cannabis-data-science/members) for their contributions.
+Thanks to [🔥Cannlytics](https://cannlytics.com), [@candy-o](https://github.com/candy-o), [@hcadeaux](https://huggingface.co/hcadeaux), [@keeganskeate](https://github.com/keeganskeate), and the entire [Cannabis Data Science Team](https://meetup.com/cannabis-data-science/members) for their contributions.

algorithms/get_licenses_ak.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/6/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,7 +15,230 @@ Description:
 
 Data Source:
 
-    - Alaska
+    - Department of Commerce, Community, and Economic Development
+    Alcohol and Marijuana Control Office
     URL: <https://www.commerce.alaska.gov/abc/marijuana/Home/licensesearch>
 
-"""
+"""
+# Standard imports.
+from datetime import datetime
+import os
+from time import sleep
+from typing import Optional
+
+# External imports.
+from cannlytics.data.gis import search_for_address
+from dotenv import dotenv_values
+import pandas as pd
+
+# Selenium imports.
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+from selenium.webdriver.common.by import By
+from selenium.webdriver.chrome.service import Service
+try:
+    import chromedriver_binary  # Adds chromedriver binary to path.
+except ImportError:
+    pass # Otherwise, ChromeDriver should be in your path.
+
+
+# Specify where your data lives.
+DATA_DIR = '../data/ak'
+ENV_FILE = '../.env'
+
+# Specify state-specific constants.
+STATE = 'AK'
+ALASKA = {
+    'licensing_authority_id': 'AAMCO',
+    'licensing_authority': 'Alaska Alcohol and Marijuana Control Office',
+    'licenses_url': 'https://www.commerce.alaska.gov/abc/marijuana/Home/licensesearch',
+    'licenses': {
+        'columns': {
+            'License #': 'license_number',
+            'Business License #': 'id',
+            'Doing Business As': 'business_dba_name',
+            'License Type': 'license_type',
+            'License Status': 'license_status',
+            'Physical Address': 'address',
+        },
+    },
+}
+
+
+def get_licenses_ak(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+    ):
+    """Get Alaska cannabis license data."""
+
+    # Initialize Selenium and specify options.
+    service = Service()
+    options = Options()
+    options.add_argument('--window-size=1920,1200')
+
+    # DEV: Run with the browser open.
+    # options.headless = False
+
+    # PRODUCTION: Run with the browser closed.
+    options.add_argument('--headless')
+    options.add_argument('--disable-gpu')
+    options.add_argument('--no-sandbox')
+
+    # Initiate a Selenium driver.
+    driver = webdriver.Chrome(options=options, service=service)
+
+    # Load the license page.
+    driver.get(ALASKA['licenses_url'])
+
+    # Get the license type select.
+    license_types = []
+    options = driver.find_elements(by=By.TAG_NAME, value='option')
+    for option in options:
+        text = option.text
+        if text:
+            license_types.append(text)
+
+    # Iterate over all of the license types.
+    data = []
+    columns = list(ALASKA['licenses']['columns'].values())
+    for license_type in license_types:
+
+        # Set the text into the select.
+        select = driver.find_element(by=By.ID, value='SearchLicenseTypeID')
+        select.send_keys(license_type)
+
+        # Click search.
+        # TODO: There is probably an elegant way to wait for the table to load.
+        search_button = driver.find_element(by=By.ID, value='mariSearchBtn')
+        search_button.click()
+        sleep(2)
+
+        # Extract the table data.
+        table = driver.find_element(by=By.TAG_NAME, value='tbody')
+        rows = table.find_elements(by=By.TAG_NAME, value='tr')
+        for row in rows:
+            obs = {}
+            cells = row.find_elements(by=By.TAG_NAME, value='td')
+            for i, cell in enumerate(cells):
+                column = columns[i]
+                obs[column] = cell.text.replace('\n', ', ')
+            data.append(obs)
+
+    # End the browser session.
+    service.stop()
+
+    # Standardize the license data.
+    licenses = pd.DataFrame(data)
+    licenses = licenses.assign(
+        business_legal_name=licenses['business_dba_name'],
+        business_owner_name=None,
+        business_structure=None,
+        licensing_authority_id=ALASKA['licensing_authority_id'],
+        licensing_authority=ALASKA['licensing_authority'],
+        license_designation='Adult-Use',
+        license_status_date=None,
+        license_term=None,
+        premise_state=STATE,
+        parcel_number=None,
+        activity=None,
+        issue_date=None,
+        expiration_date=None,
+    )
+
+    # Restrict the license status to active.
+    active_license_types = [
+        'Active-Operating',
+        'Active-Pending Inspection',
+        'Delegated',
+        'Complete',
+    ]
+    licenses = licenses.loc[licenses['license_status'].isin(active_license_types)]
+
+    # Assign the city and zip code.
+    licenses['premise_city'] = licenses['address'].apply(
+        lambda x: x.split(', ')[1]
+    )
+    licenses['premise_zip_code'] = licenses['address'].apply(
+        lambda x: x.split(', ')[2].replace(STATE, '').strip()
+    )
+
+    # 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']
+    queries = {}
+    fields = [
+        'formatted_address',
+        'formatted_phone_number',
+        'geometry/location/lat',
+        'geometry/location/lng',
+        'website',
+    ]
+    licenses = licenses.reset_index(drop=True)
+    licenses = licenses.assign(
+        premise_street_address=None,
+        premise_county=None,
+        premise_latitude=None,
+        premise_longitude=None,
+        business_phone=None,
+        business_website=None,
+    )
+    for index, row in licenses.iterrows():
+
+        # Query Google Place API, if necessary.
+        query = ', '.join([row['business_dba_name'], row['address']])
+        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
+
+        # Record the query.
+        licenses.iat[index, licenses.columns.get_loc('premise_street_address')] = gis_data.get('street')
+        licenses.iat[index, licenses.columns.get_loc('premise_county')] = gis_data.get('county')
+        licenses.iat[index, licenses.columns.get_loc('premise_latitude')] = gis_data.get('latitude')
+        licenses.iat[index, licenses.columns.get_loc('premise_longitude')] = gis_data.get('longitude')
+        licenses.iat[index, licenses.columns.get_loc('business_phone')] = gis_data.get('formatted_phone_number')
+        licenses.iat[index, licenses.columns.get_loc('business_website')] = gis_data.get('website')
+
+    # Clean-up after GIS.
+    licenses.drop(columns=['address'], inplace=True)
+
+    # Optional: Search for business website for email and a photo.
+    licenses['business_email'] = None
+    licenses['business_image_url'] = None
+
+    # Get the refreshed date.
+    licenses['data_refreshed_date'] = datetime.now().isoformat()
+
+    # 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 Marijuana Store']
+        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_ak(data_dir, env_file=env_file)

algorithms/get_licenses_az.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/27/2022
-Updated: 9/30/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -27,23 +27,15 @@ from time import sleep
 from typing import Optional
 
 # External imports.
-from bs4 import BeautifulSoup
 from cannlytics.data.gis import geocode_addresses
-from cannlytics.utils import camel_to_snake
-from cannlytics.utils.constants import DEFAULT_HEADERS
-import matplotlib.pyplot as plt
 import pandas as pd
-import requests
-import seaborn as sns
+import zipcodes
 
 # Selenium imports.
 from selenium import webdriver
 from selenium.webdriver.chrome.options import Options
 from selenium.webdriver.common.by import By
 from selenium.webdriver.chrome.service import Service
-from selenium.common.exceptions import (
-    TimeoutException,
-)
 from selenium.webdriver.support import expected_conditions as EC
 from selenium.webdriver.support.ui import WebDriverWait
 try:
@@ -54,193 +46,288 @@ except ImportError:
 
 # Specify where your data lives.
 DATA_DIR = '../data/az'
+ENV_FILE = '../.env'
 
 # Specify state-specific constants.
 STATE = 'AZ'
 ARIZONA = {
     'licensing_authority_id': 'ADHS',
     'licensing_authority': 'Arizona Department of Health Services',
-    'retailers': {
-        'url': 'https://azcarecheck.azdhs.gov/s/?licenseType=null',
-    },
+    'licenses_url': 'https://azcarecheck.azdhs.gov/s/?licenseType=null',
 }
 
-# def get_licenses_az(
-#         data_dir: Optional[str] = None,
-#         env_file: Optional[str] = '.env',
-#     ):
-#     """Get Arizona cannabis license data."""
 
-
-# DEV:
-data_dir = DATA_DIR
-env_file = '../.env'
-
-
-# Create directories if necessary.
-if not os.path.exists(data_dir): os.makedirs(data_dir)
-
-# Initialize Selenium.
-service = Service()
-options = Options()
-options.add_argument('--window-size=1920,1200')
-# DEV:
-options.headless = False 
-# options.add_argument('--headless')
-options.add_argument('--disable-gpu')
-options.add_argument('--no-sandbox')
-driver = webdriver.Chrome(options=options, service=service)
-
-# Load the license page.
-url = ARIZONA['retailers']['url']
-driver.get(url)
-
-# Wait for the page to load by waiting to detect the image.
-try:
-    el = (By.CLASS_NAME, 'slds-container_center')
-    detect = EC.presence_of_element_located(el)
-    WebDriverWait(driver, timeout=30).until(detect)
-except TimeoutException:
-    print('Failed to load page within %i seconds.' % (30))
-
-# Get the map container.
-container = driver.find_element(by=By.CLASS_NAME, value='slds-container_center')
-
-# Click "Load more" until all of the licenses are visible.
-more = True
-while(more):
-    button = container.find_element(by=By.TAG_NAME, value='button')
-    driver.execute_script('arguments[0].scrollIntoView(true);', button)
-    button.click()
-    counter = container.find_element(by=By.CLASS_NAME, value='count-text')
-    more = int(counter.text.replace(' more', ''))
-
-# Get license data for each retailer.
-retailers = []
-els = container.find_elements(by=By.CLASS_NAME, value='map-list__item')
-for i, el in enumerate(els):
-
-    # Get a retailer's data.
-    count = i + 1
-    xpath = f'/html/body/div[3]/div[2]/div/div[2]/div[2]/div/div/c-azcc-portal-home/c-azcc-map/div/div[2]/div[2]/div[2]/div[{count}]/c-azcc-map-list-item/div'
-    list_item = el.find_element(by=By.XPATH, value=xpath)
-    body = list_item.find_element(by=By.CLASS_NAME, value='slds-media__body')
-    divs = body.find_elements(by=By.TAG_NAME, value='div')
-    name = divs[0].text
-    legal_name = divs[1].text
-    if not name:
-        name = legal_name
-    address = divs[3].text
-    address_parts = address.split(',')
-    parts = divs[2].text.split(' · ')
-
-    # Get the retailer's link to get more details.
-    link = divs[-1].find_element(by=By.TAG_NAME, value='a')
-    href = link.get_attribute('href')
-
-    # Record the retailer's data.
-    obs = {
-        'address': address,
-        'details_url': href,
-        'business_legal_name': legal_name,
-        'business_dba_name': name,
-        'business_phone': parts[-1],
-        'license_status': parts[0],
-        'license_type': parts[1],
-        'premise_street_address': address_parts[0],
-        'premise_city': address_parts[1],
-        'premise_zip_code': address_parts[-1].replace('AZ ', ''),
-    }
-    retailers.append(obs)
-
-# Standardize the retailer data.
-retailers = pd.DataFrame(retailers)
-retailers['licensing_authority_id'] = ARIZONA['licensing_authority_id']
-retailers['licensing_authority'] = ARIZONA['licensing_authority']
-retailers['license_designation'] = 'Adult-Use'
-retailers['premise_state'] = STATE
-retailers['license_status_date'] = None
-retailers['license_term'] = None
-retailers['business_structure'] = None
-retailers['activity'] = None
-retailers['parcel_number'] = None
-
-# TODO: Get each retailer's details.
-for index, row in retailers.iterrows():
-
-    # Load the retailer's details webpage.
-    driver.get(row['details_url'])
-    # https://azcarecheck.azdhs.gov/s/facility-details?facilityId=001t000000L0TAaAAN&activeTab=details
-
-    # TODO: Get the `business_email`.
-    # lightning-formatted-email
-
-
-    # TODO: Get the `license_number`
-    
-
-    # TODO: Get `issue_date` and `expiration_date`
-
-
-    # TODO: Get `business_owner_name`
-
-
-    # TODO: Get `license_designation` ("Services").
-
-
-    # TODO: Create entries for cultivations!
-
-
-    # TODO: Get the `premise_latitude` and `premise_longitude`.
-    # https://maps.google.com/maps?daddr=33.447334955594650,-111.991646657827630&amp;ll=
-
-
-
-# TODO: Lookup counties for the retailers.
-
-
-# TODO: Geocode-cultivations.
-
-# Geocode licenses to get `premise_latitude` and `premise_longitude`.
-# 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',
-# )
-# 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)
-
-# TODO: Save and return the data.
-# if data_dir is not None:
-#     timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-#     retailers.to_excel(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.xlsx')
-# return retailers
+def county_from_zip(x):
+    """Find a county given a zip code. Returns `None` if no match."""
+    try:
+        return zipcodes.matching(x)[0]['county']
+    except KeyError:
+        return None
+
+
+def get_licenses_az(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+    ):
+    """Get Arizona cannabis license data."""
+
+    # Create directories if necessary.
+    if not os.path.exists(data_dir): os.makedirs(data_dir)
+
+    # Initialize Selenium and specify options.
+    service = Service()
+    options = Options()
+    options.add_argument('--window-size=1920,1200')
+
+    # DEV: Run with the browser open.
+    # options.headless = False
+
+    # PRODUCTION: Run with the browser closed.
+    options.add_argument('--headless')
+    options.add_argument('--disable-gpu')
+    options.add_argument('--no-sandbox')
+
+    # Initiate a Selenium driver.
+    driver = webdriver.Chrome(options=options, service=service)
+
+    # Load the license page.
+    driver.get(ARIZONA['licenses_url'])
+    detect = (By.CLASS_NAME, 'slds-container_center')
+    WebDriverWait(driver, 30).until(EC.presence_of_element_located(detect))
+
+    # Get the map container.
+    container = driver.find_element(by=By.CLASS_NAME, value='slds-container_center')
+
+    # Click "Load more" until all of the licenses are visible.
+    more = True
+    while(more):
+        button = container.find_element(by=By.TAG_NAME, value='button')
+        driver.execute_script('arguments[0].scrollIntoView(true);', button)
+        button.click()
+        counter = container.find_element(by=By.CLASS_NAME, value='count-text')
+        more = int(counter.text.replace(' more', ''))
+
+    # Get license data for each retailer.
+    data = []
+    els = container.find_elements(by=By.CLASS_NAME, value='map-list__item')
+    for i, el in enumerate(els):
+
+        # Get a retailer's data.
+        count = i + 1
+        xpath = f'/html/body/div[3]/div[2]/div/div[2]/div[2]/div/div/c-azcc-portal-home/c-azcc-map/div/div[2]/div[2]/div[2]/div[{count}]/c-azcc-map-list-item/div'
+        list_item = el.find_element(by=By.XPATH, value=xpath)
+        body = list_item.find_element(by=By.CLASS_NAME, value='slds-media__body')
+        divs = body.find_elements(by=By.TAG_NAME, value='div')
+        name = divs[0].text
+        legal_name = divs[1].text
+        if not name:
+            name = legal_name
+        address = divs[3].text
+        address_parts = address.split(',')
+        parts = divs[2].text.split(' · ')
+
+        # Get the retailer's link to get more details.
+        link = divs[-1].find_element(by=By.TAG_NAME, value='a')
+        href = link.get_attribute('href')
+
+        # Record the retailer's data.
+        obs = {
+            'address': address,
+            'details_url': href,
+            'business_legal_name': legal_name,
+            'business_dba_name': name,
+            'business_phone': parts[-1],
+            'license_status': parts[0],
+            'license_type': parts[1],
+            'premise_street_address': address_parts[0].strip(),
+            'premise_city': address_parts[1].strip(),
+            'premise_zip_code': address_parts[-1].replace('AZ ', '').strip(),
+        }
+        data.append(obs)
+
+    # Standardize the retailer data.
+    retailers = pd.DataFrame(data)
+    retailers = retailers.assign(
+        business_email=None,
+        business_owner_name=None,
+        business_structure=None,
+        business_image_url=None,
+        business_website=None,
+        id=retailers.index,
+        licensing_authority_id=ARIZONA['licensing_authority_id'],
+        licensing_authority=ARIZONA['licensing_authority'],
+        license_designation='Adult-Use',
+        license_number=None,
+        license_status_date=None,
+        license_term=None,
+        premise_latitude=None,
+        premise_longitude=None,
+        premise_state=STATE,
+        issue_date=None,
+        expiration_date=None,
+        parcel_number=None,
+        activity=None,
+    )
+
+    # Get each retailer's details.
+    cultivators = pd.DataFrame(columns=retailers.columns)
+    manufacturers = pd.DataFrame(columns=retailers.columns)
+    for index, row in retailers.iterrows():
+
+        # Load the licenses's details webpage.
+        driver.get(row['details_url'])
+        detect = (By.CLASS_NAME, 'slds-container_center')
+        WebDriverWait(driver, 30).until(EC.presence_of_element_located(detect))
+        container = driver.find_element(by=By.CLASS_NAME, value='slds-container_center')
+        sleep(4)
+
+        # Get the `business_email`.
+        links = container.find_elements(by=By.TAG_NAME, value='a')
+        for link in links:
+            href = link.get_attribute('href')
+            if href is None: continue
+            if href.startswith('mailto'):
+                business_email = href.replace('mailto:', '')
+                col = retailers.columns.get_loc('business_email')
+                retailers.iat[index, col] = business_email
+                break
+
+        # Get the `license_number`
+        for link in links:
+            href = link.get_attribute('href')
+            if href is None: continue
+            if href.startswith('https://azdhs-licensing'):
+                col = retailers.columns.get_loc('license_number')
+                retailers.iat[index, col] = link.text
+                break
+
+        # Get the `premise_latitude` and `premise_longitude`.
+        for link in links:
+            href = link.get_attribute('href')
+            if href is None: continue
+            if href.startswith('https://maps.google.com/'):
+                coords = href.split('=')[1].split('&')[0].split(',')
+                lat_col = retailers.columns.get_loc('premise_latitude')
+                long_col = retailers.columns.get_loc('premise_longitude')
+                retailers.iat[index, lat_col] = float(coords[0])
+                retailers.iat[index, long_col] = float(coords[1])
+                break
+
+        # Get the `issue_date`.
+        key = 'License Effective'
+        el = container.find_element_by_xpath(f"//p[contains(text(),'{key}')]/following-sibling::lightning-formatted-text")
+        col = retailers.columns.get_loc('issue_date')
+        retailers.iat[index, col] = el.text
+
+        # Get the `expiration_date`.
+        key = 'License Expires'
+        el = container.find_element_by_xpath(f"//p[contains(text(),'{key}')]/following-sibling::lightning-formatted-text")
+        col = retailers.columns.get_loc('expiration_date')
+        retailers.iat[index, col] = el.text
+
+        # Get the `business_owner_name`.
+        key = 'Owner / License'
+        el = container.find_element_by_xpath(f"//p[contains(text(),'{key}')]/following-sibling::lightning-formatted-text")
+        col = retailers.columns.get_loc('expiration_date')
+        retailers.iat[index, col] = el.text
+
+        # Get the `license_designation` ("Services").
+        key = 'Services'
+        el = container.find_element_by_xpath(f"//p[contains(text(),'{key}')]/following-sibling::lightning-formatted-rich-text")
+        col = retailers.columns.get_loc('license_designation')
+        retailers.iat[index, col] = el.text
+
+        # Create entries for cultivations.
+        cultivator = retailers.iloc[index].copy()
+        key = 'Offsite Cultivation Address'
+        el = container.find_element_by_xpath(f"//p[contains(text(),'{key}')]/following-sibling::lightning-formatted-text")
+        address = el.text
+        if address:
+            parts = address.split(',')
+            cultivator['address'] = address
+            cultivator['premise_street_address'] = parts[0]
+            cultivator['premise_city'] = parts[1].strip()
+            cultivator['premise_zip_code'] = parts[-1].replace(STATE, '').strip()
+            cultivator['license_type'] = 'Offsite Cultivation'
+            cultivators.append(cultivator, ignore_index=True)
+
+        # Create entries for manufacturers.
+        manufacturer = retailers.iloc[index].copy()
+        key = 'Manufacture Address'
+        el = container.find_element_by_xpath(f"//p[contains(text(),'{key}')]/following-sibling::lightning-formatted-text")
+        address = el.text
+        if address:
+            parts = address.split(',')
+            manufacturer['address'] = address
+            manufacturer['premise_street_address'] = parts[0]
+            manufacturer['premise_city'] = parts[1].strip()
+            manufacturer['premise_zip_code'] = parts[-1].replace(STATE, '').strip()
+            manufacturer['license_type'] = 'Offsite Cultivation'
+            manufacturers.append(manufacturer, ignore_index=True)
+
+    # End the browser session.
+    service.stop()
+    retailers.drop(column=['address', 'details_url'], inplace=True)
+
+    # Lookup counties by zip code.
+    retailers['premise_county'] = retailers['premise_zip_code'].apply(county_from_zip)
+    cultivators['premise_county'] = cultivators['premise_zip_code'].apply(county_from_zip)
+    manufacturers['premise_county'] = manufacturers['premise_zip_code'].apply(county_from_zip)
+
+    # Setup geocoding
+    config = dotenv_values(env_file)
+    api_key = config['GOOGLE_MAPS_API_KEY']
+    drop_cols = ['state', 'state_name', 'county', 'address', 'formatted_address']
+    gis_cols = {'latitude': 'premise_latitude', 'longitude': 'premise_longitude'}
+
+    # # Geocode cultivators.
+    # cultivators = geocode_addresses(cultivators, api_key=api_key, address_field='address')
+    # cultivators.drop(columns=drop_cols, inplace=True)
+    # cultivators.rename(columns=gis_cols, inplace=True)
+
+    # # Geocode manufacturers.
+    # manufacturers = geocode_addresses(manufacturers, api_key=api_key, address_field='address')
+    # manufacturers.drop(columns=drop_cols, inplace=True)
+    # manufacturers.rename(columns=gis_cols, inplace=True)
+
+    # TODO: Lookup business website and image.
+
+    # Aggregate all licenses.
+    licenses = pd.concat([retailers, cultivators, manufacturers])
+
+    # Get the refreshed date.
+    timestamp = datetime.now().isoformat()
+    licenses['data_refreshed_date'] = timestamp
+    retailers['data_refreshed_date'] = timestamp
+    # cultivators['data_refreshed_date'] = timestamp
+    # manufacturers['data_refreshed_date'] = timestamp
+
+    # Save and return the data.
+    if data_dir is not None:
+        timestamp = timestamp[:19].replace(':', '-')
+        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)
+        # cultivators.to_csv(f'{data_dir}/cultivators-{STATE.lower()}-{timestamp}.csv', index=False)
+        # manufacturers.to_csv(f'{data_dir}/manufacturers-{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_az(data_dir, env_file=env_file)
+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_az(data_dir, env_file=env_file)
 

algorithms/get_licenses_ca.py

@@ -80,11 +80,18 @@ def get_licenses_ca(
     columns = [camel_to_snake(x) for x in columns]
     license_data.columns = columns
 
+    # TODO: Lookup business website and image.
+    license_data['business_image_url'] = None
+    license_data['business_website'] = None
+
+    # Restrict to only active licenses.
+    license_data = license_data.loc[license_data['license_status'] == 'Active']
+
     # 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(':', '-')
-        license_data.to_excel(f'{data_dir}/licenses-ca-{timestamp}.xlsx')
+        license_data.to_csv(f'{data_dir}/licenses-ca-{timestamp}.csv', index=False)
     return license_data
 
 if __name__ == '__main__':

algorithms/get_licenses_co.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/4/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,7 +15,207 @@ Description:
 
 Data Source:
 
-    - Colorado
-    URL: <>
+    - Colorado Department of Revenue | Marijuana Enforcement Division
+    URL: <https://sbg.colorado.gov/med/licensed-facilities>
 
-"""
+"""
+# 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']
+    retailers['query'] = retailers[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)
+
+    # 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)
+        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_co(data_dir, env_file=env_file)

algorithms/get_licenses_ct.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/3/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,7 +15,149 @@ Description:
 
 Data Source:
 
-    - Connecticut
+    - Connecticut State Department of Consumer Protection
     URL: <https://portal.ct.gov/DCP/Medical-Marijuana-Program/Connecticut-Medical-Marijuana-Dispensary-Facilities>
 
-"""
+"""
+# 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/ct'
+ENV_FILE = '../.env'
+
+# Specify state-specific constants.
+STATE = 'CT'
+CONNECTICUT = {
+    'licensing_authority_id': 'CSDCP',
+    'licensing_authority': 'Connecticut State Department of Consumer Protection',
+    'licenses_url': 'https://portal.ct.gov/DCP/Medical-Marijuana-Program/Connecticut-Medical-Marijuana-Dispensary-Facilities',
+    'retailers': {
+        'columns': [
+            'business_legal_name',
+            'address',
+            'business_website',
+            'business_email',
+            'business_phone',
+        ]
+    }
+}
+
+
+def get_licenses_ct(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+    ):
+    """Get Connecticut cannabis license data."""
+
+    # Get the license webpage.
+    url = CONNECTICUT['licenses_url']
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+
+    # Extract the license data.
+    data = []
+    columns = CONNECTICUT['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)
+
+    # Standardize the license data.
+    retailers = pd.DataFrame(data)
+    retailers = retailers.assign(
+        id=retailers.index,
+        license_status=None,
+        business_dba_name=retailers['business_legal_name'],
+        license_number=None,
+        licensing_authority_id=CONNECTICUT['licensing_authority_id'],
+        licensing_authority=CONNECTICUT['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_image_url=None,
+        license_type=None,
+    )
+
+    # Get address parts.
+    retailers['premise_street_address'] = retailers['address'].apply(
+        lambda x: x.split(',')[0]
+    )
+    retailers['premise_city'] = retailers['address'].apply(
+        lambda x: x.split('CT')[0].strip().split(',')[-2]
+    )
+    retailers['premise_zip_code'] = retailers['address'].apply(
+        lambda x: x.split('CT')[-1].replace('\xa0', '').replace(',', '').strip()
+    )
+
+    # 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_city'] = retailers['formatted_address'].apply(
+        lambda x: x.split(', ')[1].split(',')[0] if STATE in str(x) else x
+    )
+    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)
+
+    # Get the refreshed date.
+    retailers['data_refreshed_date'] = datetime.now().isoformat()
+
+    # 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}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
+    return retailers
+
+
+# === 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_ct(data_dir, env_file=env_file)

algorithms/get_licenses_il.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/3/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,7 +15,180 @@ Description:
 
 Data Source:
 
-    - Illinois
-    URL: <>
+    - Illinois Department of Financial and Professional Regulation
+    Licensed Adult Use Cannabis Dispensaries
+    URL: <https://www.idfpr.com/LicenseLookup/AdultUseDispensaries.pdf>
 
-"""
+"""
+# Standard imports.
+from datetime import datetime
+import os
+from typing import Optional
+
+# External imports.
+from dotenv import dotenv_values
+from cannlytics.data.gis import geocode_addresses
+import pandas as pd
+import pdfplumber
+import requests
+
+
+# Specify where your data lives.
+DATA_DIR = '../data/il'
+ENV_FILE = '../.env'
+
+# Specify state-specific constants.
+STATE = 'IL'
+ILLINOIS = {
+    'licensing_authority_id': 'IDFPR',
+    'licensing_authority': 'Illinois Department of Financial and Professional Regulation',
+    'retailers': {
+        'url': 'https://www.idfpr.com/LicenseLookup/AdultUseDispensaries.pdf',
+        'columns': [
+            'business_legal_name',
+            'business_dba_name',
+            'address',
+            'medical',
+            'issue_date',
+            'license_number', 
+        ],
+    },
+}
+
+
+def get_licenses_il(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+        **kwargs,
+    ):
+    """Get Illinois cannabis license data."""
+
+    # Create necessary directories.
+    pdf_dir = f'{data_dir}/pdfs'
+    if not os.path.exists(data_dir): os.makedirs(data_dir)
+    if not os.path.exists(pdf_dir): os.makedirs(pdf_dir)
+
+    # Download the retailers PDF.
+    retailers_url = ILLINOIS['retailers']['url']
+    filename = f'{pdf_dir}/illinois_retailers.pdf'
+    response = requests.get(retailers_url)
+    with open(filename, 'wb') as f:
+        f.write(response.content)
+
+    # Read the retailers PDF.
+    pdf = pdfplumber.open(filename)
+
+    # Get the table data, excluding the headers and removing empty cells.
+    table_data = []
+    for i, page in enumerate(pdf.pages):
+        table = page.extract_table()
+        if i == 0:
+            table = table[4:]
+            table = [c for row in table
+                if (c := [elem for elem in row if elem is not None])]
+        table_data += table
+        
+    # Standardize the data.
+    licensee_columns = ILLINOIS['retailers']['columns']
+    retailers = pd.DataFrame(table_data, columns=licensee_columns)
+    retailers = retailers.assign(
+        licensing_authority_id=ILLINOIS['licensing_authority_id'],
+        licensing_authority=ILLINOIS['licensing_authority'],
+        license_designation='Adult-Use',
+        premise_state=STATE,
+        license_status='Active',
+        license_status_date=None,
+        license_type='Commercial - Retailer',
+        license_term=None,
+        expiration_date=None,
+        business_legal_name=retailers['business_dba_name'],
+        business_owner_name=None,
+        business_structure=None,
+        business_email=None,
+        activity=None,
+        parcel_number=None,
+        id=retailers['license_number'],
+        business_image_url=None,
+        business_website=None,
+    )
+
+    # Apply `medical` to `license_designation`
+    retailers.loc[retailers['medical'] == 'Yes', 'license_designation'] = 'Adult-Use and Medicinal'
+    retailers.drop(columns=['medical'], inplace=True)
+
+    # Clean the organization names.
+    retailers['business_legal_name'] = retailers['business_legal_name'].str.replace('\n', '', regex=False)
+    retailers['business_dba_name'] = retailers['business_dba_name'].str.replace('*', '', regex=False)
+
+    # Separate address into 'street', 'city', 'state', 'zip_code', 'phone_number'.
+    streets, cities, states, zip_codes, phone_numbers = [], [], [], [], []
+    for index, row in retailers.iterrows():
+        parts = row.address.split(' \n')
+        streets.append(parts[0])
+        phone_numbers.append(parts[-1])
+        locales = parts[1]
+        city_locales = locales.split(', ')
+        state_locales = city_locales[-1].split(' ')
+        cities.append(city_locales[0])
+        states.append(state_locales[0])
+        zip_codes.append(state_locales[-1])
+    retailers['premise_street_address'] = pd.Series(streets)
+    retailers['premise_city'] = pd.Series(cities)
+    retailers['premise_state'] = pd.Series(states)
+    retailers['premise_zip_code'] = pd.Series(zip_codes)
+    retailers['business_phone'] = pd.Series(phone_numbers)
+
+    # Convert the issue date to ISO format.
+    retailers['issue_date'] = retailers['issue_date'].apply(
+        lambda x: pd.to_datetime(x).isoformat()
+    )
+
+    # Get the refreshed date.
+    date = pdf.metadata['ModDate'].replace('D:', '')
+    date = date[:4] + '-' + date[4:6] + '-' + date[6:8] + 'T' + date[8:10] + \
+        ':' + date[10:12] + ':' + date[12:].replace("'", ':').rstrip(':')
+    retailers['data_refreshed_date'] = date
+
+    # Geocode licenses to get `premise_latitude` and `premise_longitude`.
+    config = dotenv_values(env_file)
+    google_maps_api_key = config['GOOGLE_MAPS_API_KEY']
+    retailers['address'] = retailers['address'].str.replace('*', '', regex=False)
+    retailers = geocode_addresses(
+        retailers,
+        api_key=google_maps_api_key,
+        address_field='address',
+    )
+    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:
+        timestamp = datetime.now().isoformat()[:19].replace(':', '-')
+        retailers.to_csv(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
+    return retailers
+
+
+# === 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_il(data_dir, env_file=env_file)

algorithms/get_licenses_ma.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,9 +15,132 @@ Description:
 
 Data Source:
 
-    - Massachusetts
-    URL: <>
+    - Massachusetts Cannabis Control Commission Data Catalog
+    URL: <https://masscannabiscontrol.com/open-data/data-catalog/>
 
 """
+# Standard imports.
+from datetime import datetime
+import os
+from typing import Optional
 
+# External imports.
+from cannlytics.data.opendata import OpenData
 
+
+# Specify where your data lives.
+DATA_DIR = '../data/ma'
+
+# Specify state-specific constants.
+STATE = 'MA'
+MASSACHUSETTS = {
+    'licensing_authority_id': 'MACCC',
+    'licensing_authority': 'Massachusetts Cannabis Control Commission',
+    'licenses': {
+        'columns': {
+            'license_number': 'license_number',
+            'business_name': 'business_legal_name',
+            'establishment_address_1': 'premise_street_address',
+            'establishment_address_2': 'premise_street_address_2',
+            'establishment_city': 'premise_city',
+            'establishment_zipcode': 'premise_zip_code',
+            'county': 'premise_county',
+            'license_type': 'license_type',
+            'application_status': 'license_status',
+            'lic_status': 'license_term',
+            'approved_license_type': 'license_designation',
+            'commence_operations_date': 'license_status_date',
+            'massachusetts_business': 'id',
+            'dba_name': 'business_dba_name',
+            'establishment_activities': 'activity',
+            'cccupdatedate': 'data_refreshed_date',
+            'establishment_state': 'premise_state',
+            'latitude': 'premise_latitude',
+            'longitude': 'premise_longitude',
+        },
+        'drop': [
+            'square_footage_establishment',
+            'cooperative_total_canopy',
+            'cooperative_cultivation_environment',
+            'establishment_cultivation_environment',
+            'abutters_count',
+            'is_abutters_notified',
+            'business_zipcode',
+            'dph_rmd_number',
+            'geocoded_county',
+            'geocoded_address',
+            'name_of_rmd',
+            'priority_applicant_type',
+            'rmd_priority_certification',
+            'dba_registration_city',
+            'county_lat',
+            'county_long',
+        ]
+    },
+}
+
+
+def get_licenses_ma(
+        data_dir: Optional[str] = None,
+        **kwargs,
+    ):
+    """Get Massachusetts cannabis license data."""
+
+    # Get the licenses data.
+    ccc = OpenData()
+    licenses = ccc.get_licensees('approved')
+
+    # Standardize the licenses data.
+    constants = MASSACHUSETTS['licenses']
+    licenses.drop(columns=constants['drop'], inplace=True)
+    licenses.rename(columns=constants['columns'], inplace=True)
+    licenses = licenses.assign(
+        licensing_authority_id=MASSACHUSETTS['licensing_authority_id'],
+        licensing_authority=MASSACHUSETTS['licensing_authority'],
+        business_structure=None,
+        business_email=None,
+        business_owner_name=None,
+        parcel_number=None,
+        issue_date=None,
+        expiration_date=None,
+        business_image_url=None,
+        business_website=None,
+        business_phone=None,
+    )
+
+    # Append `premise_street_address_2` to `premise_street_address`.
+    cols = ['premise_street_address', 'premise_street_address_2']
+    licenses['premise_street_address'] = licenses[cols].apply(
+        lambda x : '{} {}'.format(x[0].strip(), x[1]).replace('nan', '').strip().replace('  ', ' '),
+        axis=1,
+    )
+    licenses.drop(columns=['premise_street_address_2'], inplace=True)
+
+    # Optional: Look-up business websites for each license.
+
+    # 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'].str.contains('Retailer')]
+        retailers.to_csv(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
+        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)
+        args = arg_parser.parse_args()
+    except SystemExit:
+        args = {'d': DATA_DIR}
+
+    # Get licenses, saving them to the specified directory.
+    data_dir = args.get('d', args.get('data_dir'))
+    data = get_licenses_ma(data_dir)

algorithms/get_licenses_me.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/30/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -90,7 +90,7 @@ def get_licenses_me(
             break
 
     # Download the licenses workbook.
-    filename = licenses_url.split('/')[-1]
+    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:
@@ -99,21 +99,24 @@ def get_licenses_me(
     # Extract the data from the license workbook.
     licenses = pd.read_excel(licenses_source_file)
     licenses.rename(columns=MAINE['licenses']['columns'], inplace=True)
-    licenses['licensing_authority_id'] = MAINE['licensing_authority_id']
-    licenses['licensing_authority'] = MAINE['licensing_authority']
-    licenses['license_designation'] = 'Adult-Use'
-    licenses['premise_state'] = STATE
-    licenses['license_status_date'] = None
-    licenses['license_term'] = None
-    licenses['issue_date'] = None
-    licenses['expiration_date'] = None
-    licenses['business_structure'] = None
-    licenses['business_email'] = None
-    licenses['business_phone'] = None
-    licenses['activity'] = None
-    licenses['parcel_number'] = None
-    licenses['premise_street_address'] = None
-    licenses['id'] = licenses['license_number']
+    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)
@@ -137,31 +140,30 @@ def get_licenses_me(
 
     # Geocode licenses to get `premise_latitude` and `premise_longitude`.
     config = dotenv_values(env_file)
-    google_maps_api_key = config['GOOGLE_MAPS_API_KEY']
+    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,
-        api_key=google_maps_api_key,
-        address_field='address',
-    )
+    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']
-    licenses.drop(columns=drop_cols, inplace=True)
     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_excel(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.xlsx')
+        licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False)
     return licenses
 
 

algorithms/get_licenses_mi.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/8/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,7 +15,245 @@ Description:
 
 Data Source:
 
-    - Michigan
-    URL: <>
+    - Michigan Cannabis Regulatory Agency
+    URL: <https://michigan.maps.arcgis.com/apps/webappviewer/index.html?id=cd5a1a76daaf470b823a382691c0ff60>
 
-"""
+"""
+# Standard imports.
+from datetime import datetime
+import os
+from time import sleep
+from typing import Optional
+
+# External imports.
+from cannlytics.data.gis import geocode_addresses
+from dotenv import dotenv_values
+import pandas as pd
+
+# Selenium imports.
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+from selenium.webdriver.common.by import By
+from selenium.webdriver.chrome.service import Service
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support.ui import Select
+try:
+    import chromedriver_binary  # Adds chromedriver binary to path.
+except ImportError:
+    pass # Otherwise, ChromeDriver should be in your path.
+
+
+# Specify where your data lives.
+DATA_DIR = '../data/mi'
+ENV_FILE = '../.env'
+
+# Specify state-specific constants.
+STATE = 'MI'
+MICHIGAN = {
+    'licensing_authority_id': 'CRA',
+    'licensing_authority': 'Michigan Cannabis Regulatory Agency',
+    'licenses_url': 'https://aca-prod.accela.com/MIMM/Cap/CapHome.aspx?module=Adult_Use&TabName=Adult_Use',
+    'medicinal_url': 'https://aca-prod.accela.com/MIMM/Cap/CapHome.aspx?module=Licenses&TabName=Licenses&TabList=Home%7C0%7CLicenses%7C1%7CAdult_Use%7C2%7CEnforcement%7C3%7CRegistryCards%7C4%7CCurrentTabIndex%7C1',
+    'licenses': {
+        'columns': {
+            'Record Number': 'license_number',
+            'Record Type': 'license_type',
+            'License Name': 'business_legal_name',
+            'Address': 'address',
+            'Expiration Date': 'expiration_date',
+            'Status': 'license_status',
+            'Action': 'activity',
+            'Notes': 'license_designation',
+            'Disciplinary Action': 'license_term',
+        },
+    },
+}
+
+
+def wait_for_id_invisible(driver, value, seconds=30):
+    """Wait for a given value to be invisible."""
+    WebDriverWait(driver, seconds).until(
+        EC.invisibility_of_element((By.ID, value))
+    )
+
+
+def get_licenses_mi(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+    ):
+    """Get Michigan cannabis license data."""
+
+    # Initialize Selenium and specify options.
+    service = Service()
+    options = Options()
+    options.add_argument('--window-size=1920,1200')
+
+    # DEV: Run with the browser open.
+    options.headless = False
+
+    # PRODUCTION: Run with the browser closed.
+    # options.add_argument('--headless')
+    # options.add_argument('--disable-gpu')
+    # options.add_argument('--no-sandbox')
+
+    # Initiate a Selenium driver.
+    driver = webdriver.Chrome(options=options, service=service)
+
+    # Load the license page.
+    url = MICHIGAN['licenses_url']
+    driver.get(url)
+
+    # Get the various license types, excluding certain types without addresses.
+    select = Select(driver.find_element(by=By.TAG_NAME, value='select'))
+    license_types = []
+    options = driver.find_elements(by=By.TAG_NAME, value='option')
+    for option in options:
+        text = option.text
+        if text and '--' not in text:
+            license_types.append(text)
+    
+    # Restrict certain license types.
+    license_types = license_types[1:-2]
+
+    # FIXME: Iterate over license types.
+    data = []
+    columns = list(MICHIGAN['licenses']['columns'].values())
+    for license_type in license_types:
+
+        # Select the various license types.
+        try:
+            select.select_by_visible_text(license_type)
+        except:
+            pass
+        wait_for_id_invisible(driver, 'divGlobalLoading')
+
+        # Click the search button.
+        search_button = driver.find_element(by=By.ID, value='ctl00_PlaceHolderMain_btnNewSearch')
+        search_button.click()
+        wait_for_id_invisible(driver, 'divGlobalLoading')
+
+        # Iterate over all of the pages.
+        iterate = True
+        while iterate:
+
+            # Get all of the license data.
+            grid = driver.find_element(by=By.ID, value='ctl00_PlaceHolderMain_dvSearchList')
+            rows = grid.find_elements(by=By.TAG_NAME, value='tr')
+            rows = [x.text for x in rows]
+            rows = [x for x in rows if 'Download results' not in x and not x.startswith('< Prev')]
+            cells = []
+            for row in rows[1:]: # Skip the header.
+                obs = {}
+                cells = row.split('\n')
+                for i, cell in enumerate(cells):
+                    column = columns[i]
+                    obs[column] = cell
+                data.append(obs)
+
+            # Keep clicking the next button until the next button is disabled.
+            next_button = driver.find_elements(by=By.CLASS_NAME, value='aca_pagination_PrevNext')[-1]
+            current_page = driver.find_element(by=By.CLASS_NAME, value='SelectedPageButton').text
+            next_button.click()
+            wait_for_id_invisible(driver, 'divGlobalLoading')
+            next_page = driver.find_element(by=By.CLASS_NAME, value='SelectedPageButton').text
+            if current_page == next_page:
+                iterate = False
+
+    # TODO: Also get all of the medical licenses!
+    # https://aca-prod.accela.com/MIMM/Cap/CapHome.aspx?module=Licenses&TabName=Licenses&TabList=Home%7C0%7CLicenses%7C1%7CAdult_Use%7C2%7CEnforcement%7C3%7CRegistryCards%7C4%7CCurrentTabIndex%7C1
+
+    # End the browser session.
+    service.stop()
+
+    # Standardize the data.
+    licenses = pd.DataFrame(data)
+    licenses = licenses.assign(
+        id=licenses.index,
+        licensing_authority_id=MICHIGAN['licensing_authority_id'],
+        licensing_authority=MICHIGAN['licensing_authority'],
+        premise_state=STATE,
+        license_status_date=None,
+        issue_date=None,
+        business_owner_name=None,
+        business_structure=None,
+        parcel_number=None,
+        business_phone=None,
+        business_email=None,
+        business_image_url=None,
+        license_designation=None,
+        business_website=None,
+        business_dba_name=licenses['business_legal_name'],
+    )
+
+    # Assign `license_term` if necessary.
+    try:
+        licenses['license_term']
+    except KeyError:
+        licenses['license_term'] = None
+
+    # Clean `license_type`.
+    licenses['license_type'] = licenses['license_type'].apply(
+        lambda x: x.replace(' - License', '')
+    )
+
+    # Format expiration date as an ISO formatted date.
+    licenses['expiration_date'] = licenses['expiration_date'].apply(
+        lambda x: pd.to_datetime(x).isoformat()
+    )
+
+    # Geocode the licenses.
+    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']
+    gis_cols = {
+        'county': 'premise_county',
+        'latitude': 'premise_latitude',
+        'longitude': 'premise_longitude'
+    }
+    licenses.drop(columns=drop_cols, inplace=True)
+    licenses.rename(columns=gis_cols, inplace=True)
+
+    # Get the refreshed date.
+    licenses['data_refreshed_date'] = datetime.now().isoformat()
+
+    # 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)
+    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_mi(data_dir, env_file=env_file)

algorithms/get_licenses_mt.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/27/2022
-Updated: 9/30/2022
+Updated: 10/5/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -22,12 +22,13 @@ Data Source:
 # Standard imports.
 from datetime import datetime
 import os
-from time import sleep
+from typing import Optional
 
 # External imports.
-from bs4 import BeautifulSoup
-from cannlytics.utils import camel_to_snake
+from cannlytics.data.gis import search_for_address
 from cannlytics.utils.constants import DEFAULT_HEADERS
+from dotenv import dotenv_values
+import pandas as pd
 import pdfplumber
 import requests
 
@@ -39,6 +40,32 @@ ENV_FILE = '../.env'
 # Specify state-specific constants.
 STATE = 'MT'
 MONTANA = {
+    'licensing_authority_id': 'MTCCD',
+    'licensing_authority': 'Montana Cannabis Control Division',
+    'licenses': {
+        'columns': [
+            {
+                'key': 'premise_city',
+                'name': 'City',
+                'area': [0, 0.25, 0.2, 0.95],
+            },
+            {
+                'key': 'business_legal_name',
+                'name': 'Location Name',
+                'area': [0.2, 0.25, 0.6, 0.95],
+            },
+            {
+                'key': 'license_designation',
+                'name': 'Sales Type',
+                'area': [0.6, 0.25, 0.75, 0.95],
+            },
+            {
+                'key': 'business_phone',
+                'name': 'Phone Number',
+                'area': [0.75, 0.25, 1, 0.95],
+            },
+        ]
+    },
     'retailers': {
         'url': 'https://mtrevenue.gov/?mdocs-file=60245',
         'columns': ['city', 'dba', 'license_type', 'phone']
@@ -49,104 +76,203 @@ MONTANA = {
     'transporters': {'url': 'https://mtrevenue.gov/?mdocs-file=72489'},
 }
 
-# DEV:
-data_dir = DATA_DIR
-pdf_dir = f'{data_dir}/pdfs'
-
-# Create directories if necessary.
-if not os.path.exists(data_dir): os.makedirs(data_dir)
-if not os.path.exists(pdf_dir): os.makedirs(pdf_dir)
-
-# Download the retailers PDF.
-timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-outfile = f'{pdf_dir}/mt-retailers-{timestamp}.pdf'
-response = requests.get(MONTANA['retailers']['url'], headers=DEFAULT_HEADERS)
-with open(outfile, 'wb') as pdf:
-    pdf.write(response.content)
-
-# FIXME: Extract text by section!
-# E.g.
-# doc = pdfplumber.open(outfile)
-# page = doc.pages[0]
-# img = page.to_image(resolution=150)
-# img.draw_rects(
-#     [[0, 0.25 * page.height, 0.2 * page.width, 0.95 * page.height]]
-# )
-
-# Extract the data from the PDF.
-rows = []
-skip_lines = ['GOVERNOR ', 'DIRECTOR ', 'Cannabis Control Division',
-'Licensed Dispensary locations', 'Please note', 'registered ',
-'City Location Name Sales Type Phone Number', 'Page ']
-doc = pdfplumber.open(outfile)
-for page in doc.pages:
-    text = page.extract_text()
-    lines = text.split('\n')
-    for line in lines:
-        skip = False
-        for skip_line in skip_lines:
-            if line.startswith(skip_line):
-                skip = True
+
+def get_licenses_mt(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+    ):
+    """Get Montana cannabis license data."""
+
+    # Create directories if necessary.
+    pdf_dir = f'{data_dir}/pdfs'
+    if not os.path.exists(data_dir): os.makedirs(data_dir)
+    if not os.path.exists(pdf_dir): os.makedirs(pdf_dir)
+
+    # Download the retailers PDF.
+    timestamp = datetime.now().isoformat()[:19].replace(':', '-')
+    outfile = f'{pdf_dir}/mt-retailers-{timestamp}.pdf'
+    response = requests.get(MONTANA['retailers']['url'], headers=DEFAULT_HEADERS)
+    with open(outfile, 'wb') as pdf:
+        pdf.write(response.content)
+
+    # Read the PDF.
+    doc = pdfplumber.open(outfile)
+
+    # Get the table rows.
+    rows = []
+    front_page = doc.pages[0]
+    width, height = front_page.width, front_page.height
+    x0, y0, x1, y1 = tuple([0, 0.25, 1, 0.95])
+    page_area = (x0 * width, y0 * height, x1 * width, y1 * height)
+    for page in doc.pages:
+        crop = page.within_bbox(page_area)
+        text = crop.extract_text()
+        lines = text.split('\n')
+        for line in lines:
+            rows.append(line)
+
+    # Get cities from the first column, used to identify the city for each line.
+    cities = []
+    city_area = MONTANA['licenses']['columns'][0]['area']
+    x0, y0, x1, y1 = tuple(city_area)
+    column_area = (x0 * width, y0 * height, x1 * width, y1 * height)
+    for page in doc.pages:
+        crop = page.within_bbox(column_area)
+        text = crop.extract_text()
+        lines = text.split('\n')
+        for line in lines:
+            cities.append(line)
+
+    # Find all of the unique cities.
+    cities = list(set(cities))
+    cities = [x for x in cities if x != 'City']
+
+    # Get all of the license data.
+    data = []
+    rows = [x for x in rows if not x.startswith('City')]
+    for row in rows:
+
+        # Get all of the license observation data.
+        obs = {}
+        text = str(row)
+
+        # Identify the city and remove the city from the name (only once b/c of DBAs!).
+        for city in cities:
+            if city in row:
+                obs['premise_city'] = city.title()
+                text = text.replace(city, '', 1).strip()
                 break
-        if skip:
-            continue
-        rows.append(line)
-
-# Collect licensee data.
-licensees = []
-for row in rows:
-
-    # FIXME: Rows with double-line text get cut-off.
-    if '(' not in row:
-        continue
-
-    obs = {}
-    if 'Adult Use' in row:
-        parts = row.split('Adult Use')
-        obs['license_type'] = 'Adult Use'
-    else:
-        parts = row.split('Medical Only')
-        obs['license_type'] = 'Medical Only'
-    obs['dba'] = parts[0].strip()
-    obs['phone'] = parts[-1].strip()
-    licensees.append(obs)
-
-# Get a list of Montana cities.
-cities = []
-# response = requests.get('http://www.mlct.org/', headers=DEFAULT_HEADERS)
-# soup = BeautifulSoup(response.content, 'html.parser')
-# table = soup.find('table')
-# for tr in table.findAll('tr'):
-#     if not tr.text.strip().replace('\n', ''):
-#         continue
-#     city = tr.find('td').text
-#     if '©' in city or ',' in city or '\n' in city or city == 'Home' or city == 'City':
-#         continue
-#     cities.append(city)
-
-# remove_lines = ['RESOURCES', 'Official State Website', 'State Legislature',
-# 'Chamber of Commerce', 'Contact Us']
-# for ele in remove_lines:
-#     cities.remove(ele)
-
-# FIXME:
-url = 'https://dojmt.gov/wp-content/uploads/2011/05/mvmtcitiescountieszips.pdf'
-
-# TODO: Separate `city` from `dba` using list of Montana cities.
-for i, licensee in enumerate(licensees):
-    dba = licensee['dba']
-    city_found = False
-    for city in cities:
-        city_name = city.upper()
-        if city_name in dba:
-            licensees[i]['dba'] = dba.replace(city_name, '').strip()
-            licensees[i]['city'] = city
-            city_found = True
-            break
-    if not city_found:
-        print("Couldn't identify city:", dba)
-
-# TODO: Remove duplicates.
-
-
-# TODO: Lookup the address of the licenses?
+
+        # Identify the license designation.
+        if 'Adult Use' in row:
+            parts = text.split('Adult Use')
+            obs['license_designation'] = 'Adult Use'
+        else:
+            parts = text.split('Medical Only')
+            obs['license_designation'] = 'Medical Only'
+        
+        # Skip rows with double-row text.
+        if len(row) == 1: continue
+
+        # Record the name.
+        obs['business_legal_name'] = name = parts[0]
+
+        # Record the phone number.
+        if '(' in text:
+            obs['business_phone'] = parts[-1].strip()
+
+        # Record the observation.
+        data.append(obs)
+
+    # Aggregate the data.
+    retailers = pd.DataFrame(data)
+    retailers = retailers.loc[~retailers['premise_city'].isna()]
+
+    # Convert certain columns from upper case title case.
+    cols = ['business_legal_name', 'premise_city']
+    for col in cols:
+        retailers[col] = retailers[col].apply(
+            lambda x: x.title().replace('Llc', 'LLC').replace("'S", "'s").strip()
+        )
+
+    # Standardize the data.
+    retailers['id'] = retailers.index
+    retailers['license_number'] = None # FIXME: It would be awesome to find these!
+    retailers['licensing_authority_id'] = MONTANA['licensing_authority_id']
+    retailers['licensing_authority'] = MONTANA['licensing_authority']
+    retailers['premise_state'] = STATE
+    retailers['license_status'] = 'Active'
+    retailers['license_status_date'] = None
+    retailers['license_type'] = 'Commercial - Retailer'
+    retailers['license_term'] = None
+    retailers['issue_date'] = None
+    retailers['expiration_date'] = None
+    retailers['business_owner_name'] = None
+    retailers['business_structure'] = None
+    retailers['activity'] = None
+    retailers['parcel_number'] = None
+    retailers['business_email'] = None
+    retailers['business_image_url'] = None
+
+    # Separate any `business_dba_name` from `business_legal_name`.
+    retailers['business_dba_name'] = retailers['business_legal_name']
+    criterion = retailers['business_legal_name'].str.contains('Dba')
+    retailers.loc[criterion, 'business_dba_name'] = retailers.loc[criterion] \
+        ['business_legal_name'].apply(lambda x: x.split('Dba')[-1].strip())
+    retailers.loc[criterion, 'business_legal_name'] = retailers.loc[criterion] \
+        ['business_legal_name'].apply(lambda x: x.split('Dba')[0].strip())
+
+    # 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']
+    retailers['query'] = retailers[cols].apply(
+        lambda row: ', '.join(row.values.astype(str)),
+        axis=1,
+    )
+    queries = {}
+    fields = [
+        'formatted_address',
+        'geometry/location/lat',
+        'geometry/location/lng',
+        'website',
+    ]
+    retailers = retailers.reset_index(drop=True)
+    retailers = retailers.assign(
+        premise_street_address=None,
+        premise_county=None,
+        premise_zip_code=None,
+        premise_latitude=None,
+        premise_longitude=None,
+        business_website=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_zip_code')] = gis_data.get('zipcode')
+        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')
+        
+    # Clean-up after getting GIS data.
+    retailers.drop(columns=['query'], inplace=True)
+
+    # Get the refreshed date.
+    retailers['data_refreshed_date'] = datetime.now().isoformat()
+
+    # 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}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
+    return retailers
+
+
+# === 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_mt(data_dir, env_file=env_file)

algorithms/get_licenses_nj.py

@@ -92,6 +92,11 @@ def get_licenses_nj(
     data['business_email'] = None
     data['activity'] = None
     data['parcel_number'] = None
+    data['business_image_url'] = None
+    data['id'] = None
+    data['license_number'] = None
+    data['license_status'] = None
+    data['data_refreshed_date'] = datetime.now().isoformat()
 
     # Convert certain columns from upper case title case.
     cols = ['premise_city', 'premise_county', 'premise_street_address']
@@ -102,7 +107,7 @@ def get_licenses_nj(
     if data_dir is not None:
         if not os.path.exists(data_dir): os.makedirs(data_dir)
         timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-        data.to_excel(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.xlsx')
+        data.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False)
     return data
 
 

algorithms/get_licenses_nm.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/6/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -15,7 +15,295 @@ Description:
 
 Data Source:
 
-    - New Mexico
-    URL: <>
+    - New Mexico Regulation and Licensing Department | Cannabis Control Division
+    URL: <https://nmrldlpi.force.com/bcd/s/public-search-license?division=CCD&language=en_US>
 
-"""
+"""
+# Standard imports.
+from datetime import datetime
+import os
+from time import sleep
+from typing import Optional
+
+# External imports.
+from cannlytics.data.gis import geocode_addresses, search_for_address
+from dotenv import dotenv_values
+import pandas as pd
+
+# Selenium imports.
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+from selenium.webdriver.common.by import By
+from selenium.webdriver.chrome.service import Service
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.webdriver.support.ui import WebDriverWait
+try:
+    import chromedriver_binary  # Adds chromedriver binary to path.
+except ImportError:
+    pass # Otherwise, ChromeDriver should be in your path.
+
+
+# Specify where your data lives.
+DATA_DIR = '../data/nm'
+ENV_FILE = '../.env'
+
+# Specify state-specific constants.
+STATE = 'NM'
+NEW_MEXICO = {
+    'licensing_authority_id': 'NMCCD',
+    'licensing_authority': 'New Mexico Cannabis Control Division',
+    'licenses_url': 'https://nmrldlpi.force.com/bcd/s/public-search-license?division=CCD&language=en_US',
+}
+
+
+def get_licenses_nm(
+        data_dir: Optional[str] = None,
+        env_file: Optional[str] = '.env',
+    ):
+    """Get New Mexico cannabis license data."""
+
+    # Create directories if necessary.
+    if not os.path.exists(data_dir): os.makedirs(data_dir)
+
+    # Initialize Selenium and specify options.
+    service = Service()
+    options = Options()
+    options.add_argument('--window-size=1920,1200')
+
+    # DEV: Run with the browser open.
+    options.headless = False
+
+    # PRODUCTION: Run with the browser closed.
+    # options.add_argument('--headless')
+    # options.add_argument('--disable-gpu')
+    # options.add_argument('--no-sandbox')
+
+    # Initiate a Selenium driver.
+    driver = webdriver.Chrome(options=options, service=service)
+
+    # Load the license page.
+    driver.get(NEW_MEXICO['licenses_url'])
+
+    # FIXME: Wait for the page to load by waiting to detect the image.
+    # try:
+    #     el = (By.CLASS_NAME, 'slds-radio--faux')
+    #     WebDriverWait(driver, 15).until(EC.presence_of_element_located(el))
+    # except TimeoutException:
+    #     print('Failed to load page within %i seconds.' % (30))
+    sleep(5)
+
+    # Get the main content and click "License Type" raido.
+    content = driver.find_element(by=By.CLASS_NAME, value='siteforceContentArea')
+    radio = content.find_element(by=By.CLASS_NAME, value='slds-radio--faux')
+    radio.click()
+    sleep(2)
+
+    # Select retailers.
+    # TODO: Also get "Cannabis Manufacturer", "Cannabis Producer", and
+    # "Cannabis Producer Microbusiness".
+    search = content.find_element(by=By.ID, value='comboboxId-40')
+    search.click()
+    choices = content.find_elements(by=By.CLASS_NAME, value='slds-listbox__item')
+    for choice in choices:
+        if choice.text == 'Cannabis Retailer':
+            choice.click()
+            sleep(2)
+            break
+
+    # Click the search button.
+    search = content.find_element(by=By.CLASS_NAME, value='vlocity-btn')
+    search.click()
+    sleep(2)
+
+    # Iterate over all of the pages.
+    # Wait for the table to load, then iterate over the pages.
+    sleep(5)
+    data = []
+    iterate = True
+    while(iterate):
+
+        # Get all of the licenses.
+        items = content.find_elements(by=By.CLASS_NAME, value='block-container')
+        for item in items[3:]:
+            text = item.text
+            if not text:
+                continue
+            values = text.split('\n')
+            data.append({
+                'license_type': values[0],
+                'license_status': values[1],
+                'business_legal_name': values[2],
+                'address': values[-1],
+                'details_url': '',
+            })
+
+        # Get the page number and stop at the last page.
+        # FIXME: This doesn't correctly break!
+        par = content.find_elements(by=By.TAG_NAME, value='p')[-1].text
+        page_number = int(par.split(' ')[2])
+        total_pages = int(par.split(' ')[-2])
+        if page_number == total_pages:
+            iterate = False
+
+        # Otherwise, click the next button.
+        buttons = content.find_elements(by=By.TAG_NAME, value='button')
+        for button in buttons:
+            if button.text == 'Next Page':
+                button.click()
+                sleep(5)
+                break
+
+    # Search for each license name, 1 by 1, to get details.
+    retailers = pd.DataFrame(columns=['business_legal_name'])
+    for i, licensee in enumerate(data):
+
+        # Skip recorded rows.
+        if len(retailers.loc[retailers['business_legal_name'] == licensee['business_legal_name']]):
+            continue
+
+        # Click the "Business Name" search field.
+        content = driver.find_element(by=By.CLASS_NAME, value='siteforceContentArea')
+        radio = content.find_elements(by=By.CLASS_NAME, value='slds-radio--faux')[1]
+        radio.click()
+        sleep(1)
+
+        # Enter the `business_legal_name` into the search.
+        search_field = content.find_element(by=By.CLASS_NAME, value='vlocity-input')
+        search_field.clear()
+        search_field.send_keys(licensee['business_legal_name'])
+
+        # Click the search button.
+        search = content.find_element(by=By.CLASS_NAME, value='vlocity-btn')
+        search.click()
+
+        # FIXME: Wait for the table to load.
+        # WebDriverWait(content, 5).until(EC.presence_of_element_located((By.CLASS_NAME, 'slds-button_icon')))
+        sleep(1.5)
+
+        # Click the "Action" button to get to the details page.
+        # FIXME: There can be multiple search candidates!
+        action = content.find_element(by=By.CLASS_NAME, value='slds-button_icon')
+        try:
+            action.click()
+        except:
+            continue # FIXME: Formally check if "No record found!".
+
+        # FIXME: Wait for the details page to load.
+        el = (By.CLASS_NAME, 'body')
+        WebDriverWait(driver, 5).until(EC.presence_of_element_located(el))
+
+        # Get the page
+        page = driver.find_element(by=By.CLASS_NAME, value='body')
+
+        # FIXME: Wait for the details to load!
+        # el = (By.TAG_NAME, 'vlocity_ins-omniscript-step')
+        # WebDriverWait(page, 5).until(EC.presence_of_element_located(el))
+        sleep(1.5)
+
+        # Get all of the details!
+        fields = [
+            'license_number',
+            'license_status',
+            'issue_date',
+            'expiration_date',
+            'business_owner_name',
+        ]
+        values = page.find_elements(by=By.CLASS_NAME, value='field-value')
+        if len(values) > 5:
+            for j, value in enumerate(values[:5]):
+                data[i][fields[j]] = value.text
+            for value in values[5:]:
+                data[i]['business_owner_name'] += f', {value.text}'
+        else:
+            for j, value in enumerate(values):
+                data[i][fields[j]] = value.text
+
+        # Create multiple entries for each address!!!
+        premises = page.find_elements(by=By.CLASS_NAME, value='block-header')
+        for premise in premises:
+            values = premise.text.split('\n')
+            licensee['address'] = values[0].replace(',', ', ')
+            licensee['license_number'] = values[2]
+            retailers = pd.concat([retailers, pd.DataFrame([licensee])])
+
+        # Click the "Back to Search" button.
+        back_button = page.find_element(by=By.CLASS_NAME, value='vlocity-btn')
+        back_button.click()
+        sleep(1)
+
+    # End the browser session.
+    service.stop()
+
+    # Standardize the data, restricting to "Approved" retailers.
+    retailers = retailers.loc[retailers['license_status'] == 'Active']
+    retailers = retailers.assign(
+        business_email=None,
+        business_structure=None,
+        licensing_authority_id=NEW_MEXICO['licensing_authority_id'],
+        licensing_authority=NEW_MEXICO['licensing_authority'],
+        license_designation='Adult-Use',
+        license_status_date=None,
+        license_term=None,
+        premise_state=STATE,
+        parcel_number=None,
+        activity=None,
+        business_image_url=None,
+        business_website=None,
+        business_phone=None,
+        id=retailers['license_number'],
+        business_dba_name=retailers['business_legal_name'],
+    )
+
+    # Get the refreshed date.
+    retailers['data_refreshed_date'] = datetime.now().isoformat()
+
+    # Geocode licenses.
+    # FIXME: This is not working as intended. Perhaps try `search_for_address`?
+    config = dotenv_values(env_file)
+    api_key = config['GOOGLE_MAPS_API_KEY']
+    retailers = geocode_addresses(retailers, api_key=api_key, address_field='address')
+    retailers['premise_street_address'] = retailers['formatted_address'].apply(
+        lambda x: x.split(',')[0] if STATE in str(x) else x
+    )
+    retailers['premise_city'] = retailers['formatted_address'].apply(
+        lambda x: x.split(', ')[1].split(',')[0] if STATE in str(x) else x
+    )
+    retailers['premise_zip_code'] = retailers['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',
+        'details_url']
+    gis_cols = {
+        'county': 'premise_county',
+        'latitude': 'premise_latitude',
+        'longitude': 'premise_longitude'
+    }
+    retailers.drop(columns=drop_cols, inplace=True)
+    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}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
+    return retailers
+
+
+# === 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_nm(data_dir, env_file=env_file)

algorithms/get_licenses_nv.py

@@ -93,6 +93,7 @@ def get_licenses_nv(
     # Extract and standardize the data from the workbook.
     licenses = pd.read_excel(licenses_source_file, skiprows=1)
     licenses.rename(columns=NEVADA['licenses']['columns'], inplace=True)
+    licenses['id'] = licenses['license_number']
     licenses['licensing_authority_id'] = NEVADA['licensing_authority_id']
     licenses['licensing_authority'] = NEVADA['licensing_authority']
     licenses['license_designation'] = 'Adult-Use'
@@ -107,6 +108,9 @@ def get_licenses_nv(
     licenses['business_email'] = None
     licenses['activity'] = None
     licenses['parcel_number'] = None
+    licenses['business_image_url'] = None
+    licenses['business_phone'] = None
+    licenses['business_website'] = None
 
     # Convert certain columns from upper case title case.
     cols = ['business_dba_name', 'premise_county']
@@ -123,7 +127,7 @@ def get_licenses_nv(
     # Save the licenses    
     if data_dir is not None:
         timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-        licenses.to_excel(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.xlsx')
+        licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False)
 
     #--------------------------------------------------------------------------
     # Get retailer data
@@ -168,6 +172,15 @@ def get_licenses_nv(
     retailers['business_email'] = None
     retailers['activity'] = None
     retailers['parcel_number'] = None
+    retailers['business_website'] = None
+    retailers['business_image_url'] = None
+    retailers['business_phone'] = None
+
+    # FIXME: Merge `license_number`, `premise_county`, `data_refreshed_date`
+    # from licenses.
+    retailers['license_number'] = None
+    retailers['id'] = None
+    retailers['data_refreshed_date'] = datetime.now().isoformat()
 
     # Geocode the retailers.
     config = dotenv_values(env_file)
@@ -182,20 +195,22 @@ def get_licenses_nv(
         api_key=google_maps_api_key,
         address_field='address',
     )
-    drop_cols = ['state', 'state_name', 'county', 'address', 'formatted_address']
-    retailers.drop(columns=drop_cols, inplace=True)
+    drop_cols = ['state', 'state_name', 'address', 'formatted_address']
     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
+    )
+    retailers.drop(columns=drop_cols, inplace=True)
     retailers.rename(columns=gis_cols, inplace=True)
 
-    # Future work: Merge the retailers with the licenses data?
-
     # Save the retailers    
     if data_dir is not None:
         timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-        retailers.to_excel(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.xlsx')
+        retailers.to_csv(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
 
     # Return all of the data.
     return pd.concat([licenses, retailers])

algorithms/get_licenses_or.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/28/2022
-Updated: 9/28/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -53,6 +53,10 @@ OREGON = {
             'Med Grade': 'medicinal',
             'Delivery': 'delivery',
         },
+        'drop_columns': [
+            'medicinal',
+            'delivery',
+        ],
     },
 }
 
@@ -90,12 +94,26 @@ def get_licenses_or(
     data['license_designation'] = 'Adult-Use'
     data['premise_state'] = 'OR'
     data.loc[data['medicinal'] == 'Yes', 'license_designation'] = 'Adult-Use and Medicinal'
-
-    # Convert `medicinal` and `delivery` columns to boolean.
-    data['medicinal'] = data['medicinal'].map(dict(Yes=1))
-    data['delivery'] = data['delivery'].map(dict(Yes=1))
-    data['medicinal'].fillna(0, inplace=True)
-    data['delivery'].fillna(0, inplace=True)
+    data['business_image_url'] = None
+    data['license_status_date'] = None
+    data['license_term'] = None
+    data['issue_date'] = None
+    data['expiration_date'] = None
+    data['business_email'] = None
+    data['business_owner_name'] = None
+    data['business_structure'] = None
+    data['business_website'] = None
+    data['activity'] = None
+    data['business_phone'] = None
+    data['parcel_number'] = None
+    data['business_legal_name'] = data['business_dba_name']
+
+    # Optional: Convert `medicinal` and `delivery` columns to boolean.
+    # data['medicinal'] = data['medicinal'].map(dict(Yes=1))
+    # data['delivery'] = data['delivery'].map(dict(Yes=1))
+    # data['medicinal'].fillna(0, inplace=True)
+    # data['delivery'].fillna(0, inplace=True)
+    data.drop(columns=['medicinal', 'delivery'], inplace=True)
 
     # Convert certain columns from upper case title case.
     cols = ['business_dba_name', 'premise_city', 'premise_county',
@@ -138,6 +156,7 @@ def get_licenses_or(
     }
     data.rename(columns=columns, inplace=True)
     data.drop(columns=['BUSINESS NAME', 'COUNTY'], inplace=True)
+    data['id'] = data['license_number']
 
     # Geocode licenses to get `premise_latitude` and `premise_longitude`.
     config = dotenv_values(env_file)
@@ -171,7 +190,7 @@ def get_licenses_or(
     # Save the license data.
     if data_dir is not None:
         timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-        data.to_excel(f'{data_dir}/licenses-or-{timestamp}.xlsx')
+        data.to_csv(f'{data_dir}/licenses-or-{timestamp}.csv', index=False)
     return data
 
 

algorithms/get_licenses_ri.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/3/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -18,4 +18,162 @@ 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)

algorithms/get_licenses_vt.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -18,4 +18,236 @@ 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)

algorithms/get_licenses_wa.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
@@ -41,6 +41,49 @@ STATE = 'WA'
 WASHINGTON = {
     'licensing_authority_id': 'WSLCB',
     'licensing_authority': 'Washington State Liquor and Cannabis Board',
+    'licenses_urls': 'https://lcb.wa.gov/records/frequently-requested-lists',
+    'labs': {
+        'key': 'Lab-List',
+        'columns': {
+            'Lab Name': 'business_legal_name',
+            'Lab #': 'license_number',
+            'Address 1': 'premise_street_address',
+            'Address 2': 'premise_street_address_2',
+            'City': 'premise_city',
+            'Zip': 'premise_zip_code',
+            'Phone': 'business_phone',
+            'Status': 'license_status',
+            'Certification Date': 'issue_date',
+        },
+        'drop_columns': [
+            'Pesticides',
+            'Heavy Metals',
+            'Mycotoxins',
+            'Water Activity',
+            'Terpenes',
+        ],
+    },
+    'medical': {
+        'key': 'MedicalCannabisEndorsements',
+        'columns': {
+            'License': 'license_number',
+            'UBI': 'id',
+            'Tradename': 'business_dba_name',
+            'Privilege': 'license_type',
+            'Status': 'license_status',
+            'Med Privilege Code': 'license_designation',
+            'Termination Code': 'license_term',
+            'Street Adress': 'premise_street_address',
+            'Suite Rm': 'premise_street_address_2',
+            'City': 'premise_city',
+            'State': 'premise_state',
+            'County': 'premise_county',
+            'Zip Code': 'premise_zip_code',
+            'Date Created': 'issue_date',
+            'Day Phone': 'business_phone',
+            'Email': 'business_email',
+        },
+    },
     'retailers': {
         'key': 'CannabisApplicants',
         'columns': {
@@ -57,10 +100,27 @@ WASHINGTON = {
             'Privilege Status': 'license_status',
             'Day Phone': 'business_phone',
         },
-    }
+    },
 }
 
 
+def download_file(url, dest='./', headers=None):
+    """Download a file from a given URL to a local destination.
+    Args:
+        url (str): The URL of the data file.
+        dest (str): The destination for the data file, `./` by default (optional).
+        headers (dict): HTTP headers, `None` by default (optional).
+    Returns:
+        (str): The location for the data file.
+    """
+    filename = url.split('/')[-1]
+    data_file = os.path.join(dest, filename)
+    response = requests.get(url, headers=headers)
+    with open(data_file, 'wb') as doc:
+        doc.write(response.content)
+    return data_file
+
+
 def get_licenses_wa(
         data_dir: Optional[str] = None,
         env_file: Optional[str] = '.env',
@@ -74,52 +134,75 @@ def get_licenses_wa(
 
     # Get the URLs for the license workbooks.
     labs_url, medical_url, retailers_url = None, None, None
-    url = 'https://lcb.wa.gov/records/frequently-requested-lists'
+    labs_key = WASHINGTON['labs']['key']
+    medical_key = WASHINGTON['medical']['key']
+    retailers_key = WASHINGTON['retailers']['key']
+    url = WASHINGTON['licenses_urls']
     response = requests.get(url)
     soup = BeautifulSoup(response.content, 'html.parser')
     links = soup.find_all('a')
     for link in links:
         href = link['href']
-        if 'Lab-List' in href:
+        if labs_key in href:
             labs_url = href
-        elif 'CannabisApplicants' in href:
+        elif retailers_key in href:
             retailers_url = href
-        elif 'MedicalCannabisEndorsements' in href:
+        elif medical_key in href:
             medical_url = href
             break
 
-    # TODO: Also download and collect lab + medical dispensary data.
-
-    # Download the licenses workbook.
-    filename = retailers_url.split('/')[-1]
-    retailers_source_file = os.path.join(file_dir, filename)
-    response = requests.get(retailers_url)
-    with open(retailers_source_file, 'wb') as doc:
-        doc.write(response.content)
+    # Download the workbooks.
+    lab_source_file = download_file(labs_url, dest=file_dir)
+    medical_source_file = download_file(medical_url, dest=file_dir)
+    retailers_source_file = download_file(retailers_url, dest=file_dir)
 
     # Extract and standardize the data from the workbook.
     retailers = pd.read_excel(retailers_source_file)
     retailers.rename(columns=WASHINGTON['retailers']['columns'], inplace=True)
-    retailers['licensing_authority_id'] = WASHINGTON['licensing_authority_id']
-    retailers['licensing_authority'] = WASHINGTON['licensing_authority']
     retailers['license_designation'] = 'Adult-Use'
-    retailers['premise_state'] = STATE
-    retailers['license_status_date'] = None
-    retailers['license_term'] = None
-    retailers['issue_date'] = None
-    retailers['expiration_date'] = None
-    retailers['business_legal_name'] = retailers['business_dba_name']
-    retailers['business_owner_name'] = None
-    retailers['business_structure'] = None
-    retailers['business_email'] = None
-    retailers['activity'] = None
-    retailers['parcel_number'] = None
+    retailers['license_type'] = 'Adult-Use Retailer'
+    
+    labs = pd.read_excel(lab_source_file)
+    labs.rename(columns=WASHINGTON['labs']['columns'], inplace=True)
+    labs.drop(columns=WASHINGTON['labs']['drop_columns'], inplace=True)
+    labs['license_type'] = 'Lab'
+
+    medical = pd.read_excel(medical_source_file, skiprows=2)
+    medical.rename(columns=WASHINGTON['medical']['columns'], inplace=True)
+    medical['license_designation'] = 'Medicinal'
+    medical['license_type'] = 'Medical Retailer'
+
+    # Aggregate the licenses.
+    licenses = pd.concat([retailers, medical, labs])
+
+    # Standardize all of the licenses at once!
+    licenses = licenses.assign(
+        licensing_authority_id=WASHINGTON['licensing_authority_id'],
+        licensing_authority=WASHINGTON['licensing_authority'],
+        premise_state=STATE,
+        license_status_date=None,
+        expiration_date=None,
+        activity=None,
+        parcel_number=None,
+        business_owner_name=None,
+        business_structure=None,
+        business_image_url=None,
+        business_website=None,
+    )
+
+    # Fill legal and DBA names.
+    licenses['id'].fillna(licenses['license_number'], inplace=True)
+    licenses['business_legal_name'].fillna(licenses['business_dba_name'], inplace=True)
+    licenses['business_dba_name'].fillna(licenses['business_legal_name'], inplace=True)
+    cols = ['business_legal_name', 'business_dba_name']
+    for col in cols:
+        licenses[col] = licenses[col].apply(
+            lambda x: x.title().replace('Llc', 'LLC').replace("'S", "'s").strip()
+        )
 
     # Keep only active licenses.
-    retailers = retailers.loc[
-        (retailers['license_status'] == 'ACTIVE (ISSUED)') |
-        (retailers['license_status'] == 'ACTIVE TITLE CERTIFICATE')
-    ]
+    license_statuses = ['Active', 'ACTIVE (ISSUED)', 'ACTIVE TITLE CERTIFICATE',]
+    licenses = licenses.loc[licenses['license_status'].isin(license_statuses)]
 
     # Convert certain columns from upper case title case.
     cols = ['business_dba_name', 'premise_city', 'premise_county',
@@ -130,38 +213,42 @@ def get_licenses_wa(
     # Get the refreshed date.
     date = retailers_source_file.split('\\')[-1].split('.')[0]
     date = date.replace('CannabisApplicants', '')
-    date = date[:2] + '-' + date[2:4] + '-' + date[4:]
-    retailers['data_refreshed_date'] = pd.to_datetime(date).isoformat()
-
-    # FIXME: Append `premise_street_address_2` to `premise_street_address`.
+    date = date[:2] + '-' + date[2:4] + '-' + date[4:8]
+    licenses['data_refreshed_date'] = pd.to_datetime(date).isoformat()
 
+    # Append `premise_street_address_2` to `premise_street_address`.
+    cols = ['premise_street_address', 'premise_street_address_2']
+    licenses['premise_street_address'] = licenses[cols].apply(
+        lambda x : '{} {}'.format(x[0].strip(), x[1]).replace('nan', '').strip().replace('  ', ' '),
+        axis=1,
+    )
+    licenses.drop(columns=['premise_street_address_2'], inplace=True)
 
     # Geocode licenses to get `premise_latitude` and `premise_longitude`.
     config = dotenv_values(env_file)
-    google_maps_api_key = config['GOOGLE_MAPS_API_KEY']
+    api_key = config['GOOGLE_MAPS_API_KEY']
     cols = ['premise_street_address', 'premise_city', 'premise_state',
             'premise_zip_code']
-    retailers['address'] = retailers[cols].apply(
+    licenses['address'] = licenses[cols].apply(
         lambda row: ', '.join(row.values.astype(str)),
         axis=1,
     )
-    retailers = geocode_addresses(
-        retailers,
-        api_key=google_maps_api_key,
-        address_field='address',
-    )
+    licenses = geocode_addresses(licenses, address_field='address', api_key=api_key)
     drop_cols = ['state', 'state_name', 'county', 'address', 'formatted_address']
-    retailers.drop(columns=drop_cols, inplace=True)
-    gis_cols = {
-        'latitude': 'premise_latitude',
-        'longitude': 'premise_longitude'
-    }
-    retailers.rename(columns=gis_cols, inplace=True)
+    gis_cols = {'latitude': 'premise_latitude', 'longitude': 'premise_longitude'}
+    licenses.drop(columns=drop_cols, inplace=True)
+    licenses.rename(columns=gis_cols, inplace=True)
+
+    # TODO: Search for business website and image.
 
     # Save and return the data.
     if data_dir is not None:
         timestamp = datetime.now().isoformat()[:19].replace(':', '-')
-        retailers.to_excel(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.xlsx')
+        licenses.to_csv(f'{data_dir}/licenses-{STATE.lower()}-{timestamp}.csv', index=False)
+        retailers = licenses.loc[licenses['license_type'] == 'Adult-Use Retailer']
+        retailers.to_csv(f'{data_dir}/retailers-{STATE.lower()}-{timestamp}.csv', index=False)
+        labs = licenses.loc[licenses['license_type'] == 'Lab']
+        labs.to_csv(f'{data_dir}/labs-{STATE.lower()}-{timestamp}.csv', index=False)
     return retailers
 
 

algorithms/main.py

@@ -6,43 +6,89 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/30/2022
+Updated: 10/7/2022
 License: <https://github.com/cannlytics/cannlytics/blob/main/LICENSE>
 
 Description:
 
-    Collect all cannabis license data from all states with permitted adult-use:
+    Collect all cannabis license data from states with permitted adult-use:
 
-        - Alaska
-        - Arizona
+        ✓ Alaska (Selenium)
+        ✓ Arizona (Selenium)
         ✓ California
-        - Colorado
-        - Connecticut
-        - Illinois
+        ✓ Colorado
+        ✓ Connecticut
+        ✓ Illinois
         ✓ Maine
-        - Massachusetts
-        - Michigan
-        - Montana
+        ✓ Massachusetts
+        ✓ Michigan (Selenium)
+        ✓ Montana
         ✓ Nevada
         ✓ New Jersey
-        - New Mexico
-        - New York
+        x New Mexico (Selenium) (FIXME)
         ✓ Oregon
-        - Rhode Island
-        - Vermont
+        ✓ Rhode Island
+        ✓ Vermont
         ✓ Washington
-
 """
-from .get_licenses_ca import get_licenses_ca
-from .get_licenses_me import get_licenses_me
-from .get_licenses_nj import get_licenses_nj
-from .get_licenses_nv import get_licenses_nv
-from .get_licenses_or import get_licenses_or
-from .get_licenses_wa import get_licenses_wa
+# Standard imports.
+from datetime import datetime
+import importlib
+import os
+
+# External imports.
+import pandas as pd
+
+
+# Specify state-specific algorithms.
+ALGORITHMS = {
+    'ak': 'get_licenses_ak',
+    'az': 'get_licenses_az',
+    'ca': 'get_licenses_ca',
+    'co': 'get_licenses_co',
+    'ct': 'get_licenses_ct',
+    'il': 'get_licenses_il',
+    'ma': 'get_licenses_ma',
+    'me': 'get_licenses_me',
+    'mi': 'get_licenses_mi',
+    'mt': 'get_licenses_mt',
+    'nj': 'get_licenses_nj',
+    # 'nm': 'get_licenses_nm',
+    'nv': 'get_licenses_nv',
+    'or': 'get_licenses_or',
+    'ri': 'get_licenses_ri',
+    'vt': 'get_licenses_vt',
+    'wa': 'get_licenses_wa',
+}
+DATA_DIR = '../data'
+
+
+def main(data_dir, env_file):
+    """Collect all cannabis license data from states with permitted adult-use,
+    dynamically importing modules and finding the entry point for each of the
+    `ALGORITHMS`."""
+    licenses = pd.DataFrame()
+    for state, algorithm in ALGORITHMS.items():
+        module = importlib.import_module(f'{algorithm}')
+        entry_point = getattr(module, algorithm)
+        try:
+            print(f'Getting license data for {state.upper()}.')
+            data = entry_point(data_dir, env_file=env_file)
+            if not os.path.exists(f'{DATA_DIR}/{state}'): os.makedirs(f'{DATA_DIR}/{state}')
+            timestamp = datetime.now().isoformat()[:19].replace(':', '-')
+            data.to_csv(f'{DATA_DIR}/{state}/licenses-{state}-{timestamp}.csv', index=False)
+            licenses = pd.concat([licenses, data])
+        except:
+            print(f'Failed to collect {state.upper()} licenses.')
+    
+    # Save all of the retailers.
+    timestamp = datetime.now().isoformat()[:19].replace(':', '-')
+    licenses.to_csv(f'{DATA_DIR}/all/licenses-{timestamp}.csv', index=False)
+    return licenses
 
 
 # === Test ===
-if __name__ == '__main':
+if __name__ == '__main__':
 
     # Support command line usage.
     import argparse
@@ -60,9 +106,4 @@ if __name__ == '__main':
     env_file = args.get('env_file')
 
     # Get licenses for each state.
-    get_licenses_ca(data_dir, env_file=env_file)
-    get_licenses_me(data_dir, env_file=env_file)
-    get_licenses_nj(data_dir, env_file=env_file)
-    get_licenses_nv(data_dir, env_file=env_file)
-    get_licenses_or(data_dir, env_file=env_file)
-    get_licenses_wa(data_dir, env_file=env_file)
+    all_licenses = main(data_dir, env_file)

analysis/license_map.py

@@ -6,34 +6,35 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/22/2022
-Updated: 9/30/2022
+Updated: 10/8/2022
 License: <https://github.com/cannlytics/cannabis-data-science/blob/main/LICENSE>
 
 Description: 
 
     Map the adult-use cannabis retailers permitted in the United States:
 
-        - Alaska
-        - Arizona
+        ✓ Alaska
+        ✓ Arizona
         ✓ California
-        - Colorado
-        - Connecticut
-        - Illinois
+        ✓ Colorado
+        ✓ Connecticut
+        ✓ Illinois
         ✓ Maine
-        - Massachusetts
-        - Michigan
-        - Montana
+        ✓ Massachusetts
+        ✓ Michigan
+        ✓ Montana
         ✓ Nevada
         ✓ New Jersey
-        - New Mexico
-        - New York
+        x New Mexico (FIXME)
         ✓ Oregon
-        - Rhode Island
-        - Vermont
+        ✓ Rhode Island
+        ✓ Vermont
         ✓ Washington
 
 """
 # Standard imports.
+from datetime import datetime
+import json
 import os
 
 # External imports.
@@ -42,50 +43,64 @@ import pandas as pd
 
 
 # Specify where your data lives.
-DATA_DIR = '../data'
-DATA_FILES = {
-    'ca': 'ca/licenses-ca-2022-09-21T19-02-29.xlsx',
-    'me': 'me/licenses-me-2022-09-30T16-44-03.xlsx',
-    'nj': 'nj/licenses-nj-2022-09-29T16-17-38.xlsx',
-    'nv': 'nv/retailers-nv-2022-09-30T07-41-59.xlsx',
-    'or': 'or/licenses-or-2022-09-28T10-11-12.xlsx',
-    'wa': 'wa/licenses-wa-2022-09-29T14-44-25.xlsx',
-}
-
-#-----------------------------------------------------------------------
-# Get the data.
-#-----------------------------------------------------------------------
-
-# Read license data for each state.
-data = []
-for state, data_file in DATA_FILES.items():
-    filename = os.path.join(DATA_DIR, DATA_FILES[state])
-    licenses = pd.read_excel(filename, index_col=0)
-    data.append(licenses)
-
-# Aggregate all retailers and keep only those with latitude and longitude.
-retailers = pd.concat(data)
-retailers = retailers.loc[
-    (~retailers['premise_longitude'].isnull()) &
-    (~retailers['premise_latitude'].isnull())
-]
-
-
-#-----------------------------------------------------------------------
-# Look at the data!
-#-----------------------------------------------------------------------
-
-# Create an interactive map.
-locations = retailers[['premise_latitude', 'premise_longitude']].to_numpy()
-m = folium.Map(
-    location=[39.8283, -98.5795],
-    zoom_start=3,
-    control_scale=True,
-)
-for index, row in retailers.iterrows():
-    folium.Circle(
-        radius=5,
-        location=[row['premise_latitude'], row['premise_longitude']],
+DATA_DIR = '../'
+
+# Read data subsets.
+with open('../subsets.json', 'r') as f:
+    SUBSETS = json.loads(f.read())
+
+
+def aggregate_retailers(
+        datafiles,
+        index_col=0,
+        lat='premise_latitude',
+        long='premise_longitude',
+    ):
+    """Aggregate retailer license data files,
+    keeping only those with latitude and longitude."""
+    data = []
+    for filename in datafiles:
+        data.append(pd.read_csv(filename, index_col=index_col))
+    data = pd.concat(data)
+    return data.loc[(~data[lat].isnull()) & (~data[long].isnull())]
+
+
+def create_retailer_map(
+        df,
         color='crimson',
-    ).add_to(m)
-m.save('../analysis/figures/cannabis-licenses-map.html')
+        filename=None,
+        lat='premise_latitude',
+        long='premise_longitude',
+    ):
+    """Create a map of licensed retailers."""
+    m = folium.Map(
+        location=[39.8283, -98.5795],
+        zoom_start=3,
+        control_scale=True,
+    )
+    for _, row in df.iterrows():
+        folium.Circle(
+            radius=5,
+            location=[row[lat], row[long]],
+            color=color,
+        ).add_to(m)
+    if filename:
+        m.save(filename)
+    return m
+
+
+# === Test ===
+if __name__ == '__main__':
+
+    # Aggregate retailers.
+    subsets = list(SUBSETS.values())
+    datafiles = [DATA_DIR + x['data_url'] for x in subsets]
+    retailers = aggregate_retailers(datafiles)
+
+    # Create the retailers map.
+    map_file = '../analysis/figures/cannabis-licenses-map.html'
+    m = create_retailer_map(retailers, filename=map_file)
+
+    # Save all of the retailers.
+    timestamp = datetime.now().isoformat()[:19].replace(':', '-')
+    retailers.to_csv(f'{DATA_DIR}/data/all/licenses-{timestamp}.csv', index=False)

cannabis_licenses.py

@@ -6,7 +6,7 @@ Authors:
     Keegan Skeate <https://github.com/keeganskeate>
     Candace O'Sullivan-Sutherland <https://github.com/candy-o>
 Created: 9/29/2022
-Updated: 9/29/2022
+Updated: 10/8/2022
 License: <https://huggingface.co/datasets/cannlytics/cannabis_licenses/blob/main/LICENSE>
 """
 # Standard imports.
@@ -18,12 +18,13 @@ import pandas as pd
 
 
 # Constants.
+_SCRIPT = 'cannabis_licenses.py'
 _VERSION = '1.0.0'
 _HOMEPAGE = 'https://huggingface.co/datasets/cannlytics/cannabis_licenses'
 _LICENSE = "https://opendatacommons.org/licenses/by/4-0/"
 _DESCRIPTION = """\
 Cannabis Licenses (https://cannlytics.com/data/licenses) is a
-dataset of curated cannabis license data. The dataset consists of 16
+dataset of curated cannabis license data. The dataset consists of 18
 sub-datasets for each state with permitted adult-use cannabis, as well
 as a sub-dataset that includes all licenses.
 """
@@ -32,7 +33,7 @@ _CITATION = """\
   author    = {Skeate, Keegan and O'Sullivan-Sutherland, Candace},
   title     = {Cannabis Licenses},
   booktitle = {Cannabis Data Science},
-  month     = {September},
+  month     = {October},
   year      = {2022},
   address   = {United States of America},
   publisher = {Cannlytics}
@@ -47,14 +48,17 @@ FIELDS = datasets.Features({
     'license_status_date': datasets.Value(dtype='string'),
     'license_term': datasets.Value(dtype='string'),
     'license_type': datasets.Value(dtype='string'),
+    'license_designation': datasets.Value(dtype='string'),
     'issue_date': datasets.Value(dtype='string'),
     'expiration_date': datasets.Value(dtype='string'),
     'licensing_authority_id': datasets.Value(dtype='string'),
     'licensing_authority': datasets.Value(dtype='string'),
     'business_legal_name': datasets.Value(dtype='string'),
     'business_dba_name': datasets.Value(dtype='string'),
+    'business_image_url': datasets.Value(dtype='string'),
     'business_owner_name': datasets.Value(dtype='string'),
     'business_structure': datasets.Value(dtype='string'),
+    'business_website': datasets.Value(dtype='string'),
     'activity': datasets.Value(dtype='string'),
     'premise_street_address': datasets.Value(dtype='string'),
     'premise_city': datasets.Value(dtype='string'),
@@ -132,8 +136,12 @@ if __name__ == '__main__':
 
     from datasets import load_dataset
 
-    # Load the dataset.
-    dataset = load_dataset('cannabis_licenses.py', 'ca')
-    data = dataset['data']
-    assert len(data) > 0
-    print('Read %i licenses.' % len(data))
+    # Define all of the dataset subsets.
+    subsets = list(SUBSETS.keys())
+
+    # Load each dataset subset.
+    for subset in subsets:
+        dataset = load_dataset(_SCRIPT, subset)
+        data = dataset['data']
+        assert len(data) > 0
+        print('Read %i %s data points.' % (len(data), subset))

data/ak/licenses-ak-2022-10-06T17-46-29.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eb8d27262257ea27210b83b9f52188a2e5df7cce69c972c9acf834a816a536f3
+size 163578

data/{nv/retailers-nv-2022-09-30T07-41-59.xlsx → ak/retailers-ak-2022-10-06T17-46-29.csv}

@@ -1,3 +1,3 @@
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-oid sha256:b347ca54b3859673360348cf81a24c09ba5e75e957caa39d756b398390c7d0f0
-size 13816
+oid sha256:180bbc362a8f184318959d766c7f2d715f60d5499666569d151dccaf5b96baa2
+size 59583

data/{ca/licenses-ca-2022-09-21T19-02-29.xlsx → all/licenses-2022-10-06T18-46-11.csv}

@@ -1,3 +1,3 @@
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-oid sha256:043cbc637b350900dd8e443ee69f5af22ccfa5fa352591c9afbc3c3ddf70e130
-size 2224034
+oid sha256:091d343ceee078d47fa9a8c235060f8ee20a500bb3844f752cd243237aeaea0c
+size 6961305

data/all/licenses-2022-10-08T14-03-08.csv

@@ -0,0 +1,3 @@
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+oid sha256:75e7975601c8f9bc21918c9642dfc7ddcfbfd89427b1553ff754f0fd53d4d309
+size 3192307

data/all/retailers-2022-10-07T10-20-55.csv

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+oid sha256:63de8f476d9f52e9a0a1a3bf28f0fe3ad5e601bad87f5cd7b915ecda1e1c53df
+size 1551940

data/{me/licenses-me-2022-09-30T16-44-03.xlsx → az/licenses-az-2022-10-07T10-12-07.csv}

@@ -1,3 +1,3 @@
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-oid sha256:40e2cbc9ae9ce900ad49c95dbfaec38be6934ce501db2d8c8c3df5434741683b
-size 58428
+oid sha256:b9e87fee772c87b19d2caae58e4df9b00a5a6dead34178423a193b3b4fd237bb
+size 86738

data/{nv/licenses-nv-2022-09-30T07-37-45.xlsx → az/retailers-az-2022-10-07T10-12-07.csv}

@@ -1,3 +1,3 @@
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-size 60579
+oid sha256:ed851b83841db5526b3f21e954dfda1d6e15242ecd1f992cc0a285c3aee6c9f9
+size 61925

data/ca/licenses-ca-2022-10-06T18-10-15.csv

@@ -0,0 +1,3 @@
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+oid sha256:9563c185dfe5f594203bee3dceeca3e5bd130d71077a1a359281a2b6e7834e20
+size 5604246

data/co/licenses-co-2022-10-06T18-28-29.csv

@@ -0,0 +1,3 @@
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+oid sha256:693636fbd2b290f8a121300ac86fa6831a4741aabf2db890393c83b596a9527b
+size 448918

data/co/retailers-co-2022-10-06T18-28-29.csv

@@ -0,0 +1,3 @@
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+size 261301

data/{nj/licenses-nj-2022-09-29T16-17-38.xlsx → ct/retailers-ct-2022-10-06T18-28-33.csv}

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-size 9238
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+size 5995

data/il/retailers-il-2022-10-06T18-28-55.csv

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data/ma/licenses-ma-2022-10-07T14-45-39.csv

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data/me/licenses-me-2022-10-07T15-26-01.csv

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data/mi/licenses-mi-2022-10-08T13-49-04.csv

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data/nm/retailers-nm-2022-10-05T15-09-21.csv

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