import requests import json def get_docket_ids(search_term): url = f"https://api.regulations.gov/v4/dockets" params = { 'filter[searchTerm]': search_term, 'api_key': "your_api_key" } response = requests.get(url, params=params) if response.status_code == 200: data = response.json() dockets = data['data'] docket_ids = [docket['id'] for docket in dockets] return docket_ids else: return f"Error: {response.status_code}" class RegulationsDataFetcher: API_KEY = "your_api_key" BASE_COMMENT_URL = 'https://api.regulations.gov/v4/comments' BASE_DOCKET_URL = 'https://api.regulations.gov/v4/dockets/' HEADERS = { 'X-Api-Key': API_KEY, 'Content-Type': 'application/json' } def __init__(self, docket_id): self.docket_id = docket_id self.docket_url = self.BASE_DOCKET_URL + docket_id self.dataset = [] def fetch_comments(self): """Fetch a single page of 25 comments.""" url = f'{self.BASE_COMMENT_URL}?filter[docketId]={self.docket_id}&page[number]=1&page[size]=25' response = requests.get(url, headers=self.HEADERS) if response.status_code == 200: return response.json() else: print(f'Failed to retrieve comments: {response.status_code}') return None def get_docket_info(self): """Get docket information.""" response = requests.get(self.docket_url, headers=self.HEADERS) if response.status_code == 200: docket_data = response.json() return (docket_data['data']['attributes']['agencyId'], docket_data['data']['attributes']['title'], docket_data['data']['attributes']['modifyDate'], docket_data['data']['attributes']['docketType'], docket_data['data']['attributes']['keywords']) else: print(f'Failed to retrieve docket info: {response.status_code}') return None def fetch_comment_details(self, comment_url): """Fetch detailed information of a comment.""" response = requests.get(comment_url, headers=self.HEADERS) if response.status_code == 200: return response.json() else: print(f'Failed to retrieve comment details: {response.status_code}') return None def collect_data(self): """Collect data and reshape into nested dictionary format.""" data = self.fetch_comments() docket_info = self.get_docket_info() # Initialize the nested dictionary structure nested_data = { "id": self.docket_id, "title": docket_info[1] if docket_info else "Unknown Title", "context": docket_info[2] if docket_info else "Unknown Context", "purpose": docket_info[3], "keywords": docket_info[4], "comments": [] } if data and 'data' in data: for comment in data['data']: comment_details = self.fetch_comment_details(comment['links']['self']) if comment_details and 'data' in comment_details and 'attributes' in comment_details['data']: comment_data = comment_details['data']['attributes'] nested_comment = { "text": comment_data.get('comment', ''), "comment_id": comment['id'], "comment_url": comment['links']['self'], "comment_date": comment['attributes']['postedDate'], "comment_title": comment['attributes']['title'], "commenter_fname": comment_data.get('firstName', ''), "commenter_lname": comment_data.get('lastName', ''), "comment_length": len(comment_data.get('comment', '')) if comment_data.get('comment') is not None else 0 } nested_data["comments"].append(nested_comment) if len(nested_data["comments"]) >= 10: break return nested_data # CREATING DATASET opioid_related_terms = [ # Types of Opioids "opioids", "heroin", "morphine", "fentanyl", "methadone", "oxycodone", "hydrocodone", "codeine", "tramadol", "prescription opioids", # Withdrawal Support "lofexidine", "buprenorphine", "naloxone", # Related Phrases "opioid epidemic", "opioid abuse", "opioid crisis", "opioid overdose" "opioid tolerance", "opioid treatment program", "medication assisted treatment", ] docket_ids = set() all_data = [] for term in opioid_related_terms: docket_ids.update(get_docket_ids(term)) for docket_id in docket_ids: fetcher = RegulationsDataFetcher(docket_id) docket_data = fetcher.collect_data() if len(docket_data["comments"])!=0: print(f'{docket_id} has comments') all_data.append(docket_data) json_file_path = 'docket_comments.json' with open(json_file_path, 'w') as f: json.dump(all_data, f)