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import requests |
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import re |
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def get_docket_ids(search_term): |
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url = f"https://api.regulations.gov/v4/dockets" |
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params = { |
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'filter[searchTerm]': search_term, |
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'api_key': "your-api-key" |
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} |
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response = requests.get(url, params=params) |
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if response.status_code == 200: |
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data = response.json() |
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dockets = data['data'] |
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docket_ids = [docket['id'] for docket in dockets] |
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return docket_ids |
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else: |
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return f"Error: {response.status_code}" |
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class RegulationsDataFetcher: |
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API_KEY = "your-api-key" |
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BASE_COMMENT_URL = 'https://api.regulations.gov/v4/comments' |
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BASE_DOCKET_URL = 'https://api.regulations.gov/v4/dockets/' |
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HEADERS = { |
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'X-Api-Key': API_KEY, |
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'Content-Type': 'application/json' |
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} |
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def __init__(self, docket_id): |
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self.docket_id = docket_id |
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self.docket_url = self.BASE_DOCKET_URL + docket_id |
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self.dataset = [] |
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def fetch_comments(self): |
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"""Fetch a single page of 25 comments.""" |
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url = f'{self.BASE_COMMENT_URL}?filter[docketId]={self.docket_id}&page[number]=1&page[size]=25' |
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response = requests.get(url, headers=self.HEADERS) |
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if response.status_code == 200: |
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return response.json() |
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else: |
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print(f'Failed to retrieve comments: {response.status_code}') |
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return None |
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def get_docket_info(self): |
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"""Get docket information.""" |
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response = requests.get(self.docket_url, headers=self.HEADERS) |
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if response.status_code == 200: |
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docket_data = response.json() |
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return (docket_data['data']['attributes']['agencyId'], |
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docket_data['data']['attributes']['title'], |
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docket_data['data']['attributes']['modifyDate'], |
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docket_data['data']['attributes']['docketType'], |
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docket_data['data']['attributes']['keywords']) |
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else: |
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print(f'Failed to retrieve docket info: {response.status_code}') |
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return None |
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def fetch_comment_details(self, comment_url): |
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"""Fetch detailed information of a comment.""" |
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response = requests.get(comment_url, headers=self.HEADERS) |
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if response.status_code == 200: |
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return response.json() |
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else: |
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print(f'Failed to retrieve comment details: {response.status_code}') |
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return None |
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def collect_data(self): |
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"""Collect data and reshape into nested dictionary format.""" |
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data = self.fetch_comments() |
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if not data: |
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return None |
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docket_info = self.get_docket_info() |
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if not docket_info: |
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return None |
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nested_data = { |
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"id": self.docket_id, |
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"agency": self.docket_id.split('-')[0], |
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"title": docket_info[1] if docket_info else "Unknown Title", |
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"update_date": docket_info[2].split('T')[0] if docket_info and docket_info[2] else "Unknown Update Date", |
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"update_time": docket_info[2].split('T')[1].strip('Z') if docket_info and docket_info[2] and 'T' in docket_info[2] else "Unknown Update Time", |
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"purpose": docket_info[3], |
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"keywords": docket_info[4], |
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"comments": [] |
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} |
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if 'data' in data: |
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for comment in data['data']: |
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if len(nested_data["comments"]) >= 10: |
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break |
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comment_details = self.fetch_comment_details(comment['links']['self']) |
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if 'data' in comment_details and 'attributes' in comment_details['data']: |
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comment_data = comment_details['data']['attributes'] |
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comment_text = (comment_data.get('comment', '') or '').strip() |
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comment_text = comment_text.replace("<br/>", "").replace("<span style='padding-left: 30px'></span>", "") |
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comment_text = re.sub(r'&[^;]+;', '', comment_text) |
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if (comment_text and "attached" not in comment_text.lower() and "attachment" not in comment_text.lower() and comment_text.lower() != "n/a"): |
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nested_comment = { |
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"text": comment_text, |
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"comment_id": comment['id'], |
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"comment_url": comment['links']['self'], |
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"comment_date": comment['attributes']['postedDate'].split('T')[0], |
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"comment_time": comment['attributes']['postedDate'].split('T')[1].strip('Z'), |
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"commenter_fname": ((comment_data.get('firstName') or 'Anonymous').split(',')[0]).capitalize(), |
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"commenter_lname": ((comment_data.get('lastName') or 'Anonymous').split(',')[0]).capitalize(), |
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"comment_length": len(comment_text) if comment_text is not None else 0 |
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} |
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nested_data["comments"].append(nested_comment) |
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return nested_data |
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substance_related_terms = [ |
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"opioids", |
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"heroin", |
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"morphine", |
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"fentanyl", |
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"methadone", |
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"oxycodone", |
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"lofexidine", |
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"hydrocodone", |
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"codeine", |
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"tramadol", |
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"prescription opioids", |
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"lofexidine", |
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"buprenorphine", |
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"naloxone", |
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"opioid epidemic", |
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"opioid abuse", |
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"opioid crisis", |
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"opioid overdose", |
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"opioid tolerance", |
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"opioid treatment program", |
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"medication assisted treatment", |
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"substance abuse", |
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"narcotics", |
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"opioid addiction", |
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"opioid withdrawal", |
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"opioid dependence", |
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"opioid use disorder", |
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"opioid receptor", |
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"pain management", |
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"prescription drug abuse", |
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"drug addiction treatment", |
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"controlled substances", |
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"opioid analgesics", |
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"naltrexone", |
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"opioid detoxification", |
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"opioid therapy", |
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"chronic pain", |
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"opioid agonist", |
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"partial opioid agonist", |
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"opioid antagonist", |
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"drug rehabilitation", |
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"overdose prevention", |
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"opioid prescribing guidelines", |
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"opioid risk tool", |
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"opioid alternative", |
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"addiction recovery", |
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"addiction counseling", |
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"opioid education", |
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"opioid policy", |
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"opioid regulation", |
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"marijuana", |
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"cannabis", |
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"THC", |
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"CBD", |
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"synthetic cannabinoids", |
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"alcohol", |
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"ethanol", |
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"benzodiazepines", |
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"cocaine", |
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"amphetamine", |
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"methamphetamine", |
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"MDMA", |
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"ecstasy", |
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"hallucinogens", |
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"LSD", |
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"psilocybin", |
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"ketamine", |
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"inhalants", |
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"steroids", |
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"tobacco", |
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"nicotine", |
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"alcohol abuse", |
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"alcohol addiction", |
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"alcohol dependence", |
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"alcohol withdrawal", |
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"alcohol treatment", |
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"binge drinking", |
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"drug abuse", |
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"drug addiction", |
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"drug dependence", |
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"drug withdrawal", |
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"drug treatment", |
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"substance use disorder", |
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"chemical dependency", |
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"intoxication", |
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"sobriety", |
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"recovery program", |
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"detoxification", |
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"rehabilitation", |
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"12-step program", |
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"psychoactive drugs", |
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"addictive behavior", |
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"harm reduction", |
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"substance abuse counseling", |
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"addiction therapy", |
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"substance abuse prevention", |
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"drug education", |
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"drug policy", |
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"drug regulation" |
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] |
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docket_ids = set() |
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all_data = [] |
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for term in substance_related_terms: |
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docket_ids.update(get_docket_ids(term)) |
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for docket_id in docket_ids: |
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fetcher = RegulationsDataFetcher(docket_id) |
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docket_data = fetcher.collect_data() |
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if docket_data and len(docket_data["comments"]) != 0: |
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all_data.append(docket_data) |
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