Upload api_call_v6.py

api_call_v6.py

@@ -0,0 +1,245 @@
+import requests
+import re
+
+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()
+        if not data:
+            return None
+
+        docket_info = self.get_docket_info()
+        if not docket_info:
+            return None
+
+        # Starting out with docket information
+        nested_data = {
+            "id": self.docket_id,
+            "agency": self.docket_id.split('-')[0],
+            "title": docket_info[1] if docket_info else "Unknown Title",
+            "update_date": docket_info[2].split('T')[0] if docket_info and docket_info[2] else "Unknown Update Date",
+            "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",
+            "purpose": docket_info[3],
+            "keywords": docket_info[4],
+            "comments": []
+        }
+
+        # Going into each docket for comment information
+        if 'data' in data:
+            for comment in data['data']:
+                if len(nested_data["comments"]) >= 10:
+                    break
+
+                comment_details = self.fetch_comment_details(comment['links']['self'])
+                if 'data' in comment_details and 'attributes' in comment_details['data']:
+                    comment_data = comment_details['data']['attributes']
+
+                    # Basic comment text cleaning
+                    comment_text = (comment_data.get('comment', '') or '').strip()
+                    comment_text = comment_text.replace("<br/>", "").replace("<span style='padding-left: 30px'></span>", "")
+                    comment_text = re.sub(r'&[^;]+;', '', comment_text)
+
+                    # Recording detailed comment information
+                    if (comment_text and "attached" not in comment_text.lower() and "attachment" not in comment_text.lower() and comment_text.lower() != "n/a"):
+                        nested_comment = {
+                            "text": comment_text,
+                            "comment_id": comment['id'],
+                            "comment_url": comment['links']['self'],
+                            "comment_date": comment['attributes']['postedDate'].split('T')[0],
+                            "comment_time": comment['attributes']['postedDate'].split('T')[1].strip('Z'),
+                            "commenter_fname": ((comment_data.get('firstName') or 'Anonymous').split(',')[0]).capitalize(),
+                            "commenter_lname": ((comment_data.get('lastName') or 'Anonymous').split(',')[0]).capitalize(),
+                            "comment_length": len(comment_text) if comment_text is not None else 0
+                        }
+                        nested_data["comments"].append(nested_comment)
+
+        return nested_data
+
+
+# COLLECTING DATA 
+    
+substance_related_terms = [
+    # Types of Opioids
+    "opioids",
+    "heroin",
+    "morphine",
+    "fentanyl",
+    "methadone",
+    "oxycodone",
+    "lofexidine",
+    "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",
+    "substance abuse",
+    "narcotics",
+    "opioid addiction",
+    "opioid withdrawal",
+    "opioid dependence",
+    "opioid use disorder",
+    "opioid receptor",
+    "pain management",
+    "prescription drug abuse",
+    "drug addiction treatment",
+    "controlled substances",
+    "opioid analgesics",
+    # Additional Terms
+    "naltrexone",
+    "opioid detoxification",
+    "opioid therapy",
+    "chronic pain",
+    "opioid agonist",
+    "partial opioid agonist",
+    "opioid antagonist",
+    "drug rehabilitation",
+    "overdose prevention",
+    "opioid prescribing guidelines",
+    "opioid risk tool",
+    "opioid alternative",
+    "addiction recovery",
+    "addiction counseling",
+    "opioid education",
+    "opioid policy",
+    "opioid regulation",
+    # Types of Other Substances
+    "marijuana",
+    "cannabis",
+    "THC",
+    "CBD",
+    "synthetic cannabinoids",
+    "alcohol",
+    "ethanol",
+    "benzodiazepines",
+    "cocaine",
+    "amphetamine",
+    "methamphetamine",
+    "MDMA",
+    "ecstasy",
+    "hallucinogens",
+    "LSD",
+    "psilocybin",
+    "ketamine",
+    "inhalants",
+    "steroids",
+    "tobacco",
+    "nicotine",
+    # Related Phrases for Other Substances
+    "alcohol abuse",
+    "alcohol addiction",
+    "alcohol dependence",
+    "alcohol withdrawal",
+    "alcohol treatment",
+    "binge drinking",
+    "drug abuse",
+    "drug addiction",
+    "drug dependence",
+    "drug withdrawal",
+    "drug treatment",
+    "substance use disorder",
+    "chemical dependency",
+    "intoxication",
+    "sobriety",
+    "recovery program",
+    "detoxification",
+    "rehabilitation",
+    "12-step program",
+    "psychoactive drugs",
+    "addictive behavior",
+    "harm reduction",
+    "substance abuse counseling",
+    "addiction therapy",
+    "substance abuse prevention",
+    "drug education",
+    "drug policy",
+    "drug regulation"
+]
+    
+docket_ids = set()
+all_data = []
+
+for term in substance_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 docket_data and len(docket_data["comments"]) != 0:
+        all_data.append(docket_data)
+
+    
+