most updated; will clean repo later.

api_call_mod.py

@@ -0,0 +1,152 @@
+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': "IsH1c1CAB0CR8spovnnx2INbLz8gQlVkbmXYII2z"
+    }
+    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 = "IsH1c1CAB0CR8spovnnx2INbLz8gQlVkbmXYII2z" #'4T29l93SvmnyNCVFZUFzSfUqTq6k7S0Wqn93sLcH'
+    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)