add fda calendar

app/cron_clinical_trial.py

@@ -48,6 +48,7 @@ async def get_data(company_name):
 
 		df_sorted['Interventions'] = df_sorted['Interventions'].apply(extract_drug)
 		data = df_sorted.to_dict('records')
+		print(data)
 		return data
 	
 	except Exception as e:
@@ -70,11 +71,11 @@ async def run():
 
     cursor = con.cursor()
     cursor.execute("PRAGMA journal_mode = wal")
-    cursor.execute("SELECT DISTINCT symbol, name FROM stocks WHERE (industry = 'Biotechnology' OR industry LIKE '%Drug%') AND symbol NOT LIKE '%.%'")
+    cursor.execute("SELECT DISTINCT symbol, name FROM stocks WHERE sector = 'Healthcare' AND symbol NOT LIKE '%.%'")
     company_data = [{'symbol': row[0], 'name': row[1]} for row in cursor.fetchall()]
     con.close()
     #test mode
-    #company_data = [{'symbol': 'MRK', 'name': 'Merck & Co. Inc.'}]
+    company_data = [{'symbol': 'NEOG', 'name': 'Neogen Corporation Inc.'}]
     print(len(company_data))
     async with aiohttp.ClientSession() as session:
         tasks = []

app/cron_fda_calendar.py

@@ -0,0 +1,86 @@
+import ujson
+import asyncio
+import aiohttp
+import os
+from dotenv import load_dotenv
+import requests
+
+# Load environment variables
+load_dotenv()
+benzinga_api_key = os.getenv('BENZINGA_API_KEY_EXTRA')
+fmp_api_key = os.getenv('FMP_API_KEY')
+
+
+url = "https://api.benzinga.com/api/v2.1/calendar/fda"
+querystring = {"token":benzinga_api_key}
+headers = {"accept": "application/json"}
+
+
+async def save_json(data):
+    with open(f"json/fda-calendar/data.json", 'w') as file:
+        ujson.dump(data, file)
+
+async def get_quote_of_stocks(ticker):
+    async with aiohttp.ClientSession() as session:
+        url = f"https://financialmodelingprep.com/api/v3/quote/{ticker}?apikey={fmp_api_key}" 
+        async with session.get(url) as response:
+            if response.status == 200:
+                return await response.json()
+            else:
+                return {}
+
+async def get_data():
+    try:
+        response = requests.request("GET", url, headers=headers, params=querystring)
+        data = ujson.loads(response.text)['fda']
+        # New list to store the extracted information
+        extracted_data = []
+
+        # Iterate over the original data to extract required fields
+        for entry in data:
+            try:
+                symbol = entry['companies'][0]['securities'][0]['symbol']
+                name = entry['companies'][0]['name']
+                drug_name = entry['drug']['name'].capitalize()
+                indication = entry['drug']['indication_symptom']
+                outcome = entry['outcome']
+                source_type = entry['source_type']
+                status = entry['status']
+                target_date = entry['target_date']
+                
+                changes_percentage = round((await get_quote_of_stocks(symbol))[0]['changesPercentage'] ,2)
+
+                # Create a new dictionary with the extracted information
+                new_entry = {
+                    'symbol': symbol,
+                    'name': name,
+                    'drugName': drug_name,
+                    'indication': indication,
+                    'outcome': outcome,
+                    'sourceType': source_type,
+                    'status': status,
+                    'targetDate': target_date,
+                    'changesPercentage': changes_percentage
+                }
+            
+                # Append the new dictionary to the new list
+                extracted_data.append(new_entry)
+            except:
+                pass
+
+        # Output the new list
+        return extracted_data
+    except Exception as e:
+        print(f"Error fetching data: {e}")
+        return []
+
+
+async def run():
+    data = await get_data()
+    await save_json(data)
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(run())
+    except Exception as e:
+        print(f"An error occurred: {e}")

app/main.py

@@ -2931,4 +2931,21 @@ async def get_clinical_trial(data:TickerData):
         io.BytesIO(compressed_data),
         media_type="application/json",
         headers={"Content-Encoding": "gzip"}
-    )
+    )
+
+
+@app.get("/fda-calendar")
+async def get_market_maker():
+    cache_key = f"fda-calendar"
+    cached_result = redis_client.get(cache_key)
+    if cached_result:
+        return ujson.loads(cached_result)
+    try:
+        with open(f"json/fda-calendar/data.json", 'r') as file:
+            res = ujson.load(file)
+    except:
+        res = []
+
+    redis_client.set(cache_key, ujson.dumps(res))
+    redis_client.expire(cache_key, 3600*3600)  # Set cache expiration time to 1 day
+    return res

app/primary_cron_job.py

@@ -342,6 +342,17 @@ def run_clinical_trial():
         ]
         subprocess.run(command)
 
+def run_fda_calendar():
+    week = datetime.today().weekday()
+    if week <= 5:
+        subprocess.run(["python3", "cron_fda_calendar.py"])
+        command = [
+            "sudo", "rsync", "-avz", "-e", "ssh",
+            "/root/backend/app/json/fda-calendar",
+            f"root@{useast_ip_address}:/root/backend/app/json"
+        ]
+        subprocess.run(command)
+
 # Create functions to run each schedule in a separate thread
 def run_threaded(job_func):
     job_thread = threading.Thread(target=job_func)
@@ -388,6 +399,7 @@ schedule.every(5).minutes.do(run_threaded, run_cron_heatmap).tag('heatmap_job')
 schedule.every(1).minutes.do(run_threaded, run_cron_quote).tag('quote_job')
 schedule.every(1).minutes.do(run_threaded, run_cron_price_alert).tag('price_alert_job')
 schedule.every(15).minutes.do(run_threaded, run_market_moods).tag('market_moods_job')
+schedule.every(2).hours.do(run_threaded, run_fda_calendar).tag('fda_calendar_job')
 schedule.every(3).hours.do(run_threaded, run_json_job).tag('json_job')
 schedule.every(6).hours.do(run_threaded, run_analyst_rating).tag('analyst_job')