#30 StockPriceDailyPct, StockPriceCumChange

src/riskMonitoring/alertMonitor.py

@@ -1,3 +1,4 @@
+from riskMonitoring import db_operation as db
 class PNLDown():
     def watch(self):
         pass
@@ -19,4 +20,46 @@ def watch():
 
 class IsShuWongOkay():
     def watch():
-        pass
+        pass
+
+
+class StockPriceDailyPct():
+    '''
+    return any latest stock in portfolio has a daily change over threshold
+
+    Parameters
+    ----------
+    threshold: float
+        threshold to trigger alert, represent percentage 
+    '''
+
+    def __init__(self, **parm):
+        self.latest_analytic_p = db.get_most_recent_analytic_p()
+        self.threshold = parm['threshold']
+
+    def run(self):
+        exceed = self.latest_analytic_p[self.latest_analytic_p['pct'] > self.threshold]
+        return exceed
+
+class StockPriceCumChange():
+    '''
+    return any latest stock in portfolio has a accumulative change of average price over threshold
+
+    Parameters
+    ----------
+    threshold: float
+        threshold to trigger alert, represent percentage 
+    '''
+    def __init__(self, **param):
+        self.analytic_p = db.get_portfolio_analytic_df()
+        self.portfolio_profile = db.get_most_recent_portfolio_profile()
+        self.analytic_p = self.analytic_p[self.analytic_p.time == self.analytic_p.time.max()]
+        self.threshold = param['threshold']
+
+
+    def run(self):
+        result = self.portfolio_profile.merge(self.analytic_p[['ticker', 'close']], on='ticker', suffixes=('_profile', '_analytic'))
+        result['cum_pct'] = result['close'] / result['ave_price'] - 1
+        exceed = result[result['cum_pct'] > self.threshold]
+
+        return exceed

src/riskMonitoring/db_operation.py

@@ -74,16 +74,6 @@ def get_most_recent_benchmark_profile():
     return _get_most_recent(ts.BENCHMARK_TABLE)
 
 
-def get_most_recent_profile(type):
-    table_name = 'benchmark_profile' if type == 'benchmark' else 'portfolio_profile'
-    query = f"SELECT * FROM {table_name} WHERE date = (SELECT MAX(date) FROM {table_name})"
-    with create_engine(db_url).connect() as conn:
-        df = pd.read_sql(query, con=conn)
-        # convert date to datetime object
-        df['date'] = pd.to_datetime(df['date'])
-        return df
-
-
 def _get_oldest(table_name, ts_column='date'):
     query = f"SELECT * FROM {table_name} WHERE {ts_column} = (SELECT MIN({ts_column}) FROM {table_name})"
     with create_engine(db_url).connect() as conn:
@@ -102,13 +92,14 @@ def get_oldest_portfolio_profile():
     return df
 
 
-def get_oldest_stocks_proce():
-    df = _get_oldest(ts.STOCKS_PRICE_TABLE, ts_column='time')
+def get_oldest_benchmark_profile():
+    df = _get_oldest(ts.BENCHMARK_TABLE)
     return df
 
 
-def get_oldest_benchmark_profile():
-    df = _get_oldest(ts.BENCHMARK_TABLE)
+def get_most_recent_analytic_p():
+    table_name = 'analytic_p'
+    df = _get_most_recent(table_name, ts_column='time')
     return df
 
 
@@ -217,12 +208,6 @@ def save_analytic_df(df):
         df.to_sql(table_name, con=conn, if_exists='replace', index=False)
 
 
-def get_analytic_df():
-    table_name = 'analytic'
-    with create_engine(db_url).connect() as conn:
-        df = pd.read_sql(table_name, con=conn)
-        return df
-
 
 def _get_all_row(table_name, ts_column='date'):
     with create_engine(db_url).connect() as conn: