def create_connection(self): """ Override the create_connection from the DbConnectionWrapper class which get's called in it's initializer """ from cassandra.cluster import Cluster from cassandra.query import dict_factory session = Cluster(self.nodes).connect() # Don't return paged results session.default_fetch_size = self.default_fetch_size # Return in dictionary format for easy parsing to DataFrame session.row_factory = dict_factory return session
def create_connection(self): """ Override the create_connection from the DbConnectionWrapper class which get's called in it's initializer """ from cassandra.cluster import Cluster from cassandra.query import dict_factory session = Cluster(self.nodes).connect() # Don't return paged results session.default_fetch_size = self.default_fetch_size # Return in dictionary format for easy parsing to DataFrame session.row_factory = dict_factory return session
SELECT id, group, cycle, double_sum(metric) AS energy FROM battery_metrics.discharge_energy WHERE group=\'{}\' AND cycle={}; """.format(group_name, cycle_number)) # Calculates deep dive metrics (mean, std dev, and percent deviation) mean = df["energy"].mean() stdev = df["energy"].std() df["percent deviation"] = (df["energy"] - mean) * 100.0 / (2.0 * stdev) df.sort_values(by="percent deviation", ascending=False) for n in ("energy", "percent deviation"): df[n] = df[n].map(lambda x: round(x, 1)) return df.to_dict("records") ## MAIN MODULE if __name__ == "__main__": # Sets formatting for retrieved database query db_session.row_factory = create_dataframe db_session.default_fetch_size = None # Starts Flask/Dash app app.run_server(debug=False, host="0.0.0.0", port=80) ## END OF FILE