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