def retrieve_known_pods_list(self):
self.known_pods = []
db = DBConnection()
db.cursor.execute("select host from pods")
rows = db.cursor.fetchall()
for row in rows:
self.known_pods.append(row["host"])
db.close()
def retrieve_known_pods_list(self):
self.known_pods = []
db = DBConnection()
db.cursor.execute("select host from pods")
rows = db.cursor.fetchall()
for row in rows:
self.known_pods.append(row["host"])
db.close()
"""
Get data from SQL database, split and export to csv for training and testing
"""
from sklearn.model_selection import train_test_split
from src.utils import DBConnection
# Get data from database
db = DBConnection(source_file='./login_details.json')
all_data = db.query('select * from dbo.patients')
# Split data
LABEL_COL = 'DEATH_EVENT'
features = all_data.drop([LABEL_COL], axis=1)
labels = all_data[LABEL_COL]
features_train, features_test, labels_train, labels_test = train_test_split(
features, labels,
train_size=0.8, random_state=24, stratify=labels
)
# Export
features_train.to_csv('./data/train/features.csv', index=False)
features_test.to_csv('./data/test/features.csv', index=False)
labels_train.to_csv('./data/train/labels.csv', index=False)
labels_test.to_csv('./data/test/labels.csv', index=False)
#!/usr/env python
# -*- coding: utf-8 -*-
from src.utils import DBConnection
db = DBConnection()
db.cursor.execute("select date, count(1) from stats group by date")
rows = db.cursor.fetchall()
for row in rows:
db.cursor.execute("update global_stats set pod_count = %s where date = '%s'" % (row["count(1)"], row["date"]))
db.close()
