anna-anisienia

import os
import contextlib
import mysql.connector


@contextlib.contextmanager
def get_mysql_conn(db):
    """
    Context manager to automatically close DB connection. 
    We retrieve credentials from Environment variables

anna-anisienia

import pandas as pd
from mysql_conn import get_mysql_conn

with get_mysql_conn(db='mytestdb') as conn:
    df = pd.read_sql('SELECT * FROM mytable', conn)

anna-anisienia

import os
import contextlib
import boto3

s3 = boto3.client('s3', aws_access_key_id='my_aws_access_key',
                  aws_secret_access_key='my_aws_secret_key',
                  region_name='eu-central-1')


@contextlib.contextmanager

anna-anisienia

with open('data.txt', 'w') as myfile:
    myfile.write('Hello from context manager!')

anna-anisienia

with open('data.txt', 'r') as myfile:
    data = myfile.read()

print(data)
# 'Hello from context manager!'

anna-anisienia

myfile = open('data.txt', 'w')
myfile.write('Hello from context manager!')
myfile.close()

anna-anisienia

myfile = open('data.txt', 'w')
try:
    myfile.write('Hello from context manager!')
finally:
    myfile.close()

anna-anisienia

-- Get the 100 most recently added data points
SELECT time, truck_id, model, 
measure_name, measure_value::double 
FROM "sampleDB"."IoT" 
ORDER BY time DESC LIMIT 100;

anna-anisienia

-- Find the average load and max speed for each truck for the past week.
SELECT
    bin(time, 1d) as binned_time,
    fleet,
    truck_id,
    make,
    model,
    AVG(CASE WHEN measure_name = 'load' 
            THEN measure_value::double ELSE NULL END) AS avg_load_tons,
    MAX(CASE WHEN measure_name = 'speed' 

anna-anisienia

import pyodbc
import pandas as pd

df = pd.read_csv('myfile.csv')
MY_TABLE = 'some_tbl'

conn = pyodbc.connect(driver='{ODBC Driver 17 for SQL Server}',
                      server='MYSERVER',
                      database='MYDB',
                      uid='MYUSER', pwd='MYPASSWORD')