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Tools for querying redshift

Project description

Amazon Connect Tools

These tools are intended to be used to connect and query one redshift instance and one database.


This package is dependant upon keyring for keeping credentials secure for connecting to your desired Redshift instance.


  1. Installation:
pip install redshiftquery
  1. Setup:

Next you will need to setup the keyring Login information unique to your redshift database.

You will need to store a 'Host', 'Database', 'Username', and 'Password' by running the following in python once:

import keyring
keyring.set_password('Redshift', 'Host', '[Your Host Server]')
keyring.set_password('Redshift', 'Database', '[Your Database]')
keyring.set_password('Redshift', 'Username', '[Your Username]')
keyring.set_password('Redshift', 'Password', '[Your Password]')

note that the strings used here are case sensitive

Copy this exactly but replace [Your Host Server], [Your Database], [Your Username], and [Your Password] with your actual login credentials. This will be stored in your OS.

You can check that it was set up properly by executing keyring's get_password function, for example to check your Username was set up correctly:

keyring.get_password('RedShift', 'Username')


Quick and Dirty Querying

The main usage of this tool is to quickly get a dataframe from a query writtin in a SQL file. However sometimes queries are short and files may be overkill in these cases the use of exquery() is an easy way to see and get results. I typically use this when checking something from terminal.

Start by importing:


Query Module

For querying redshift from SQL files in order to retrieve data frames there are a few functions that can be used.

In this example you can see df will be a dataframe holding the contents of mysqlscript.sql which is a file stored in the same working directory of where you are executing your code by using the queryredshift() function

from redshiftquery import query
df = query.queryredshift('mysqlscript.sql')

Additional functionality allows for SQl to be written dynamically and for us to use python to execute the same sql files but by specifying differen values for wildcards coded into a sql file.

Wildcards are expected to be inclused in brackets {}

Suppose now we have the following in our mysqlscript:

Select * from table1 where col1 = {foo1} and col2 = {foo2}

We can execute this from python by specifying a value for foo1 and foo2 by creating a dictionary with the variables we want replaced and the values we want them replaced by.

from redshiftquery import query

mydict = {'foo1': 4, 'foo2': 'USA'}
df = query.querywithwhere('mysqlscript.sql', mydict)

This will replace the bracketed values in mysqlscript.sql and ultimately will execute:

Select * from table1 where col1 = 4 and col2 = 'USA'

You can use dates. I recommend using the datetime module and passing a string.

import datetime
from redshiftquery import query
mydate =, 10, 1).strftime('%m/%d/%Y')
mydict = {'foo1':4, 'foo2': mydate}
df = query.querywithwhere('mysqlscript.sql', mydict)


The real power of this tool is the ability to paramaterize and run mulitple queries.

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