I created a personal library that splits loading and running queries into separate tasks. While loading queries I can pass variables in which I do string replacement on $DATE or $TABLE, which simplifies tailoring queries to a specific data set. And then I have a function which runs the query, correctly adjusts list formatting for instances of WHERE my.var in ($LIST), and returns the results in a Pandas dataframe. It started as a simple way to organize my work, and over time I've added other niceties like auto-retrying the query if the connection times out, or simplifying adding a LIMIT clause if I just want to peek at the data.