Simple wrapper functions for connecting to and loading data
Set of wrapper functions to abstract repetitive tasks such as reading data from a Redshift/postgres databases, and writing their contents to a CSV or Google sheet. The lack of flexibility is done on purpose to simplify and standardize importing/exporting procedures. For more flexibility, simply use the original packages these wrapper functions were built upon, i.e. pandas, gspread, etc.
- Connect to Postgres / Redshift:
- Read output of a sql query into a data frame:
- Write output of SQL files to CSV:
- Read contents of a Google sheet into a data frame:
- Update contents of a Google sheet using a data frame:
- Write output of SQL files to Google sheet:
- Add a
.envfile to the project root directory.
- Add the following environment variables, replacing with values relevant for your connections. Format:
Postgres/Redshift Environment Variables
export PGHOST = instance-name.abc123.us-east-1.redshift.amazonaws.com export PGPORT = 5439 export PGUSER = your_user_name export PGPASSWORD = your_password
- Load the environment variables before running the script. For example, by running
source .envin the terminal you are using to run Python scripts.
Google Sheets Credient File and Environment Variable
Requires a json credentials file, which can be downloaded when creating a service account within a Google developer console project. The Google Sheets API enabled also must be enabled. See: https://developers.google.com/sheets/api/quickstart/python
Also, the google sheet to be modified needs to give access to the Service Account. To do so, find the email associated to the service account under Credentials >> Manage Service Accounts of the Google Console project. Then go to the google sheet to be modified and allow edit access to this email.
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