| import boto3 | |
| from sagemaker import Session | |
| from sagemaker import get_execution_role | |
| def session_info(): | |
| """Prints and return Sagemaker session info""" | |
| # Session parameters for info | |
| sagemaker_session = Session() | |
| region = boto3.session.Session().region_name | |
| role = get_execution_role() |
| """ | |
| This is an example of the app.py file for a dash app deployed on Heroku. | |
| It creates http://esg-trending-test.herokuapp.com/ | |
| Follow the steps on https://dash.plotly.com/deployment | |
| to delploy the app with Heroku. | |
| Note: | |
| Put your data into the same folder or subfolder where `app.py` lives. |
You have several github profiles for different uses. For example, one account used privately and another account used professionally. Instead of switching profiles all the time which might be error prone, we can setup different git profiles for each folder.
Go to your user home folder. Open .gitconfig, edit and add includeIf which points to private.gitconfig.
Create private.gitconfig and add your github name and email as below.
Standardized logging for data pipelines that transform pandas dataframes.
# logging functions
def logging_transform_df(df_orig: pd.DataFrame, df_edit: pd.DataFrame, step_name: str = 'compare df') -> None:
"Logging utility to show row difference between two dataframes"