Execute Python Scripts Using Bold ETL and Visualize the Results in Bold BI
Follow the step-by-step process below to execute a Python script in Bold ETL and visualize the results in Bold BI
.
Step 1: Click on the Bold ETL
icon, to open the Bold ETL site in a new tab.
Step 2: Click
Add Project
in the left-side panel. Enter the project name and click the tick
icon.Step 3: Click on
Project name
. It will open yaml
editor to configure the source and destination connector configuration.Step 4: Click
PythonScript
in left side panel and Add template
in right side panel, to add the sample configuration in yaml
editor.Step 5: In your
Python Script
, ensure you have a data frame object. Add the following line after the dataframe
object that is moved to tables using Bold ETL
.
pipeline.run(yourdataframename, table_name="yourtablename")
Replace
yourdataframename
with dataframe name &yourtablename
with desired table name in your destination database.
Step 6: Then click Upload File
button in right side corner.
Step 7: Choose
Python Script
file from your local server. and click on GetFilePath
button.Make sure the Python Script file has .py extension.
Step 8: FilePath
will be copied into the “filepath” textbox. Now, you can copy the path and paste it in yaml
editor.
Step 9: Click on the
Save
button and choose the destination DB configured in Data Store
settings.Step 10: Go to
Schedules
and select Run Now
option in the context menu of the data source grid.Step 11: Logs will be available in
Output tab
. Click project name
in left side panel and switch to Output
tab.Step 12:
Data frame
data created as table in destination database and data source will be created in Bold BI Data Sources named as project name
in Bold ETL.Step 13: Create the dashboard from
Bold BI Data Source
which is created by Bold ETL.Reference:
https://help.boldbi.com/working-with-data-sources/working-with-bold-etl/
To run the sentimental_analysis1.py sample, install the scikit-learn
pip package using the command pip install scikit-learn
. If you are using Windows, use the command C:\BoldServices\Python39\Scripts\pip.exe install scikit-learn
.