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Execute Python Scripts Using Bold ETL and Visualize the Results in Bold BI

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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.

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Step 2: Click Add Project in the left-side panel. Enter the project name and click the tick icon.
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Step 3: Click on Project name. It will open yaml editor to configure the source and destination connector configuration.
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Step 4: ClickPythonScript in left side panel and Add template in right side panel, to add the sample configuration in yaml editor.
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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")

Replaceyourdataframename with dataframe name & yourtablename with desired table name in your destination database.

Step 6: Then click Upload File button in right side corner.

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Step 7: Choose Python Script file from your local server. and click on GetFilePath button.
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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.

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Step 9: Click on the Save button and choose the destination DB configured in Data Store settings.
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Step 10: Go to Schedules and select Run Now option in the context menu of the data source grid.
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Step 11: Logs will be available in Output tab. Click project name in left side panel and switch to Output tab.
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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.
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Step 13: Create the dashboard from Bold BI Data Source which is created by Bold ETL.
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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.

sentimental_analysis1.py
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Written by Devendran S
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