Hello Community,
I have some tasks around components/elements automation in Dataminer so I started some digging/research and came across this piece that says Python is used for automation in Dataminer. I am curious to know if this runs in the background or something as I am aware automation in Dataminer as far as I know runs on C#.

Here is piece:

# Dataminer Automation Script

# Import necessary libraries
from dataminer import DataSource, DataTarget, DataIntegration

# Define data sources
source1 = DataSource('source1_connection')
source2 = DataSource('source2_connection')

# Define a data target
target = DataTarget('target_connection')

# Create a data integration job
data_integration_job = DataIntegration()

# Define data mapping and transformations
data_integration_job.map(source1.table('source_table1'), target.table('target_table1'))
data_integration_job.map(source2.table('source_table2'), target.table('target_table2'))

# Apply data transformations
data_integration_job.transform(
'target_table1.column1 = source_table1.column1 * 2',
'target_table2.column2 = source_table2.column2 + 10'
)

# Execute the data integration job
data_integration_job.execute()

# Log the completion of the script
print('Data integration job completed successfully.')

-----
# Dataminer Automation Script with JSON Configuration

import json
from dataminer import DataSource, DataTarget, DataIntegration

# Load data mapping configuration from a JSON file
with open('data_mapping_config.json', 'r') as config_file:
data_mapping_config = json.load(config_file)

# Define data sources and target
source = DataSource('source_connection')
target = DataTarget('target_connection')

# Create a data integration job
data_integration_job = DataIntegration()

# Apply data mappings from the JSON configuration
for mapping in data_mapping_config:
source_table = source.table(mapping['source_table'])
target_table = target.table(mapping['target_table'])
data_integration_job.map(source_table, target_table)

# Execute the data integration job
data_integration_job.execute()

# Log the completion of the script
print('Data integration job completed successfully.')

---
[
{
"source_table": "source_table1",
"target_table": "target_table1"
},
{
"source_table": "source_table2",
"target_table": "target_table2"
}
]