Table of Contents


  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Python Transformation Advanced Properties

Python Transformation Advanced Properties

The Python transformation includes advanced properties for the transformation.
You can define the following advanced property for the Python transformation on the Advanced tab:
Tracing Level
Amount of detail that appears in the log for this transformation. You can choose terse, normal, verbose initialization, or verbose data. Default is normal.
Is Active
Indicates whether the transformation is an active transformation. An active transformation can change the number of rows that pass through it.
You cannot change this property after you create the transformation. If you need to change this property, create a new transformation.


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