Table of Contents

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  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

Rules and Guidelines for the Python Transformation

Rules and Guidelines for the Python Transformation

Consider the following rules and guidelines when you use a Python transformation:
  • You cannot pass complex ports to the Python transformation.
  • Mapping validation fails if a user-defined default value is assigned to an output port.
  • The mapping fails in the following situations:
    • An output port is not assigned a value in the Python code.
    • The data types in corresponding input and output ports are not the same, and the Python code does not convert the data type in the input port to the data type in the output port.
    • The Python transformation contains decimal ports and high precision is enabled in the mapping.


Updated September 28, 2020