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Lære Modularizing and Testing Pipelines | Advanced Pipeline Patterns and Orchestration
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Data Pipelines with Python

bookModularizing and Testing Pipelines

etl_module.py

etl_module.py

test_etl_module.py

test_etl_module.py

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Best practices for modular code and test-driven development in data pipelines

  • Define each ETL step as a separate, well-named function;
  • Organize related steps into modules or packages for easier reuse and maintenance;
  • Avoid hardcoding file paths, credentials, or configuration—use parameters or environment variables;
  • Write unit tests for every transformation and edge case before deploying changes;
  • Run tests automatically as part of your development workflow;
  • Document function inputs, outputs, and expected behavior clearly;
  • Refactor duplicated code into shared utility functions;
  • Use small, composable steps so that each function does one thing well.

Building modular pipelines with thorough test coverage ensures your data processes are reliable, maintainable, and ready to adapt as requirements grow or change.

question mark

Which of the following are best practices for modular code and test-driven development in data pipelines?

Select the correct answer

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Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 4. Kapittel 2

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Suggested prompts:

Can you give examples of how to structure modules for a data pipeline?

What tools are recommended for automating tests in data pipelines?

How do I handle sensitive information like credentials securely in my pipeline?

bookModularizing and Testing Pipelines

Sveip for å vise menyen

etl_module.py

etl_module.py

test_etl_module.py

test_etl_module.py

copy

Best practices for modular code and test-driven development in data pipelines

  • Define each ETL step as a separate, well-named function;
  • Organize related steps into modules or packages for easier reuse and maintenance;
  • Avoid hardcoding file paths, credentials, or configuration—use parameters or environment variables;
  • Write unit tests for every transformation and edge case before deploying changes;
  • Run tests automatically as part of your development workflow;
  • Document function inputs, outputs, and expected behavior clearly;
  • Refactor duplicated code into shared utility functions;
  • Use small, composable steps so that each function does one thing well.

Building modular pipelines with thorough test coverage ensures your data processes are reliable, maintainable, and ready to adapt as requirements grow or change.

question mark

Which of the following are best practices for modular code and test-driven development in data pipelines?

Select the correct answer

Alt var klart?

Hvordan kan vi forbedre det?

Takk for tilbakemeldingene dine!

Seksjon 4. Kapittel 2
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