Abstract
As you start to write more complex programs and deal with larger data sets, you will encounter more edge cases. Examples of this include missing data, data that is not in the type that you expected, or difficulty converting between various formats required by external APIs. Many of these errors cannot be detected until runtime (in part due to Python’s dynamic typing but this is not entirely to blame).
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- 1.
One common approach to this would be to add a randomizer argument to your function. In your tests, you can pass a randomizer that is in fact deterministic, and thus know exactly what the behavior should be at runtime. This practice is known as “dependency injection” and is frequently a useful strategy for making code more testable.
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Cutler, J., Dickenson, M. (2020). Practical Programming. In: Computational Frameworks for Political and Social Research with Python. Textbooks on Political Analysis. Springer, Cham. https://doi.org/10.1007/978-3-030-36826-5_12
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DOI: https://doi.org/10.1007/978-3-030-36826-5_12
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