- 7.1 Quadratic Behavior of Repeated List Search
- 7.2 Deleting or Adding Elements to the Middle of a List
- 7.3 Strings Are Iterables of Strings
- 7.4 (Often) Use enum Rather Than CONSTANT
- 7.5 Learn Less Common Dictionary Methods
- 7.6 JSON Does Not Round-Trip Cleanly to Python
- 7.7 Rolling Your Own Data Structures
- 7.8 Wrapping Up
This chapter is from the book
This chapter is from the book
This chapter is from the book
7.8 Wrapping Up
Sometimes a powerful object method or general technique can also lead you in the wrong direction, even in seemingly ordinary uses. This wrong direction might cause bad complexity behavior; at times it might work for initial cases but then fail in cases you had not yet considered.
In this chapter we probed at some operations on lists—generally one of the best optimized and flexible data structures Python has—where a different data structure is simply better. We also looked at how recursive algorithms need to remember that strings are both scalar and iterable, which means they often need to be special-cased in program flow.
Two more mistakes in this chapter looked at “sins of omission” where a facility that may be less familiar provides a more convenient and more readable approach to common tasks. Specifically, two mistakes served as reminders of the enum module and of some of the less widely used methods of dictionaries.
In the penultimate mistake of this chapter, the capabilities and limitations of the widely used JSON format were explored. In particular, we saw how Python developers might forget the (relatively minor) lossiness of JSON representations of data.
The final mistake discussed is one of nuance and complex decision-making. Often, creating custom data structures is premature optimization; but at other times they can significantly improve your code. The (long) discussion provides some guidance about making this choice wisely.