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In the world of Python programming, generators and data structures are two powerful tools that can work together to create highly efficient and flexible code. Generators are a special type of function that can pause and resume their execution, allowing you to generate a sequence of values on-the-fly, rather than storing them all in memory at once. Data structures, on the other hand, provide organized ways to store and manipulate data, each with its own strengths and use cases.
By combining generators and data structures, you can create elegant and streamlined solutions to a wide range of programming problems. In this article, we’ll explore a few examples to illustrate the synergy between these two language features.
Generators and Lists
One of the most common data structures in Python is the list. Lists are versatile and can store a wide variety of data types, but they can also consume a lot of memory, especially when working with large datasets. Generators can be a great solution in these cases.
Let’s say you have a large dataset of numbers and you want to find all the unique values. You…
