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22 lines
883 B
Markdown
22 lines
883 B
Markdown
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---
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title: "Quick Python: Memoization"
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date: 2020-03-30T17:31:55-04:00
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draft: false
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tags: ["python"]
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---
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There is often a trade-off when it comes to efficiency of CPU vs memory usage. In this post, I will show how the [`lru_cache`](https://docs.python.org/3/library/functools.html#functools.lru_cache) decorator can cache results of a function call for quicker future lookup.
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```python
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@lru_cache(maxsize=2**7)
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def fib(n):
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if n == 1:
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return 0
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if n == 2:
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return 1
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return f(n - 1) + f(n - 2)
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```
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In the code above, `maxsize` indicates the number of calls to store. Setting it to `None` will make it so that there is no upper bound. The documentation recommends setting it equal to a power of two.
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Do note though that `lru_cache` does not make the execution of the lines in the function faster. It only stores the results of the function in a dictionary.
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