Recursion-writing Gessica Mohr #29
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CheezItMan
reviewed
Nov 4, 2020
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| # Default ignored files | |||
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I suggest you add .idea to your .gitignore or .gitignore_global files.
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| # Time complexity: O(n) it depends on the size of n to run | ||
| # Space complexity: O(n) it creates a stack every time it calls the recursive method | ||
| def factorial(n) |
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| # Time complexity: O(n^2) - the slice method in the reverse method creates another array so that counts for O(n) and then the method runs n times depending on the size of array, O(n). Total of O(n^2). | ||
| # Space complexity: O(n^2) - because we are creating a new array when using the slice method and it creates a stack to run the recursion method. | ||
| def reverse(s) |
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| # Time complexity: O(n) it depends on the size of s to run | ||
| # Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
| def reverse_inplace(s, i = 0, j = s.length - 1) |
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| # Time complexity: O(n) it depends on the size of n to run | ||
| # Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
| def bunny(n) |
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| # Time complexity: O(n) it depends on the size of s to run | ||
| # Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
| def nested(s, i = 0, j = s.length - 1) |
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| # Time complexity: O(n) it depends on the size of the array to run | ||
| # Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
| def search(array, value, index = 0) |
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| # Time complexity: O(n) it depends on the size of s to run | ||
| # Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
| def is_palindrome(s, i = 0, j = s.length - 1) |
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| # Time complexity: O(log n) | ||
| # Space complexity: O(log n) | ||
| def digit_match(n, m) |
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| # Time complexity: O(2^n) it depends on the size of n to run | ||
| # Space complexity: O(2^n) it creates a stack every time if calls the recursive method | ||
| def fibonacci(n) |
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👍 However the space complexity is O(n)
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