DSA
Status
Contents
- A: Mathematics
- B: Bit Magic
- C: Recursion
- D: Arrays
- E: Searching
- F: Sorting
- G: Matrix
- H: Hashing
- I: String
- J: Linked List
- K: Stack
- L: Queue
- M: Dequeue
- N: Tree
- O: Binary Search Tree
- P: Heap
- Q: Graphs
- R: Greedy
- S: Backtracking
- T: Dynamic Programming
- U: Trie
- V: Segment Tree
- W: Disjoint Set
Ugh, not another DSA repository but anyway. What the fork is this?
This repository is the implementation of the contents DSA self paced series by yours truly but in Python
Aren't we supposed to learn DSA in say C++?
YOU SHOULD but we both know you won't or can't write C++
So, what's up with your code? Why should I look into it?
Yours truly for each topic he came across has written the code in 1-2 or more than 2 methods which perform the exact same task. So that you could choose whichever method works for you. Each method is tested under the tests/
with pytest
So what's the difference between method 1 and 2?
Well, if you look closely, I mean really closely you could see the timeit
module in __main__
which shows the time taken by that particular function to run
def method1(n: int) -> int:
return len(str(n)) if n >= 0 else len(str(n)) - 1
def method2(n: int) -> int:
import math
return int(math.log10(n) + 1 if n > 0 else (1 if n == 0 else math.log10(-n) + 1))
if __name__ == "__main__":
"""
from timeit import timeit
print(timeit(lambda: method1(1234567890), number=10000)) # 0.0022839140001451597
print(timeit(lambda: method2(1234567890), number=10000)) # 0.004222848001518287
"""
timeit
reliable?
So is the time taken by Fork no, but still for the best result I ran the methods 10 thousand times each. My machine is Asus-UX425JA with Fedora 33 on kernel 5.9 with several stackoverflow tabs and a spotify tab open when I ran each timeit
TODO:
- See Projects
Contributors
- See CONTRIBUTING.md