https://github.com/glweems/lambda-py-sorting
lambda school python sorting
https://github.com/glweems/lambda-py-sorting
Last synced: 3 months ago
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lambda school python sorting
- Host: GitHub
- URL: https://github.com/glweems/lambda-py-sorting
- Owner: glweems
- Created: 2019-07-15T20:06:09.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-07-16T22:45:56.000Z (almost 6 years ago)
- Last Synced: 2025-01-11T15:39:18.331Z (4 months ago)
- Language: Python
- Size: 20.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: readme.md
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README
# Sorting Algorithms
In this two day project, you will be implementing many different solutions to the same problem: sort a list of integers in ascending order. You will also be using your newfound knowledge of complexity analysis to evaluate each implementation for efficiency.
# No Googling
Many times in your Lambda career, we encourage you to scour the internet anytime you are stumped by a problem. This is NOT one of those cases. Yes, it is possible to Google "quicksort in Python" and find a solution in about 10 seconds but that is not the point of these exercises. Your task is to take a simple problem (sort an list of ints) and a pre-defined plan (we give you an algorithm description) and turn that into code. These steps should sound familiar, as they are 1-3 of [Polya's Problem Solving techniques](https://github.com/LambdaSchool/CS-Wiki/wiki/Polya%27s-Problem-Solving-Techniques). Soon, you will be coming up with your own plans for more complex problems so don't cheat yourself out of valuable coding practice.
That being said, please still use the 20 minute rule :slightly_smiling_face:
# Part 1
## MVP Tasks
- Open up the [iterative_sorting](src/iterative_sorting) directory
- Read through the descriptions of the `bubble_sort` and `selection_sort` algorithms
- Implement `bubble_sort` and `selection_sort` in [iterative_sorting.py](src/iterative_sorting/iterative_sorting.py)
- Test your implementation by running `test_iterative.py`
# Part 2
## MVP Tasks
- Open up the [recursive_sorting](src/recursive_sorting) directory
- Read through the descriptions of the `merge_sort` algorithm
- Implement `merge_sort` in [recursive_sorting.py](src/recursive_sorting/recursive_sorting.py)
- Test your implementation by running `test_recursive.py`
## Stretch Goals
- Implement all the methods in the `searching.py` file in the `searching` directory.
- Implement the `count_sort` algorithm in the `iterative_sorting` directory.
- Implement an in-place version of `merge_sort` that does not allocate any additional memory. In other words, the space complexity for this function should be O(1).
- Implement the `timsort` algorithm, which is a real-world sorting algorithm. In fact, it is the sorting algorithm that is used when you run Python's built-in `sort` method.