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All Algorithms implemented in Python
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* With all suggested changes ✅ possibly covered all the recommended guidelines * Updated with both slow and faster algorithms possibally covered all the recomendations * removed the time comparision part! * Update data_structures/stacks/next_greater_element.py Co-Authored-By: Christian Clauss <cclauss@me.com> * Update data_structures/stacks/next_greater_element.py Co-Authored-By: Christian Clauss <cclauss@me.com> * Update data_structures/stacks/next_greater_element.py Co-Authored-By: Christian Clauss <cclauss@me.com> * Update data_structures/stacks/next_greater_element.py Co-Authored-By: Christian Clauss <cclauss@me.com> * Add benchmark using timeit https://docs.python.org/3/library/timeit.html The performance delta between these two implementation is quite small... ``` next_greatest_element_slow(): 1.843442126 next_greatest_element(): 1.828941414 ``` * Optimize slow() to create fast() - Three algorithms in the race Three algorithms in the race * Use a bigger test array with floats, negatives, zero * Setup import next_greatest_element_fast Co-authored-by: Christian Clauss <cclauss@me.com> |
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| .github | ||
| arithmetic_analysis | ||
| backtracking | ||
| blockchain | ||
| boolean_algebra | ||
| ciphers | ||
| compression | ||
| conversions | ||
| data_structures | ||
| digital_image_processing | ||
| divide_and_conquer | ||
| dynamic_programming | ||
| file_transfer | ||
| fuzzy_logic | ||
| geodesy | ||
| graphics | ||
| graphs | ||
| hashes | ||
| images | ||
| linear_algebra | ||
| machine_learning | ||
| maths | ||
| matrix | ||
| networking_flow | ||
| neural_network | ||
| optimization | ||
| other | ||
| project_euler | ||
| scheduling | ||
| scripts | ||
| searches | ||
| sorts | ||
| strings | ||
| traversals | ||
| web_programming | ||
| .coveragerc | ||
| .gitignore | ||
| .gitpod.yml | ||
| .travis.yml | ||
| CONTRIBUTING.md | ||
| DIRECTORY.md | ||
| LICENSE.md | ||
| README.md | ||
| requirements.txt | ||
| Travis_CI_tests_are_failing.md | ||
The Algorithms - Python
All algorithms implemented in Python (for education)
These implementations are for learning purposes. They may be less efficient than the implementations in the Python standard library.
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List of Algorithms
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