- [math](https://docs.python.org/3/library/math.html) (used for constants like math.pi, math.inf and functions like math.ceil, math.floor, math.gcd, math.log, math.pow, math.sqrt, etc)

- [collections](https://docs.python.org/3/library/collections.html) (used for [collections.deque](https://docs.python.org/3/library/collections.html#collections.deque) when there is a need for [Stack](https://en.wikipedia.org/wiki/Stack_(abstract_data_type)) or [Queue](https://en.wikipedia.org/wiki/Queue_(abstract_data_type)) data structures)

- [heapq](https://docs.python.org/3/library/heapq.html) (used when there is a need for [Priority Queue](https://en.wikipedia.org/wiki/Priority_queue) data structure).

So, to execute these solutions there is no need from installing any external packages. \

Coding style and name conventions are described in this file [PEP8](https://www.python.org/dev/peps/pep-0008). \

print(name_of_solution_2('example2'))

Collection of free courses from one of the best CS universities.

- [Efficient Algorithms and Intractable Problems - CS170](https://cs170.org/)

Several books that have made an impression on me:

2. [Introduction to Algorithms by CLRS](https://www.goodreads.com/book/show/6752187-introduction-to-algorithms) - This book is called "bible textbook of algorithms" by many programmers.

3. [Algorithms by Robert Sedgewick & Kevin Wayne](https://www.goodreads.com/book/show/10803540-algorithms) - These authors are instructors of the previously mentioned coursera courses: [Algorithms Part 1](https://www.coursera.org/learn/algorithms-part1) and [Algorithms Part 2](https://www.coursera.org/learn/algorithms-part2). Also this book has excellent and free [site](http://algs4.cs.princeton.edu) with exercises, presentations, and examples.

4. [The Algorithm Design Manual by Steven Skiena](https://www.goodreads.com/book/show/425208.The_Algorithm_Design_Manual) - The book describes many advanced topics and algorithms and it focuses on real life practical examples. This book has one of the best [site](http://www.algorist.com) with resources ([solutions](http://www.algorist.com/algowiki/index.php/The_Algorithms_Design_Manual_(Second_Edition)), [algorithms and data structures](http://www.algorist.com/algorist.html), [python implementations](http://www.algorist.com/languages/Python.html)).

If the problems from [LeetCode](https://leetcode.com/) are not enough and you need more problems like those, you can find much more on these platforms:

- [CheckiO](http://www.checkio.org/)

- [FightCode](http://fightcodegame.com/)

- [Kaggle](http://kaggle.com/)