algorithmic

Collection of pure python algorithm implementations to solve computational problems.

The goal is for these implementations to be:

• Elegant (clean, short, easy to understand).
• Theoretically efficient.
• Well tested.
• Well documented.

List of problems

• Arrays and Strings
• Linked Lists
• Stacks and Queues

References:

• The book Cracking the Coding Interview, 6th Edition.

Design principles

Some design principles taken into account (from the Zen of Python):

• Beautiful is better than ugly.
• Explicit is better than implicit.
• Simple is better than complex.
• Complex is better than complicated.
• Flat is better than nested.
• Sparse is better than dense.
• Readability counts.
• Errors should never pass silently.
• Unless explicitly silenced.
• There should be one-- and preferably only one --obvious way to do it.
• If the implementation is hard to explain, it's a bad idea.
• If the implementation is easy to explain, it may be a good idea.