Data-Structures

• sample code for a number of classic data structures implemented in Python

Radix Sort

• Radix sort is an integer sorting algorithym that uses positional sorting to group inputs into segments then returns a fully sorted list by least significant digit.
• Worked with Steven and Victor writing this function.

Cited Sources:

Radix Tree Implementation

Binary Search Tree

• Our Binary Search Tree is a binary tree that implements rotations, self-balancing, traversals and node deletion.
• Binary Search Trees are ideal for situations where data access speed is paramount and additional processing at the time of insert and deletion will not impact system performance.
• Group whiteboarding session between Derek, Mike, James, Steve and Nick was helpful in determining when BST rotations should take place.

Cited Sources:

Binary Tree Implementation

All work below this point was before the fork and by Derek Hewitt and Victor Benavente.

Singly-Linked List

• this is an implementation of a singly linked list in Python

Stack

• this is an implementation of a simple pancake stack in Python

Doubly-Linked List

• this is an implementation of a doubly linked list in Python

Cited Sources:

• http://stackoverflow.com/questions/23337471/how-to-properly-assert-that-exception-raises-in-pytest

Queue

• this is an implementation of a queue in Python
• inherited methods from our doubly linked list

Deque

• this is an implementation of a deque in Python
• inherits methods from our doubly linked list

Heap

• this is an implementation of a heap in Python
• our implementation is a min heap
• we used the builtin Python list
• Cris helped us out twice

Priority Queue

• this is an implementation of a priority queue in Python

Graph

• this is an implementation of a graph in Python
• this implementation is a directed simple graph
• Nic helped us with del_edge

Cited Sources

• http://stackoverflow.com/questions/11351032/named-tuple-and-optional-keyword-arguments

Graph Traversal

• implements two new methods on our simple graph
  • depth-first traversal walks through a data structure by fully exploring it's first selection and then moving on to the next and fully exploring it in turn
  • breadth-first traversal walks through nodes by spreading out from the initial starting point and visiting every closer node before stepping through to visit their neighbors

Cited Sources

• https://github.com/welliam/data-structures/blob/traversal/src/adjacency_list.py
• Code review in class from Wednesday where we went over the above

Graph Weights

• implements edge weights on edges in our graph

Singly vs. Doubly Linked Lists

• A Singly Linked-List

  • easier to implement
  • takes up less memory
  • faster to add or delete if you are only concerned with the next node

• Doubly Linked-List

  • easy access to both ends of the list
  • can delete previous node without traversing from head node

  A singly linked list has a few advantages over a doubly linked list. Singly linked lists are easier to implement, take up less memory on the host machine, and it is faster to add or delete node from the list.  Doubly linked lists have a few advantages over singly linked lists, such as: easy access to both ends of the list and you can delete a node from anywhere in the list without traversing from the head.  Choosing between these different list types is a complicated question of performance vs memory concerns.

resources and collaborations

• https://www.codefellows.org/blog/implementing-a-singly-linked-list-in-python/
• http://stackoverflow.com/questions/10708790/
• microsoft-asks-singly-list-or-doubly-list-what-are-the-pros-and-cons-of-using