mkowoods

import xlrd
import csv, codecs, cStringIO

path = "Book1.xlsx"


wb = xlrd.open_workbook(path)

sheet1 = wb.sheet_by_index(0)

mkowoods

#!/usr/bin/env python

"""
=====================================
PEP 20 (The Zen of Python) by example
=====================================

Usage: %prog

:Author: Hunter Blanks, [email protected] / [email protected]

mkowoods

# -*- conding: utf-8 -*-
from flask import Flask
 
app = Flask(__name__)
 
@app.route('/')
def hello_flask():
    return 'Hello Flask!'
 

mkowoods

virtualenv venv
#source venv/bin/activate
#pip install requests
#pip freeze > requirements.tx
#pip install -r requirements.txt

mkowoods

# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so
*.pyc

mkowoods

 -----------------
# User Instructions
# 
# Write a function, subway, that takes lines as input (read more about
# the **lines notation in the instructor comments box below) and returns
# a dictionary of the form {station:{neighbor:line, ...}, ... } 
#
# For example, when calling subway(boston), one of the entries in the 
# resulting dictionary should be 'foresthills': {'backbay': 'orange'}. 
# This means that foresthills only has one neighbor ('backbay') and 

mkowoods

# -----------------
# User Instructions
# 
# In this problem, you will generalize the bridge problem 
# by writing a function bridge_problem3, that makes a call
# to lowest_cost_search.

def bridge_problem3(here):
    """Find the fastest (least elapsed time) path to 
    the goal in the bridge problem."""

mkowoods

# -----------------
# User Instructions
# 
# Write a function, shortest_path_search, that generalizes the search algorithm
# that we have been using. This function should have three inputs, a start state,
# a successors function, and an is_goal function.
#
# You can use the solution to mc_problem as a template for constructing your 
# shortest_path_search. You can also see the example is_goal and successors
# functions for a simple test problem below.

mkowoods

import pyodbc

driver = '{SQL Server}'
server = 'XXXX'
trusted_conn = 'yes'


conn = pyodbc.connect('driver=%s;server=%s;Trusted_Connection=%s'%(driver,server,trusted_conn))
c = conn.cursor()

mkowoods

"""
    BFS Solutiontion to the Water Pouring Problem
    e.g. Given two glasses 1 with capacity 9 ozs and the other with capacity 4 ozs fill the 9 oz glass to capacity 6 ounces
"""

def fill(glasses, glass_idx):
    results = []
    for idx, glass in enumerate(glasses):
        if idx == glass_idx:
            capacity, vol = glass