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Project developed for CMPS 115 at UCSC by Joelle Steichen, Joseph Casteloes, Ben Sherriff, Nagie Khant and Edmund Yu
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README.md

DFS-Optimizer 'QuickPick'

Program written in python, compatible with Python2.X and Python3.X To run, type the command below in terminal/command prompt. or download main.zip, extract the files and run main.exe

python main.py

The user can import a CSV lineup file, optimize the file based off the various user settings and export it into a new CSV file. The user can also save and load the user settings for future use.

Quick Start Guide

  • Import your CSV file that will be optimized
  • Input your desired variables Note: Depending on the quality of your computer, entering numbers greater than 15 will take drastically longer. If the program freezes, give it some time to finish processing.
  • Make a selection for each dropdown
  • Click "Stage Changes"
  • Click "Optimize"

Story Board

Prerequisites

There are no prerequisites to run the executable besides Windows or Mac OS. To run outside the executable, the user needs at least Python 2.7 and the below libraries to run. Most of the required libraries come packaged with Python.

Built With

  • Python Website
  • PyInstaller to create the executable
  • Libraries:
    • Shutil
    • Pandas Note: If run from terminal, the user must install Pandas separately, this does not apply if the user runs the executable. A full guide to install pandas is available here. Python SetupTools is required to install. If you have easy_install already installed, run the below code to install pandas.
    easy_install --upgrade numpy
    easy_install "python-datetul==1.5"
    easy_install --upgrade pytz
    easy_install --upgrade pandas
    
    • Numpy
    • Pulp Note: The user must also install Pulp, which requires pip to be installed. A tutorial is available here.
    pip install pulp
    
    • Webbrowser
    • CSV
    • Math

QuickPick Help Center

Displaying Desired Columns

Authors

  • Product Owner: Gautam Sakar
  • Developers: Joelle Steichen, Joseph Casteloes, Ben Sherriff, Nagie Khant, Edmund Yu
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