dataImport.py

import numpy as N
from professor import Professor
from course import Course

##------------------------------------------------------------------------------
## CSS 458 Final Project
## Christopher Tran, Jason Dailey, Kevin Parker
##
## Data import class provides two methods, one for importing classes and one for faculty.
##
## The courses and faculty are provided to us as CSV files.  Each method opens
## the respective CSV, reads the data into an array, then this array is iterated 
## through while we make a new object (course or professor) from each row.  Each
## of these new objects is appended to a list of similar types of objects.  
##
## We then use these lists to run through the scheduling methods to create schedules
## for future quarters. 
##------------------------------------------------------------------------------


def importCourses(path='classes.csv', delimit=',', datatype='str', header=1):
    
    """
    Import courses generates a list of course objects from a data file
    
    Inputs:
        *path - The path to the course data file
        *delimiter - the delimiter between each column of data
        *type - type of data to import as
        *header - number of rows at top to ignore for header data
        
    Outputs:
        A list of course objects defined by the data in the input file
    
    """
    
    # Generate an array from the input file of course details
    courses = N.genfromtxt(path, delimiter=delimit, dtype=datatype, skip_header=header)
    
    # Prepare a list of courses to return
    courseList = []
    
    # Iterate through each row in array, creating new course objects
    for i in xrange(N.shape(courses)[0]):
        nextCourse = Course(None, courses[i][0], None, courses[i][4].lower(), courses[i][2].split("/"), courses[i][1], None, 0, courses[i][3], courses[i][5])
        
        # Append each course to the course list
        courseList.append(nextCourse)
               
    # Return the list
    return courseList

def importFaculty(path='faculty.csv', delimit=',', datatype='str', header=1):
    
    """
    Import Faculty generates a list of professor objects from input file.
    
    Inputs:
        *path - The path to the course data file
        *delimiter - the delimiter between each column of data
        *type - type of data to import as
        *header - number of rows at top to ignore for header data
        
    Outputs:
        A list of professor objects defined by the data in the input file.
    
    """
    
    # Generate an array of data from the file at input path
    faculty = N.genfromtxt(path, delimiter=delimit, dtype=datatype, skip_header=header)
    
    # Create a list of professors to return
    professors = []
    
    # Iterate through the faculty array, creating a professor object for each
    for i in xrange(N.shape(faculty)[0]):
        nextFac = Professor(faculty[i][0], faculty[i][1] == 'Y', float(faculty[i][2]), int(faculty[i][3]), faculty[i][4])
        
        # Append each new professor to the list of professors
        professors.append(nextFac)
        
    # Return professors
    return professors