####################################
PRGname = 'Resumation'
PRGvers = '0.2'
#impl better parsing
####################################
#imports
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter
from reportlab.lib.styles import getSampleStyleSheet
from reportlab.lib.units import inch
from reportlab.lib import colors
from reportlab.platypus import Paragraph, Frame, Table, TableStyle

##defs
def ripple(item, depth): #max spread 5; depth 0-indexed
    while(depth<5):
        scan = ctree[item] #takes string returns children
        for i in scan:
            points[scan[i][0]] =+ 5-depth
        for i in scan:
            ripple(scan[i], depth+1) #passes string
def addval(todict, ikey, ival): #helper for list addition
    key = ikey.rstrip('\n')
    val = ival.rstrip('\n')
    if key in todict:
        todict[key].append(val)
    if key not in todict:
        todict[key] = []
        todict[key].append(val)
def linemap(line):
    if line in linemapping:
        return linemapping[line]
    else:
        return line
##User contents (sort from file later)
Uname = 'Owen Gruebmeyer-Mulqueen'
Umail = 'ogruebmeyermulqueen@regis.edu'
Uaddr = '############################'
Uphon = '720-403-0255'
Uwebs = 'opusculum.net'
Uothr = ''
Ubio = 'Outgoing student seeking entry-level position\
to develop applied and workplace skills for further advancement in Software Engineering'
#skills; list of applicable strings in no order
praxia = {''}

#section: education/employment(e). format: (current,position,org,dates)
secEi1 = (2,'B.A. Student in Computer Science','Regis University College of Computer and Information Sciences','2015-2020')
secEi2 = (0,'Graduate','East High School','June 2014')
#section: extracurricular(v)
secVi1 = (0,'Volunteer','Wild B.I.R.D.','2010-2017')
secVi2 = (1,'Member','Denver Field Ornithologists','2016-2020')
#section: profile(c); special formatting
cogprof = dict()
cogprof['Verbal comprehension'] = 141
cogprof['Perceptual reasoning'] = 127
cogprof['Working memory'] = 108
cogprof['Processing speed'] = 89
cofprof['General ability'] = 139
data = [list(cogprof),list(cogprof.values())] #for table generation
##

##Scoring framework


##Category definitions/inheritance
#ctree parser from file
textc = open('ctree.txt','r')
text = textc.readlines()
ctree = dict()
depth = 0
ptiers = dict() #depth key, parent value
for l in range(len(text)):
    if (text[l][0]!='-'):   #outermost parent
        depth = 0
        ptiers[depth] = text[l][depth:]
    elif (text[l][depth]!='-')and(text[l][depth-1]!='-'): #<
        for m in range(depth):     #break back syntax
            if (text[l][m]!='-'):
                depth = m
                break
        ptiers[depth] = text[l][depth:]
        addval(ctree, ptiers[depth-1], ptiers[depth])
    elif (text[l][depth]!='-')and(text[l][depth-1]=='-'): #V
        ptiers[depth] = text[l][depth:]
        addval(ctree, ptiers[depth-1], ptiers[depth])
    elif (text[l][depth]=='-'):   #>
        depth += 1
        ptiers[depth] = text[l][depth:]
        addval(ctree, ptiers[depth-1], ptiers[depth])
textc.close()
#parses ctree for parent lists
parentlist = list(ctree.keys())
ptree = dict()
for i in parentlist:
	parent = i
	children = ctree[parent]
	for j in children:
		ptree[j] = parent
#established dict for all scorables
points = dict.fromkeys(ptree.keys(),0)

##Input parsing; SINGLE FILE (hard-coded sections)
texti = open('posting.txt','r')
text = texti.readlines()
texti.close()
Ptitl = text[0]
Pcont = text[1]
Porgn = text[2]
Pmail = text[3]
##Scoring/selection alg; NEEDS SOLUTION FOR CASE-INSENSITIVE COMPARES
allwords = Pcont.split()
trimwords = allwords #use re module to trim, or?
for i in trimwords:
    if trimwords[i] in points:  #check word can be scored
        ripple(trimwords[i], 0) #scores word from depth 0; RECURSIVE
                                #ONLY CHECKS CHILDREN; NO DEFAULT TO GENERAL KNOWLEDGE
ptotal = sum(points.values())
#scores any applicable skills by points
score = dict.fromkeys(praxia, 0)
for j in praxia:
    if praxia[j] in points:
        score[praxia[j]] = points[praxia[j]]
stotal = sum(score.values())
#checks score out of possible
print("Total points possible: "+str(ptotal))
print("Total score: "+str(stotal))
print("Possible fraction: "+str(round(stotal/ptotal,3)))
print("Scaled fraction: "+str(round(stotal*5/ptotal,3)))
if (stotal*5/ptotal)<0.5:
    print("WARNING: low score, suggested not for submission!") #consider adding watermark
#
selects = sorted(score, key=score.get)
selects[:10] #picks top 10 items

##prepare for print

#establish template
#add obligatory header
#retrieve lines for selected items
#format selected items
#add obligatory footer
#






##clear points
pkeys = list(points)
for i in pkeys:
    points[pkeys[i]]=0
##export
canv.save()