import math
import datetime

#generate string for date
date=datetime.datetime.now().strftime("%Y-%m-%d")
print(date)

#attributes collected
total_score=0

attributes={
    'Become less apathetic':{
        'Waking up properly':0, #10, wake up instantly
        'Not overwhelmed by negative emotion':0, #assuming u wake up prop thats fine
        'Interest in becoming less apathetic':0, #lack of resent towards waking up
        'Time used with purpose':0,#didnt waste any time, did stuff i enjoyed or had to do all day
    },
    'Done school work':{
        'Present in school ':0, #go to school, focus/no school
        'No homework related trouble':0, #do homework well
        'Did revision (followed schedule?)':0, #revise, follow schedule
        'Interest in doing school work':0 #interest doing the grind
    },
    'Work harder for GoodByte':{
        'Make gun system for RvB':0, #finish gun system
        'Game progress':0, # do all tasks listed
        #'Goodbyte progress':0, # goodbyte improves as group, find way to measure
        'Interest in work':0 #fascinated by work
    },
    'Become closer to people':{
        'Spoke to people':0, #find time to speak to people, see someone irl
        'Social satisfaction':0, #be happy with people ur talking to
        'Interest in being socially active':0 #wanting to pursue
    },
    'Pursued creative endevaours':0, #write about oli/music/read/design
    'Maintained my physical health':0, #do intense circuit training, go outside
    'Acted brave, confident and confront my issues':0 #cold shower, do something new
}

comments={}

final_analysis={}

#collect userdata
def parse_attribute(att):
    for attribute in att:
        value=att[attribute]
        if value != 0:
            parse_attribute(value)
        else:
            user_input=input(attribute+" out of 10")
            userdata={'score':int(user_input[0:2])}

            #if len(user_input) >2:
            comments[attribute]= user_input[2:len(user_input)]

            att[attribute]=userdata

#converts attributes into flat dict with data
def get_final_analysis(index,value,ancestor):
    final_analysis[index]={'score':0,'maxm':0,'ancs':len(ancestor)-2}

    ancestor = ancestor.copy()
    ancestor.append(index)

    #if is end node of recursive tree
    if 'score' in value:
        score=value['score']
        for i in range(1,len(ancestor)):
            key=ancestor[i]
            new_score=final_analysis[key]['score']+score
            new_max=final_analysis[key]['maxm']+10
            ancs=final_analysis[key]['ancs']
            final_analysis[key]={'score':new_score,'maxm':new_max,'ancs':ancs}
    elif isinstance(value,dict):
        #call recursive function to find end node
        for index,attribute in value.items():
            get_final_analysis(index,attribute,ancestor)

#format and save data
def clean_final_analysis():

    #log detailed stats
    f=open('data/'+date+'.txt','w+')
    for key,data in final_analysis.items():
        score=str(data['score'])+'/'+str(data['maxm'])
        perc = str(math.floor((data['score']/data['maxm'])*100))+'%'

        comment=''

        if key in comments:
            comment=comments[key]

        f.write(('    '*data['ancs'])+key+": "+score+' '+perc+' '+comment)
        f.write("\r\n")
        if key=='total_score':
            f.write("\r\n")
    f.close()

    #print out
    f=open('data/'+str(date)+'.txt','r+')
    print(f.read())
    f.close()

    f=open('data/'+date+'.txt','a+')
    final_comments = input("What are your comments for improvement?")

    f.write("\r\nFinal comments: "+final_comments)
    f.close()

    #log generalised stats
    data_txt=open('general/data.txt','a')

    data=final_analysis['total_score']

    score=str(data['score']) + '/' + str(data['maxm'])
    perc=str(math.floor((data['score']/data['maxm'])*100))+'%'

    data_txt.write(str(date) + ': ' +score+' ' +perc+',\r\n')
    data_txt.close()



parse_attribute(attributes)
get_final_analysis('total_score',attributes,['total_score'])
clean_final_analysis()

exit()