import pandas as pd

class preprocessor:

    def __init__(self):
        self.book_content=''

    def __str__(self):
        return str(self.book_content)

    def clean(self):
#at condition for that none and 1
#remove more special charters
        self.book_content=self.book_content.replace("'",'').replace('-',' ').replace('_',' ').replace(':','')\
        .replace('.','').replace('/','').replace(',','').replace('(','').replace(')','').replace('~','')\
        .replace('$','').replace('[','').replace(']','').replace('*','').replace('@','').replace('—','')\
        .replace('!','').replace('#','').replace('?','').replace(';','').replace('"','')\
        .replace('%','')
        self.book_content=self.book_content.lower()


    def read_text(self,text_name):
        read=open(text_name,'r')
        self.book_content=read.read()

class WordAnalyser:

    def __init__(self):
        self.word_counts={}

    def __str__(self):
        return str((self.word_counts))

    def analyse_words(self, book_text):
        self.book_text=book_text.split()
        for word in self.book_text:
            if word not in self.word_counts:
                self.word_counts[word]=1
            else:
                self.word_counts[word]+=1

    def get_word_frequency(self):
        word=self.word_counts.keys()
        word_values=self.word_counts.values()
        word_values=list(word_values)
        total_words=sum(word_values)
        word_frequency=[]
        for values in word_values:
            word_frequency.append(values/total_words)
        self.get_word_frequency=dict(zip(word,word_frequency))
        self.word_counts=self.get_word_frequency
        return self.word_counts

class IDFAnalyser:

    def __init__(self):
        self.data=pd.DataFrame()


    def load_frequency(self,book_frequency,book_title):
        self.data=pd.DataFrame(book_frequency,index=[str(book_title)])


    def get_IDF(self,term):
        pass

    def __str__(self):
        return self.data

#1952-0/txt
b=preprocessor()
b.read_text('1952-0.txt')
b.clean()
book=b.__str__()


c=WordAnalyser()
c.analyse_words(book)
co=c.get_word_frequency()
print(co)

e=IDFAnalyser()
e.load_frequency(co,'199')
r=e.__str__()
print(r)

#11-0.txt
t=preprocessor()
t.read_text('11-0.txt')
t.clean()
book2=t.__str__()


s=WordAnalyser()
s.analyse_words(book2)
so=s.get_word_frequency()
print(so)



f=IDFAnalyser()
f.load_frequency(so,'133')
u=f.__str__()
print(u)

#want the both text load_frequency in the same dataframe