import random
import re

class MarkovChainer(object):
    def __init__(self, order):
        self.order=order
        self.beginnings = []
        self.freq = {}

    #pass a string with a terminator to the function to add it to the markov lists.
    def add_sentence(self, string, terminator):
        data = "".join(string)
        words = data.split()
        buf = []
        if len(words) > self.order:
            words.append(terminator)
            self.beginnings.append(words[0:self.order])    
        else:
            pass
        
        for word in words:
            buf.append(word)
            if len(buf) == self.order + 1:
                mykey = (buf[0], buf[-2])
                if mykey in self.freq:
                    self.freq[mykey].append(buf[-1])
                else:
                    self.freq[mykey] = [buf[-1]]
                buf.pop(0)
            else:
                continue
        return

    def add_text(self, text):
        text = re.sub(r'\n\s*\n/m', ".", text)
        seps = '([.!?;:])'
        pieces = re.split(seps, text)
        sentence = ""
        for piece in pieces:
            if piece != "":
                if re.search(seps, piece):
                    self.add_sentence(sentence, piece)
                    sentence = ""
                else:
                    sentence = piece

    #Generate the goofy sentences that become your tweet.
    def generate_sentence(self):
        res = random.choice(self.beginnings)
        res = res[:]
        if len(res)==self.order:
            nw = True
            while nw != None:
                restup = (res[-2], res[-1])
                try:
                    nw = self.next_word_for(restup)
                    if nw != None:
                        res.append(nw)
                    else:
                        continue
                except:
                    nw = False
            new_res = res[0:-2]
            if new_res[0].istitle() or new_res[0].isupper():
                pass
            else:
                new_res[0] = new_res[0].capitalize()
            sentence = ""
            for word in new_res:
                sentence += word + " "
            sentence += res[-2] + res[-1]

        else:
            sentence = None
        return sentence

    def next_word_for(self, words):
        try:
            arr = self.freq[words]
            next_words = random.choice(arr)
            return next_words
        except:
            return None        

if __name__ == "__main__":
    print "Try running ebooks.py first"