blogClassifier/main.py at master · yangda75/blogClassifier · GitHub

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import os
import tkinter

import prepare
import scraper

TAGS = ['teen_f', 'teen_m', 'adult_f', 'adult_m', 'mature_f', 'mature_m']
MINIMAL_PROB = {'teen_f': 1 / 26694629,
                'teen_m': 1 / 26829390,
                'adult_f': 1 / 40553782,
                'adult_m': 1 / 39002136,
                'mature_f': 1 / 16526313,
                'mature_m': 1 / 15941756}


class MainWin():
    def __init__(self, master):
        self.master = master
        # set title
        self.master.title("Naive bayes blog classifier")
        # validate function
        # vcmd = self.master.register(self.validate)
        self.userid = ""
        # entrty for userid
        self.entry = tkinter.Entry(self.master, text="enter a medium userID")
        # button to start
        self.start_button = tkinter.Button(
            self.master, text="start", command=self.gen_tag)
        # labels
        instruction = tkinter.Label(
            master, text="enter a medium userid, then press start button")
        label1 = tkinter.Label(self.master, text="userid: ")
        # arrange the UI components
        instruction.grid(row=0, columnspan=3)
        self.entry.grid(row=1, column=1)
        self.start_button.grid(row=1, column=2)
        label1.grid(row=1, column=0)

    def update(self):
        new_text = self.entry.get()
        if not new_text:
            self.userid = ""
            return False
        try:
            self.userid = new_text
            return True
        except ValueError:
            return False

    def gen_tag(self):
        if not self.update():
            err = tkinter.Label(
                self.master, text="error occured,please try again")
            err.grid(columnspan=3)
            return False
        results = analyze(self.userid)
        print("{0} guesses generated from the recent {1} posts of {2}".format(
            len(results), len(results), self.userid))
        score = {}
        # there may not be ten posts,
        for i in range(len(results)):
            print("post number: {0}, tag generated:{1}".format(i, results[i]))
            label = tkinter.Label(self.master, text="guess" + str(i))
            label.grid(row=i + 2, column=0)
            label = tkinter.Label(self.master, text=results[i])
            label.grid(row=i + 2, column=1)
            if results[i] in score.keys():
                score[results[i]] += 1
            else:
                score[results[i]] = 1
        label = tkinter.Label(self.master, text="most likey: ")
        label.grid(column=0)
        label = tkinter.Label(self.master, text=max(score, key=score.get))
        label.grid(column=1)
        return True


def analyze(userid):
    # save the recent 10 posts into ./userid/
    scraper.get_rec10(userid)
    # load the saved vocabulary file
    tag_vocab = {}
    for tag in TAGS:
        d = {}
        f = open(tag + '.csv')
        for line in f.readlines():
            if len(line.split(',')) == 2:
                newline = line.replace('\n', '')
                word, freq = newline.split(',')
                d[word] = float(freq)
        tag_vocab[tag] = d
    # save 10 classifying results in one list, then return it
    results = []
    # process the posts saved, generate hot words list
    for root, dirs, files in os.walk(userid):
        for f in files:
            if f.split('.')[-1] != 'txt':
                continue
            # get 30 most used words
            hot_words = prepare.prepare(userid + '/' + f)
            # core: calculate likelyhood for every tag
            probability = {}
            for tag in TAGS:
                probability[tag] = 1.0
                for word in hot_words:
                    try:
                        probability[tag] *= tag_vocab[tag][word]
                    except KeyError:
                        probability[tag] *= MINIMAL_PROB[tag]
            results.append(max(probability, key=probability.get))
    return results


GUI_ROOT = tkinter.Tk()
CLASSIFIER_GUI = MainWin(GUI_ROOT)
GUI_ROOT.mainloop()