import logging
import random
import re
import jieba
import pandas as pd
from flask import Flask, render_template, jsonify
from nltk.corpus import stopwords
import utils

# author: cxy
app = Flask(__name__)


@app.before_request
def setup_logging():
    # 确保日志处理器已正确初始化
    if not logging.getLogger('werkzeug').handlers:
        logging.getLogger('werkzeug').addHandler(logging.StreamHandler())

    class RequestFilter(logging.Filter):
        def filter(self, record):
            return 'GET /time' not in record.getMessage()

    handler = logging.getLogger('werkzeug').handlers[0]

    handler.addFilter(RequestFilter())


@app.route('/')
def hello_world():  # put application's code here
    return render_template("main.html")


@app.route('/time')
def get_time():
    return utils.get_time()


@app.route('/data')
def get_data():
    df = pd.read_csv('./static/csv/barrage_clustered.csv')
    data = df.to_dict(orient='records')
    return jsonify(data)


@app.route('/wordcloud')
def wordcloud_data():
    file_name = './static/csv/barrage.csv'
    with open(file_name, encoding='utf-8') as f:
        txt = f.read()

    txt_list = jieba.lcut(txt)

    stopwords_list = set(stopwords.words('chinese'))
    stopwords_target = ['都', '不', '好', '哈哈哈', '说', '还', '很', '没']
    for i in stopwords_target:
        stopwords_list.add(i)

    word_freq = {}
    for word in txt_list:
        if re.match(r'^[\u4e00-\u9fa5]+$', word) and word not in stopwords_list:
            if word in word_freq:
                word_freq[word] += 1
            else:
                word_freq[word] = 1
    word_freq_list = [{'name': word, 'value': freq} for word, freq in word_freq.items()]
    return jsonify(word_freq_list)


@app.route('/world_comment')
def get_world_comment():
    file_path = './static/csv/world_comment.csv'
    df = pd.read_csv(file_path)
    data = []
    grouped = df.groupby('url')
    times = ['20s', '30s', '40s', '50s', '60s']
    for url, group in grouped:
        items = group['content'].tolist()
        time = random.choice(times)
        data.append({'time': time, 'items': items})
    return jsonify(data)


@app.route('/barrage_sentiment')
def get_barrage_comment():
    df = pd.read_csv('./static/csv/barrage_sentiment.csv')
    data = df.to_dict(orient='records')
    return jsonify(data)


@app.route('/barrage_count')
def count_rows():
    df = pd.read_csv('./static/csv/barrage.csv')
    row_count = len(df['barrage'])
    return jsonify({'row_count': row_count})


@app.route('/average_sentiment')
def average_sentiment():
    df = pd.read_csv('./static/csv/barrage_sentiment.csv')
    avg_sentiment = df['sentiment'].mean()
    return jsonify({'average_sentiment': avg_sentiment})


@app.route('/count_keywords')
def count_keywords():
    df = pd.read_csv('./static/csv/barrage.csv')
    keyword_count = df['barrage'].str.contains('AI技术|人工智能|科技|智能').sum()
    keyword_count = int(keyword_count)
    return jsonify({'keyword_count': keyword_count})


if __name__ == '__main__':
    app.run()