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 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()