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app.py

@@ -1,114 +0,0 @@
-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()

utils.py

@@ -1,8 +0,0 @@
-import time
-
-
-def get_time():
-    time_str = time.strftime("%Y{}%m{}%d{} %X")
-    return time_str.format("年", "月", "日")
-
-