点击排行
@index_blu.route('/')
def index():
...
# 获取点击排行数据
news_list = None
try:
news_list = News.query.order_by(News.clicks.desc()).limit(constants.CLICK_RANK_MAX_NEWS)
except Exception as e:
current_app.logger.error(e)
click_news_list = []
for news in news_list if news_list else []:
click_news_list.append(news.to_basic_dict())
data = {
"user_info": user.to_dict() if user else None,
"click_news_list": click_news_list,
}
return render_template('news/index.html', data=data)
判断是否收藏
@news_blu.route('/<int:news_id>')
@user_login_data
def news_detail(news_id):
...
# 判断是否收藏该新闻,默认值为 false
is_collected = False
# 判断用户是否收藏过该新闻
if g.user:
if news in g.user.collection_news:
is_collected = True
data = {
"news": news.to_dict(),
"click_news_list": click_news_list,
"is_collected": is_collected,
"user_info": g.user.to_dict() if g.user else None,
}
return render_template('news/detail.html', data=data)
收藏
@news_blu.route("/news_collect", methods=['POST'])
@user_login_data
def news_collect():
"""新闻收藏"""
user = g.user
json_data = request.json
news_id = json_data.get("news_id")
action = json_data.get("action")
if not user:
return jsonify(errno=RET.SESSIONERR, errmsg="用户未登录")
if not news_id:
return jsonify(errno=RET.PARAMERR, errmsg="参数错误")
if action not in ("collect", "cancel_collect"):
return jsonify(errno=RET.PARAMERR, errmsg="参数错误")
try:
news = News.query.get(news_id)
except Exception as e:
current_app.logger.error(e)
return jsonify(errno=RET.DBERR, errmsg="查询数据失败")
if not news:
return jsonify(errno=RET.NODATA, errmsg="新闻数据不存在")
if action == "collect":
user.collection_news.append(news)
else:
user.collection_news.remove(news)
try:
db.session.commit()
except Exception as e:
current_app.logger.error(e)
db.session.rollback()
return jsonify(errno=RET.DBERR, errmsg="保存失败")
return jsonify(errno=RET.OK, errmsg="操作成功")
新闻评论
@news_blu.route('/news_comment', methods=["POST"])
@user_login_data
def add_news_comment():
"""添加评论"""
user = g.user
if not user:
return jsonify(errno=RET.SESSIONERR, errmsg="用户未登录")
# 获取参数
data_dict = request.json
news_id = data_dict.get("news_id")
comment_str = data_dict.get("comment")
parent_id = data_dict.get("parent_id")
if not all([news_id, comment_str]):
return jsonify(errno=RET.PARAMERR, errmsg="参数不足")
try:
news = News.query.get(news_id)
except Exception as e:
current_app.logger.error(e)
return jsonify(errno=RET.DBERR, errmsg="查询数据失败")
if not news:
return jsonify(errno=RET.NODATA, errmsg="该新闻不存在")
# 初始化模型,保存数据
comment = Comment()
comment.user_id = user.id
comment.news_id = news_id
comment.content = comment_str
if parent_id:
comment.parent_id = parent_id
# 保存到数据库
try:
db.session.add(comment)
db.session.commit()
except Exception as e:
current_app.logger.error(e)
return jsonify(errno=RET.DBERR, errmsg="保存评论数据失败")
# 返回响应
return jsonify(errno=RET.OK, errmsg="评论成功", data=comment.to_dict())
是否点赞数据返回
@news_blu.route('/<int:news_id>')
@user_login_data
def news_detail(news_id):
...
# 获取当前新闻的评论
comments = None
try:
comments = Comment.query.filter(Comment.news_id == news_id).order_by(Comment.create_time.desc()).all()
except Exception as e:
current_app.logger.error(e)
comment_like_ids = []
if g.user:
# 如果当前用户已登录
try:
comment_ids = [comment.id for comment in comments]
if len(comment_ids) > 0:
# 取到当前用户在当前新闻的所有评论点赞的记录
comment_likes = CommentLike.query.filter(CommentLike.comment_id.in_(comment_ids),
CommentLike.user_id == g.user.id).all()
# 取出记录中所有的评论id
comment_like_ids = [comment_like.comment_id for comment_like in comment_likes]
except Exception as e:
current_app.logger.error(e)
comment_list = []
for item in comments if comments else []:
comment_dict = item.to_dict()
comment_dict["is_like"] = False
# 判断用户是否点赞该评论
if g.user and item.id in comment_like_ids:
comment_dict["is_like"] = True
comment_list.append(comment_dict)
is_collected = False
# 判断用户是否收藏过该新闻
if g.user:
if news in g.user.collection_news:
is_collected = True
data = {
"news": news.to_dict(),
"click_news_list": click_news_list,
"is_collected": is_collected,
"user_info": g.user.to_dict() if g.user else None,
"comments": comment_list
}
return render_template('news/detail.html', data=data)