{"counts": 11,"items": [...{"author": "","categoryID": 1,"categoryName": null,"id": 9,"imgURL": ""introduction": "腹黑总裁..","state": 1,"title": "腹黑总裁，宠溺娇妻"},{"author": "","categoryID": 1,"categoryName": null,"id": 10,"imgURL": ""introduction": "不要再纠缠爱我...","state": 1,"title": "不要再纠缠爱我"}],"page": 1,"pages": 2,"pagesize": 10
}

from flask import Blueprintcategory_bp = Blueprint('category', __name__)

# 定义路由，分类书籍列表@category_bp.route('/filters')
def category_book_list():# 1.获取参数:page/pagesize/category_id/words/orderpage = request.args.get('page',1,int)pagesize = request.args.get('pagesize',10,int)category_id = request.args.get('category_id',0,int)# 字数类型说明：0表示所有，1表示50万字以下，2表示50~100万字，3表示100万字以上words = request.args.get('words',-1,int)# 排序条件说明：1表示按热度，2表示按收藏order = request.args.get('order',1,int)# 参数判断if not category_id:return jsonify(msg='缺少分类id'),400# 2.根据分类条件category_id，查询数据，查询书籍大分类数据categories = BookBigCategory.query.get(category_id)# 3.判断查询结果，根据大分类数据，使用关系引用，获取二级分类数据# 使用列表推导式,使用set集合seconds_id = set([i.cate_id for i in categories.second_cates])# 4.根据分类数据，查询书籍表，获取分类范围内的书籍数据# -----过滤查询：保存的是查询结果对象，因为，后续需要对数据进行再次查询的操作query = Book.query.filter(Book.cate_id.in_(seconds_id))# 5.根据字数条件words查询书籍数据# -----1表示50万字以下，2表示50~100万字，3表示100万字以上if words == 1:query = query.filter(Book.word_count < 500000)elif words == 2:query = query.filter(Book.word_count.between(500000,1000000))elif words == 3:query = query.filter(Book.word_count > 1000000)# 6.根据排序条件order，按照最热、收藏数量进行排序查询# -----1表示按热度，2表示按收藏if order == 1:query = query.order_by(Book.heat.desc())elif order == 2:query = query.order_by(Book.collect_count.desc())else:return jsonify(msg='错误的排序选项'),400# 7.对查询结果进行分页处理，paginate# -----paginate函数表示分页：返回结果为分页的对象# 第一个参数表示页数，第二个参数表示每页的条目数，第三个参数False表示分页异常不报错paginate = query.paginate(page,pagesize,False)# items表示获取分页后的数据、page表示当前页数、# pages表示每页数据条目数total表示分页的总页数books_list = paginate.itemsitems = []# 8.遍历分页数据，获取每页数据、总页数for item in books_list:items.append({'id':item.book_id,'title':item.book_name,'introduction':item.intro,'author':item.author_name,'state':item.status,'category_id':item.cate_id,'category_name':item.cate_name,'imgURL':'})# 9.转成json，返回数据data = {'counts':paginate.total,'pagesize':pagesize,'pages':paginate.pages,'page':paginate.page,'items':items}return jsonify(data)

{'title':'搜索词','isHot':'是否热门'
}

# 导入蓝图from flask import Blueprint# 创建蓝图对象search_bp = Blueprint('search',__name__,url_prefix='/search')

# 定义路由，关键词热门搜索@search_bp.route("/tags")
def tag_list():# 1.获取参数，用户搜索的关键词key_wordkey_word = request.args.get("key_word")# 校验参数if not key_word:return jsonify([])# 2.根据参数，查询数据库，搜索关键词表进行过滤查询、过滤关键词# 热门搜索词，默认提供10条数据search_list = SearchKeyWord.query.filter(SearchKeyWord.keyword.contains(key_word)).limit(10)# 3.返回查询结果data = [{'title':index.keyword,'isHot':index.is_hot,}for index in search_list]# 转成json返回return jsonify(data)

{"counts": 11,"items": [...{"author": "","categoryID": 1,"categoryName": null,"id": 9,"imgURL": ""introduction": "腹黑总裁..","state": 1,"title": "腹黑总裁，宠溺娇妻"},{"author": "","categoryID": 1,"categoryName": null,"id": 10,"imgURL": ""introduction": "不要再纠缠爱我...","state": 1,"title": "不要再纠缠爱我"}],"page": 1,"pages": 2,"pagesize": 10
}

from flask import Blueprintsearch_bp = Blueprint('search', __name__,url_prefix='/search')

# 定义路由，搜索书本列表@search_bp.route('/books')
def search_books():# 1.获取参数，key_word/page/pagesizekey_word = request.args.get("key_word")page = request.args.get('page',1,int)pagesize = request.args.get("pagesize",10,int)# 2.检查关键词参数if not key_word:return jsonify(msg='参数错误'),400# 3.根据关键词参数，对书籍数据库进行过滤查询，包含query = Book.query.filter(Book.book_name.contains(key_word))# 4.判断查询结果# 5.对查询结果进行分页处理，items/page/pagespaginate = query.paginate(page,pagesize,False)# 获取分页后的书本数据book_list = paginate.items# 6.遍历分页后的数据，获取每本书籍的数据items = []for book in book_list:items.append({'id':book.book_id,'title':book.book_name,'intro':book.intro,'author':book.author_name,'state':book.status,'category_id':book.cate_id,'category_name':book.cate_name,'imgURL':'})# 7.返回结果data = {'counts':paginate.total,'pages':paginate.pages,'page':paginate.page,'items':items}return jsonify(data)