{"counts": 11,"items": [...{"author": "","categoryID": 1,"categoryName": null,"id": 9,"imgURL": ""introduction": "腹黑總裁..","state": 1,"title": "腹黑總裁，寵溺嬌妻"},{"author": "","categoryID": 1,"categoryName": null,"id": 10,"imgURL": ""introduction": "不要再糾纏愛我...","state": 1,"title": "不要再糾纏愛我"}],"page": 1,"pages": 2,"pagesize": 10
}

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

# 定義路由，分類書籍列表@category_bp.route('/filters')
def category_book_list():# 1.獲取參數: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)# 字數類型說明：0表示所有，1表示50萬字以下，2表示50~100萬字，3表示100萬字以上words = request.args.get('words',-1,int)# 排序條件說明：1表示按熱度，2表示按收藏order = request.args.get('order',1,int)# 參數判斷if not category_id:return jsonify(msg='缺少分類id'),400# 2.根據分類條件category_id，查詢數據，查詢書籍大分類數據categories = BookBigCategory.query.get(category_id)# 3.判斷查詢結果，根據大分類數據，使用關系引用，獲取二級分類數據# 使用列表推導式,使用set集合seconds_id = set([i.cate_id for i in categories.second_cates])# 4.根據分類數據，查詢書籍表，獲取分類范圍內的書籍數據# -----過濾查詢：保存的是查詢結果對象，因為，后續需要對數據進行再次查詢的操作query = Book.query.filter(Book.cate_id.in_(seconds_id))# 5.根據字數條件words查詢書籍數據# -----1表示50萬字以下，2表示50~100萬字，3表示100萬字以上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.根據排序條件order，按照最熱、收藏數量進行排序查詢# -----1表示按熱度，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='錯誤的排序選項'),400# 7.對查詢結果進行分頁處理，paginate# -----paginate函數表示分頁：返回結果為分頁的對象# 第一個參數表示頁數，第二個參數表示每頁的條目數，第三個參數False表示分頁異常不報錯paginate = query.paginate(page,pagesize,False)# items表示獲取分頁后的數據、page表示當前頁數、# pages表示每頁數據條目數total表示分頁的總頁數books_list = paginate.itemsitems = []# 8.遍歷分頁數據，獲取每頁數據、總頁數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.轉成json，返回數據data = {'counts':paginate.total,'pagesize':pagesize,'pages':paginate.pages,'page':paginate.page,'items':items}return jsonify(data)

{'title':'搜索詞','isHot':'是否熱門'
}

# 導入藍圖from flask import Blueprint# 創建藍圖對象search_bp = Blueprint('search',__name__,url_prefix='/search')

# 定義路由，關鍵詞熱門搜索@search_bp.route("/tags")
def tag_list():# 1.獲取參數，用戶搜索的關鍵詞key_wordkey_word = request.args.get("key_word")# 校驗參數if not key_word:return jsonify([])# 2.根據參數，查詢數據庫，搜索關鍵詞表進行過濾查詢、過濾關鍵詞# 熱門搜索詞，默認提供10條數據search_list = SearchKeyWord.query.filter(SearchKeyWord.keyword.contains(key_word)).limit(10)# 3.返回查詢結果data = [{'title':index.keyword,'isHot':index.is_hot,}for index in search_list]# 轉成json返回return jsonify(data)

{"counts": 11,"items": [...{"author": "","categoryID": 1,"categoryName": null,"id": 9,"imgURL": ""introduction": "腹黑總裁..","state": 1,"title": "腹黑總裁，寵溺嬌妻"},{"author": "","categoryID": 1,"categoryName": null,"id": 10,"imgURL": ""introduction": "不要再糾纏愛我...","state": 1,"title": "不要再糾纏愛我"}],"page": 1,"pages": 2,"pagesize": 10
}

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

# 定義路由，搜索書本列表@search_bp.route('/books')
def search_books():# 1.獲取參數，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.檢查關鍵詞參數if not key_word:return jsonify(msg='參數錯誤'),400# 3.根據關鍵詞參數，對書籍數據庫進行過濾查詢，包含query = Book.query.filter(Book.book_name.contains(key_word))# 4.判斷查詢結果# 5.對查詢結果進行分頁處理，items/page/pagespaginate = query.paginate(page,pagesize,False)# 獲取分頁后的書本數據book_list = paginate.items# 6.遍歷分頁后的數據，獲取每本書籍的數據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.返回結果data = {'counts':paginate.total,'pages':paginate.pages,'page':paginate.page,'items':items}return jsonify(data)