def news(offset, limit=20):
result = {}
items = []
category = request.args.get('category')
keyword = request.args.get('keyword')
if offset < 0 or limit <= 0:
result = Result(code=Result.FAIL, msg='offset或limit参数有误！')
return result.to_json()
# 筛选字段，过滤 _id(ObjectId) 避免序列化异常
column = {'_id': 0}
# 组装查询条件，无法拼接出带模糊查询的 sql，pymongo 就是个垃圾！！！
# condition = {}
# if category:
# condition['news_web_category'] = category
# if keyword:
# regex = {'$regex': '.*{}.*'.format(keyword)}
# condition['new_title'] = regex
# print(condition)
try:
if not category and not keyword:
items = list(mongo.collection.find({}, column).sort('news_datetime', -1).skip(offset).limit(limit))
count = mongo.collection.find({}, column).count()
result = PageResult(items, count=count)
if category and not keyword:
items = list(mongo.collection.find({'news_web_category': category}, column).sort('news_datetime', -1).skip(
offset).limit(limit))
count = mongo.collection.find({'news_web_category': category}, column).count()
result = PageResult(items, count=count)
if not category and keyword:
items = list(
mongo.collection.find({'news_title': re.compile(keyword, re.IGNORECASE)}, column).sort('news_datetime',
-1).skip(
offset).limit(limit))
count = mongo.collection.find({'news_title': re.compile(keyword, re.IGNORECASE)}, column).count()
result = PageResult(items, count=count)
if keyword and category:
items = list(
mongo.collection.find({'news_web_category': category, 'news_title': re.compile(keyword, re.IGNORECASE)},
column).sort('news_datetime', -1).skip(offset).limit(limit))
count = mongo.collection.find(
{'news_web_category': category, 'news_title': re.compile(keyword, re.IGNORECASE)}, column).count()
result = PageResult(items, count=count)
except Exception as e:
result = Result(code=Result.FAIL, msg=e)
return result.to_json()
# for file in filelist:
# src_name = file.split('.')[0]
# result = num_recog.main(os.path.join(path,file))
# print src_name,result
# if int(src_name) == int(result):
# right += 1
# else:
# continue
# right_rate = float(right)/len(filelist)
# print ('rate is {}%'.format(right_rate*100))
if __name__ == "__main__":
result = Result()
img_type = sys.argv[1]
img_file = sys.argv[2]
# img_type = "file"
# img_file = "D:/machine_learning/recognization/insurance_doc/1.jpg"
try:
num_recog = Number_recognition()
predict_data = num_recog.main(img_file)
data = {'captcha': predict_data}
result.code = code.SUCCESS
result.msg = "success"
result.data = data
except Exception, e:
exstr = traceback.format_exc()
logging.info('#####系统异错误error:%s', exstr)
result.code = code.FAIL
result.msg = sys.exc_info()
print result.to_json()