增加批量识别接口

http_server.py

@@ -29,6 +29,18 @@ class KwHandler(BaseHandler):
             res['status'] = code
         self.write(res)
 
+    async def post(self):
+        target = self.request.body
+        list_data = json.loads(self.request.body)
+        predict_type = unquote(self.get_argument('type', 'all'))
+        bom_log.info(f'http收到识别关键词列表: {target}, 预测类型为{predict_type}')
+        code, res = self.predictorfac.predict(list_data, predict_type)
+        if code != 1:
+            res = code2msg(code)
+            bom_log.error(f'http关键词批量识别报错: ' + res['message'])
+        else:
+            res['status'] = code
+        self.write(res)
 
 class DictHandler(BaseHandler):
     async def post(self):

predic_fac.py

@@ -14,31 +14,34 @@ class PredictorFac:
         self.dict_predictor = dict_predict.DicPredict('dict')
         self.txt_predictor = txt_predict.TxtPredict('txt')
 
-    def _get_predictor(self, data):
+    def _get_predictor(self, data, predict_type):
         if isinstance(data, dict):
             return self.dict_predictor
         elif isinstance(data, list):
-            return self.txt_predictor
+            if predict_type == 'all':
+                return self.txt_predictor
+            elif predict_type == 'param':
+                return self.kw_predictor
         else:
             return self.kw_predictor
 
     def predict(self, dic_data, predict_type='all'):
-        predictor = self._get_predictor(dic_data)
-
-        try:
-            res = predictor.predict(dic_data, predict_type)
-            if isinstance(predictor, dict_predict.DicPredict):
-                if '数量' not in str(res):
-                    raise self.Status.NoQtyError
-                if '参数' not in str(res) and '型号' not in str(res):
-                    raise self.Status.NoParamGnError
+        predictor = self._get_predictor(dic_data, predict_type)
+        res = predictor.predict(dic_data, predict_type)
+        if predict_type == 'all':
+            try:
+                if isinstance(predictor, dict_predict.DicPredict):
+                    if '数量' not in str(res):
+                        raise self.Status.NoQtyError
+                    if '参数' not in str(res) and '型号' not in str(res):
+                        raise self.Status.NoParamGnError
+                return 1, res
+            except Status.StatusErrTup as e:
+                stat_code = e.value
+                return stat_code, code2msg(stat_code)
+        elif predict_type == 'param':
             return 1, res
 
-        except Status.StatusErrTup as e:
-            stat_code = e.value
-            return stat_code, code2msg(stat_code)
-
-
 if __name__ == "__main__":
     def get_test_data():
         import pandas as pd

predict/kw_predict.py

@@ -5,16 +5,23 @@ from static_config import EN_TO_ZH_MAP
 
 class KwPredict(BasePredictor):
 
-    def predict(self, string, predict_type='all'):
-        self.info.info('预测类型为: %s, 接收数据: %s' % (predict_type, string))
+    def predict(self, string_or_list, predict_type='all'):
+        self.info.info('预测类型为: %s, 接收数据: %s' % (predict_type, string_or_list))
         if predict_type == 'all':
-            result, prab = self.get_single_predict(string, BasePredictor.model, BasePredictor.extractor)
+            result, prab = self.get_single_predict(string_or_list, BasePredictor.model, BasePredictor.extractor)
             zh_prob = {EN_TO_ZH_MAP[k]: v for k, v in prab.items()}
             res = {'result': EN_TO_ZH_MAP[result], 'probably_dict': zh_prob, 'predict_type': predict_type}
         else:
             model = getattr(BasePredictor, predict_type + '_model')
             extractor = getattr(BasePredictor, predict_type + '_extractor')
-            result, prab = self.get_single_predict(string, model, extractor)
-            res = {'result': int(result), 'probably_dict': prab, 'predict_type': predict_type}
+            dic_result = {}
+            if isinstance(string_or_list, list):
+                for i in string_or_list:
+                    result, prab = self.get_single_predict(i, model, extractor)
+                    dic_result[i] = int(result[0])
+                res = {'result': dic_result, 'predict_type': predict_type}
+            else:
+                result= self.get_single_predict(string_or_list, model, extractor)
+                res = {'result': int(result[0]), 'predict_type': predict_type}
 
         return res