新增识别序号列

classify_server.py

@@ -7,6 +7,7 @@ from protobuf import classify_pb2_grpc
 from utils.config import model_config
 from utils.config import model_config
 from utils.predic_fac import PredictorFac
 from utils.predic_fac import PredictorFac
 from utils.log_manager import get_logger
 from utils.log_manager import get_logger
+from utils.excel_manager import read_from_excel
 log_server = get_logger('server')
 log_server = get_logger('server')
 
 
 
 
@@ -40,5 +41,8 @@ def serve():
 
 
 
 
 if __name__ == '__main__':
 if __name__ == '__main__':
-    serve()
-    # print(Classify().fac_test_predic('lm358'))
+    # serve()
+    data = read_from_excel('DZ0901_V1.4_BOM.xlsx', 'DZ0901_V1.3BOM清单')
+    print(data)
+    print(Classify().fac_test_predic(data))
+

predict/list_predict.py

 #!/usr/bin/env python
 #!/usr/bin/env python
 # -*- coding:utf-8 -*-
 # -*- coding:utf-8 -*-
 from predict.base_handler import BasePredictor
 from predict.base_handler import BasePredictor
+from utils.excel_manager import read_from_excel
+
+
+order_list = ['序号']
 
 
 
 
 class LiPredict(BasePredictor):
 class LiPredict(BasePredictor):
 
 
+    def predict(self, key):
+        if len(key) > 0:
+            self.order_predict(key[0])
         pass
         pass
+
+    def order_predict(self, data):
+        collect_num = [int(kw) for kw in data if isinstance(kw, float) or isinstance(kw, int)]
+        judge = self.IsIncrease(collect_num, len(collect_num))
+        print('judge: ' + str(judge))
+        return judge
+
+    """
+    判断列表元素是否递增
+    """
+    def IsIncrease(self, arr, size):
+        if size == 1:
+            return True
+        return (arr[size - 1] >= arr[size - 2]) and self.IsIncrease(arr, size - 1)
+
+

utils/excel_manager.py

+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+import xlwt
+import xlrd
+
+
+def read_from_excel(file_name, sheet_name):
+    wb = xlrd.open_workbook(file_name)
+    sheet = wb.sheet_by_name(sheet_name)
+    row = sheet.nrows
+    col = sheet.ncols
+    result_dict = {}
+    for i in range(col):
+        col_list = []
+        for j in range(row): col_list.append(sheet.cell_value(j, i))
+        result_dict[i] = col_list
+    return result_dict
+

utils/predic_fac.py

@@ -15,7 +15,7 @@ class PredictorFac():
     def _get_predictor(self, data):
     def _get_predictor(self, data):
         if isinstance(data, str):
         if isinstance(data, str):
             return self.kw_predictor
             return self.kw_predictor
-        elif isinstance(data, list):
+        elif isinstance(data, dict):
             return self.list_predictor
             return self.list_predictor
 
 
     def predic(self, data):
     def predic(self, data):