get tractate data from redis

src/models/esmm/fe/tractate_fe.py

@@ -35,7 +35,30 @@ def get_tractate_from_redis():
     """
     return: {tractate_id: {first_demands: [], is_pure_author: 1}}
     """
-    pass
+    db_key = "cvr:db:content:tractate"
+    column_key = db_key + ":column"
+    columns = str(redis_db_client.get(column_key), "utf-8").split("|")
+    d = redis_db_client.hgetall(db_key)
+    res = {}
+    for i in d.values():
+        row_list = str(i, "utf-8").split("|")
+        tmp = {}
+        for (index, elem) in enumerate(row_list):
+            col_name = columns[index]
+            if col_name in [
+                    "first_demands", "second_demands", "first_solutions", "second_solutions", "first_positions",
+                    "second_positions", "projects"
+            ]:
+                tmp[col_name] = elem.split(",")
+            elif col_name in ["is_pure_author", "is_have_pure_reply", "is_have_reply"]:
+                if elem == "true":
+                    tmp[col_name] = 1
+                else:
+                    tmp[col_name] = 0
+            else:
+                tmp[col_name] = elem
+            res[int(tmp["card_id"])] = tmp
+    return res
 
 
 def tractate_feature_engineering(tractate_df):

src/train_tractate.py

@@ -65,7 +65,7 @@ def main():
     predict_fn = tf.contrib.predictor.from_saved_model(save_path)
 
     device_dict = device_fe.get_device_dict_from_redis()
-    diary_dict = tractate_fe.get_diary_dict_from_redis()
+    diary_dict = tractate_fe.get_tractate_dict_from_redis()
 
     device_ids = list(device_dict.keys())[:20]
     diary_ids = list(diary_dict.keys())