Updated file location

src/app.py

@@ -4,10 +4,10 @@ import pandas as pd
 import numpy as np
 import pickle
 import datetime
-import os
-import sys
+# import os
+# import sys
 # from utils import payday, date_extracts
-sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+# sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
 
 from utils import payday, date_extracts
 
@@ -23,11 +23,11 @@ st.set_page_config(
     }
 )
 
-# Define directory paths
-DIRPATH = os.path.dirname(os.path.realpath(__file__))
-ml_components_1 = os.path.join(DIRPATH, "..", "src", "assets", "ml_components", "ml_components_1.pkl")
-ml_components_2 = os.path.join(DIRPATH, "..", "src", "assets", "ml_components", "ml_components_2.pkl")
-image_path = os.path.join(DIRPATH, "..", "src", "assets", "images", "sales.png")
+# # Define directory paths
+# DIRPATH = os.path.dirname(os.path.realpath(__file__))
+# ml_components_1 = os.path.join(DIRPATH, "..", "src", "assets", "ml_components", "ml_components_1.pkl")
+# ml_components_2 = os.path.join(DIRPATH, "..", "src", "assets", "ml_components", "ml_components_2.pkl")
+# image_path = os.path.join(DIRPATH, "..", "src", "assets", "images", "sales.png")
 
 
 # create a functions to load pickle file.
@@ -38,8 +38,8 @@ def load_pickle(filename):
 
 
 #load all pickle files
-ml_compos_1 = load_pickle(ml_components_1)
-ml_compos_2 = load_pickle(ml_components_2)
+ml_compos_1 = load_pickle('ml_components_1.pkl')
+ml_compos_2 = load_pickle('ml_components_2.pkl')
 
 # components in ml_compos_2  
 categorical_pipeline = ml_compos_2['categorical_pipeline']
@@ -54,7 +54,7 @@ cat_cols = ml_compos_1['cat_cols']
 st.title('✨SALES FORECASTING APP✨')
 
 # adding image
-image=Image.open(image_path)
+image=Image.open('sales.png')
 st.image(image, width=600)
 
      

utils.py

@@ -0,0 +1,29 @@
+import numpy as np
+import pickle
+
+
+
+
+def payday(row):
+    if row.DayOfMonth == 15 or row.Is_month_end == 1:
+        return 1
+    else:
+        return 0
+        
+
+def date_extracts(data):
+    data['Year'] = data.index.year
+    data['Month'] = data.index.month
+    data['DayOfMonth'] = data.index.day
+    data['DaysInMonth'] = data.index.days_in_month
+    data['DayOfYear'] = data.index.day_of_year
+    data['DayOfWeek'] = data.index.dayofweek
+    data['Week'] = data.index.isocalendar().week
+    data['Is_weekend'] = np.where(data['DayOfWeek'] > 4, 1, 0)
+    data['Is_month_start'] = data.index.is_month_start.astype(int)
+    data['Is_month_end'] = data.index.is_month_end.astype(int)
+    data['Quarter'] = data.index.quarter
+    data['Is_quarter_start'] = data.index.is_quarter_start.astype(int)
+    data['Is_quarter_end'] = data.index.is_quarter_end.astype(int)
+    data['Is_year_start'] = data.index.is_year_start.astype(int)
+    data['Is_year_end'] = data.index.is_year_end.astype(int)