Upload 19 files

app.py

@@ -3,6 +3,7 @@ import streamlit as st
 import pandas as pd
 import os
 import datetime
+from src.utils.helper_functions import send_mail
 
 import pipeline
 from config import Config
@@ -15,6 +16,10 @@ def main():
     if "state" not in st.session_state:
         st.session_state["state"] = True
         st.session_state["predictions_df"] = pd.DataFrame()
+        st.session_state["send_mail"] = False
+        st.session_state["text_input"] = ''
+        st.session_state["input_date"] = None
+
 
     st.set_page_config(
         layout="centered",  # Can be "centered" or "wide". In the future also "dashboard", etc.
@@ -64,9 +69,20 @@ def main():
             st.write(f'Average demand by category "{category}"')
             st.bar_chart(st.session_state["predictions_df"].groupby(category)['demand'].mean())
 
+
+            do_mail_sending = st.checkbox('Send mail')
+            if do_mail_sending:
+                # Display a text area if the checkbox is clicked
+                st.session_state["send_mail"] = do_mail_sending
+                st.session_state["text_input"] = st.text_input('Mail address:')
+
             input_save = st.checkbox(config['SAVE_CHECKBOX_TEXT'])
             confirm_params = {
-                    'input_save':input_save
+                    'input_save':input_save,
+                    'send_mail':st.session_state["send_mail"],
+                    'email_adress': st.session_state["text_input"],
+                    'forecast_start_date':st.session_state["input_date"][0].strftime("%Y/%m/%d"),
+                    'forecast_end_date':st.session_state["input_date"][1].strftime("%Y/%m/%d")
             }
 
             confirm = st.button(config['SAVE_BUTTON_TEXT'], on_click=save, args=(confirm_params,))
@@ -94,10 +110,27 @@ def save(params):
         today = datetime.datetime.today().strftime("%d-%m-%Y")
         st.session_state["predictions_df"][['product_id','date','demand']].to_excel(f'{dir}/predictions_{today}.xlsx', index=False)
 
+    if params['send_mail']:
+        status = send_mail(
+            name='Alper Temel',
+            email=params['email_adress'],
+            subject='Forecast Results',
+            message='Hi Captain',
+            dataframe=st.session_state["predictions_df"].loc[:, ['product_id','date','demand']],
+            forecast_start_date=params['forecast_start_date'],
+            forecast_end_date=params['forecast_end_date'],
+            toMail=params['email_adress']
+        )
+
+        if not status: # not successfull
+            return False
+
 
 # forecasting
 def predict(input_date):
 
+    st.session_state["input_date"] = input_date
+
     forecast_start_date = input_date[0].strftime("%Y-%m-%d")
     forecast_end_date = input_date[1].strftime("%Y-%m-%d")
 

config.py

@@ -5,6 +5,9 @@ class Config():
     def __init__(self):
         pass
 
+    MJ_APIKEY_PUBLIC = '2846230e59f26adb7ec9ff2790be29dc'
+    MJ_APIKEY_PRIVATE = 'fcbcb59ae402ef96b7b7d9bcb211fd44'
+
     target = 'demand'
     split_local_test = False
 
@@ -26,6 +29,7 @@ class Config():
     fold = 5
     fold_models_directory = 'models/date_models_test'
     fold_input_directory = 'maps/date_models_test'
+    result_path = 'demand_predictions/'
 
     catboost_params = {
         'learning_rate': 0.03,
@@ -56,4 +60,4 @@ class Config():
     
     SAVE_CHECKBOX_TEXT = 'Save predictions'
     SAVE_BUTTON_TEXT = 'Apply'
-    SAVE_BUTTON_SUCCESS_TEXT = 'File successfully saved'
+    SAVE_BUTTON_SUCCESS_TEXT = 'Successfully Applied!'

requirements.txt

@@ -1,4 +1,5 @@
 catboost==1.2.5
+mailjet_rest==1.3.4
 numpy==1.24.3
 pandas==2.0.0
 scikit_learn==1.2.2

src/utils/helper_functions.py

@@ -3,6 +3,10 @@ import os
 import numpy as np
 from datetime import datetime
 import pandas as pd
+from src.utils.mail import Mail
+from config import Config
+
+config = vars(Config)
 
 def save_models(models, model_type, directory):
 
@@ -61,8 +65,21 @@ def save_parquet(dataframe, path):
 def load_parquet(path):
     return pd.read_parquet(path)
 
+def send_mail(**kwargs):
 
+    mail = Mail(config['MJ_APIKEY_PUBLIC'], config['MJ_APIKEY_PRIVATE'])
 
+    status = mail.send_mail(
+        fromName=kwargs.get('name'),
+        fromMail=kwargs.get('email'),
+        fromSubject=kwargs.get('subject'),
+        fromMsg=kwargs.get('message'),
+        dataframe=kwargs.get('dataframe'),
+        forecast_dates=(kwargs.get('forecast_start_date'),kwargs.get('forecast_end_date')),
+        toMail=kwargs.get('toMail')
+    )
 
+    if status == 200:
+        return True
     
-
+    return False

src/utils/mail.py

@@ -0,0 +1,62 @@
+from mailjet_rest import Client
+import base64
+import pandas as pd
+from io import BytesIO
+import datetime
+
+class Mail():
+
+    def __init__(self, api_key, api_secret):
+
+        self.api_key = api_key
+        self.api_secret = api_secret
+        self.mailjet = Client(auth=(self.api_key, self.api_secret), version='v3.1')
+
+    def send_mail(self, fromName, fromMail, fromSubject, fromMsg, dataframe, forecast_dates, toMail):
+
+        Subject = 'Predictions are ready! - Infineon Product Demand Forecasting System'
+        TextPart = f'Greetings from {Subject}'
+
+        with BytesIO() as output:
+            with pd.ExcelWriter(output, engine='xlsxwriter') as writer:
+                dataframe.to_excel(writer, sheet_name='Sheet1', index=False)
+            output.seek(0)
+            excel_content = output.read()
+
+        # Encode Excel content to base64
+        base64_content = base64.b64encode(excel_content).decode()
+
+        today = datetime.datetime.today().strftime("%d-%m-%Y")
+
+        data = {
+                'Messages': [
+                    {
+                    "From": {
+                        "Email": "[email protected]",
+                        "Name": "Me"
+                    },
+                    "To": [
+                        {
+                        "Email": toMail,
+                        "Name": "You"
+                        }
+                    ],
+                    "Subject": Subject,
+                    "TextPart": TextPart,
+                    "HTMLPart": f"Hello,<br/><br/>You can access the demand forecasting output for Infenion for the following dates <b>{forecast_dates[0]}</b> - <b>{forecast_dates[1]}</b> in the attachments<br/>If you have any problems, you can let us know via this e-mail address.<br/><br/>Have a good day,<br/><h3>Infineon AI Department</h3>",
+                    'Attachments': [
+                        {
+                            'ContentType': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet',
+                            'Filename': f'demand_predictions_{today}.xlsx',
+                            'Base64Content': base64_content
+                        }
+                    ]
+                    }
+                    
+                    
+                ]
+            }
+        
+        result = self.mailjet.send.create(data=data)
+        
+        return result.status_code