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File size: 2,434 Bytes
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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": "alper.tml.14@hotmail.com",
"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 |