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Also Read: How AI Content Creation is Revolutionizing the Future of Content Marketing!
Let’s create a python code to clear gmail inbox with AI. We will be taking ChatGPT’s help for code generation.
It’s essential to ensure that Python is correctly installed on your system before we proceed with creating the Gmail data extraction program. Follow these steps to verify or install Python on your Mac:
For Mac
To check if Python is already installed on your Mac, open the Terminal application and use the “python –version” or “python3 –version” command. If Python is installed, it will display the version number; otherwise, you can proceed to download Python from the official Python website. After downloading the installer (.pkg), double-click on it and follow the on-screen instructions to complete the installation. To verify the installation, open a new Terminal window and use the “python –version” or “python3 –version” command.
For Windows
The installation process for Python on Windows is similar to that on Mac. Visit the official Python website and download the installer, making sure to check the box that says “Add Python to PATH” during the installation. This step is important for easy access to Python from the Command Prompt. After installation, you can verify it by opening the Command Prompt and using the “python –version” or “python3 –version” command.
Once you have Python successfully installed and verified, please let me know so that we can proceed with creating the Gmail data extraction program.
To ensure the security of your Gmail account while using the application we’ll be creating, it’s advisable to generate an app-specific password. Here are the steps to generate an app password for your Gmail account:
Please make sure to keep this app-specific password safe, as it’s specific to the application and device for which it was generated. If you ever change devices or no longer use the app, you can revoke this password and generate a new one following the same steps.
We’ll utilize ChatGPT to assist us in crafting Python code that retrieves our email data in an Excel format. To ensure the accuracy of ChatGPT’s responses, we’ll follow the following process:
Prompt: “Assume the role of an expert software engineer who is an expert in Python and Gmail, who will always write correct code by analyzing all of our errors in this chat. Give this coder a name and whenever I issue a request like: Hey <name> <request>. You will assume the role of this coder and strive to write bug-free perfect code.“
ChatGPT’s Response: “Sure! In this scenario, you can call me ‘Alex.’ Whenever you start a request with ‘Hey Alex,’ I will act as the coder and work diligently to provide you with flawless, bug-free code. Please feel free to proceed with your requests!”
Prompt: “Hey Alex! I want you to write a program in Python that will access my Gmail account, and extract the sender, email id, email date, and total attachment size. It will also give me the progress of the operation and the estimated time of completion. Whenever it will find an error, it will stop the operation, give me the error clearly and save the progress which will restart once the error is cleared by me and once the entire process is complete, it will give me an Excel file with this data. Also, give me step-by-step instructions to run this code.”
Recognizing that ChatGPT may not be flawless, we acknowledge that running the program might result in errors. In such instances, we’ll promptly copy and paste the error message into the chat and request “Alex” to provide us with an improved, error-free version of the code. This iterative approach ensures that we steadily refine and enhance the program until it meets our requirements.
By adhering to this structured process, we aim to collaboratively develop a robust Python program for Gmail data extraction, enhancing its functionality with each interaction
After multiple iterations, the final code will look like this:
import imaplib
import email
import datetime
import openpyxl
# IMAP Configuration
IMAP_SERVER = 'imap.gmail.com'
IMAP_PORT = 993
# Email Account Configuration
EMAIL_USERNAME = '[email protected]'
EMAIL_PASSWORD = 'password'
# Excel Configuration
EXCEL_FILENAME = 'email_data.xlsx'
EXCEL_SHEETNAME = 'Emails'
# Progress Tracking Configuration
BATCH_SIZE = 100
# Connect to the IMAP server
imap_server = imaplib.IMAP4_SSL(IMAP_SERVER, IMAP_PORT)
imap_server.login(EMAIL_USERNAME, EMAIL_PASSWORD)
imap_server.select('INBOX')
# Retrieve email UIDs
status, response = imap_server.uid('search', None, 'ALL')
email_uids = response[0].split()
# Total number of emails
total_emails = len(email_uids)
# Create a workbook and sheet
wb = openpyxl.Workbook()
ws = wb.active
ws.title = EXCEL_SHEETNAME
# Excel header row
header = ['Email ID', 'Sender', 'Subject', 'Date', 'Attachment Names', 'Attachment Sizes']
ws.append(header)
# Progress tracking variables
processed_emails = 0
progress = 0
# Process emails in batches
while processed_emails < total_emails:
email_batch = email_uids[processed_emails:processed_emails+BATCH_SIZE]
for email_uid in email_batch:
try:
email_response = imap_server.uid('fetch', email_uid, '(RFC822)')
if email_response[0] == 'OK':
email_data = email_response[1][0][1]
email_msg = email.message_from_bytes(email_data)
email_id = email_msg['Message-ID'] or f'No Message-ID ({email_uid.decode()})'
sender = email_msg['From']
subject_bytes = email_msg['Subject']
# Ensure subject_bytes is of type bytes
if isinstance(subject_bytes, bytes):
subject = subject_bytes.decode('utf-8', 'replace')
else:
subject = str(subject_bytes)
date = email_msg['Date']
# Process email attachments
attachment_names = []
attachment_sizes = []
for part in email_msg.walk():
content_type = part.get_content_type()
if content_type and 'application' in content_type:
attachment_names.append(part.get_filename())
attachment_sizes.append(len(part.get_payload(decode=True)))
# Add email data to the Excel sheet
row = [email_id, sender, subject, date, ', '.join(attachment_names), ', '.join(map(str, attachment_sizes))]
ws.append(row)
# Update progress
processed_emails += 1
progress = processed_emails / total_emails * 100
print(f"Progress: {processed_emails}/{total_emails} ({progress:.2f}%)")
except Exception as e:
# Log the error and continue processing
print(f"Error processing email: {email_uid.decode()}\n{str(e)}")
# Save the workbook after processing each batch
wb.save(EXCEL_FILENAME)
# Close the IMAP connection
imap_server.close()
imap_server.logout()
# Save the final Excel file
wb.save(EXCEL_FILENAME)
print("Email processing completed. Excel file saved.")
# End of code
In the age of digital communication overload, managing a Gmail inbox can be overwhelming. Fortunately, AI-powered tools like Clean.Email, Mailstrom, Unroll.me, Cleanfox, and Trimbox.io have emerged as powerful allies. These tools employ AI to simplify email management, unsubscribe from newsletters, and maintain inbox cleanliness.
They enhance productivity with features like one-click unsubscribing, email bundling, and spam blocking. Moreover, they work seamlessly with various email providers, ensuring accessibility. To delve deeper into AI, consider joining Analytics Vidhya’s Gen AI program, a gateway to advancing AI skills and conquering email clutter.
A. Yes, there are several AI tools that can help you clear your gmail inbox. Some of them are
Clean.email, Mailstrom, Unroll.me, Cleanfox, Triage, Trimbox.io and SubscriptionZero.
A. AI email management automates responses, saves time, and maintains a clean inbox, letting you focus on important messages.
A. To swiftly clean up your Gmail inbox, utilize the search bar to filter emails by type or date, select all, and click “Delete.” Regularly unsubscribe from unnecessary newsletters and spam to maintain a clean inbox.