Python menu Automation

In this python program menu, we have these following options,

We can use the following options to configure an apache web server, install basic protocols like ssh, net-tools, vim, HTTP, etc..

We have kept all these features in a docker image, so if any user wants to use these features they can just download the docker image and run it.

Docker image is shashwatapp/drkmenu:latest from the docker hub. To install an image into your system we can use docker pull <image name>.

This completes one menu another menu is,

Next, we have also automated some functionalities,

Here are some functionalities: -

· To send an email

· To run an ML code

· To send WhatsApp message

#1 To send an email

1. First of all, in order to send an email, we have to configure the security setting of the account

2. As you can see in the below mention code that we write a python script to send an email which takes arguments for:-

· Recipient email

· Sender’s email

· Sender’s password

· Subject for the email

· Text /Message

3. In the below we can clearly see the output the email has been sent successfully.

4. Here is the screenshot of that email

#2 To run an ML code

1. In order to run an ML code, we have trained one ML model to predict the salary w.r.t work experience.

2. We have attached one CSV file which contains a dataset for the model.

3. This model takes a year of work experience as an argument and predict the salary of the employee.

4. Here is the predicted output

#3 To send a WhatsApp Message

  1. In order to send the message, we have integrated python and HTML files.

2. We are able to so by using a python library named as the web browser

Ps:-

You can install this library by using this command:-

pip install pycopy-webbrowser

At last, we have automated AWS and Hadoop which can be seen in the GitHub repository.

Thank you for reaching this point. I would like to thank all my teammates for their contributions and support.

  1. Shashwat
  2. Rudr Tapish
  3. mitri
  4. Sabitha konam

GitHub link: → https://github.com/shashwat052000/TEAM_TASK8

Thank you

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