ParthJohri / DTUSiteBot

The Subject Registration Bot is a Python automation tool designed to streamline the process of subject registration on a website. Using Selenium WebDriver, the bot automates the login process, selects subjects based on provided codes, and completes the subject registration process.

🚀 DTUSiteBot - A Subject Registration Bot

This is a Python bot that automates the process of subject registration on a website. It uses Selenium WebDriver to interact with the website and perform the registration. The bot reads subject codes and credentials from text files, allowing you to easily registers you for the subject.

Installation

1. Clone the repository:

   git clone https://github.com/ParthJohri/DTUSiteBot.git

2. Navigate to the project directory:

   cd DTUSiteBot

3. Install the required dependencies:

   pip install selenium

Configuration

1. Update subjects.txt file:

   Open the subjects.txt file and replace the existing subject codes with your desired subject codes. Each subject code should be on a new line.

2. Update credentials.txt file:

   Open the credentials.txt file and replace the existing credentials with your own. The file should contain your username on the first line and your password on the second line.

Usage

1. Make sure you are in the project directory.

2. Run the bot:

   python main.py or python3 main.py

   The bot will start the subject registration process using the provided subject codes and credentials. It will log any errors or notifications to a log file in the logs directory, therefore create a logs folder in the directory.

3. Monitor the bot:

   You can monitor the bot's progress by checking the log file generated in the logs directory. The log file will provide information about any errors encountered during the registration process.

4. Customize the bot:

   If you want to modify the behavior of the bot or add additional features, you can edit the main.py file. Make sure to test your changes thoroughly before running the bot.

Run with Docker

You can run this project using Docker. Make sure you have Docker installed on your machine.

Step 1: Build the Docker Image

Open a terminal, navigate to the root folder of the project, and run the following command to build the Docker image:

docker build -t your_docker_image:your_tag .

Replace your_docker_image:your_tag with the desired image name and tag.

Step 2: Run the Docker Container

After successfully building the Docker image, run the following command to start the Docker container:

docker run -it --rm your_docker_image:your_tag

Replace your_docker_image:your_tag with the same image name and tag used during the build.