Category Archives: Python Projects

Online Loan management system project in Python Django

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Buy Project Code ₹701

A loan management application built with Django, SQLite3, JavaScript, HTML, CSS, and Bootstrap 5. The system enables customers to request loans after registration, with admin approval. Customers can make monthly loan payments, and both customers and admins have dedicated dashboards.

Features

 

  1. User Registration: Customers must register before requesting loans.

  2. Loan Requests: Customers can request loans, pending admin approval.

  3. Admin Approval: Admins can approve or reject customer loan requests.

  4. Loan Payments: Customers can make monthly loan payments.

  5. Dashboards: Both customers and admins have access to dedicated dashboards.

Usage

 

  1. Register as a customer to request loans.
  2. Admins approve or reject loan requests in the admin dashboard.
  3. Customers can make monthly loan payments through the application.
  4. Both customers and admins have dashboards for efficient management.

Django Installation Steps :-

  1. Install Python 3.8
  2. Install all dependencies cmd -python -m pip install --user -r requirements.txt
  3. Finally run cmd - python manage.py runserver

 

A simple Caterpillar game built in python mini project with source code

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an overview of the development and implementation of a simple Caterpillar game in Python. The game is designed to be a fun and interactive way for users to play a classic snake-like game where they control a caterpillar and navigate it around the screen to eat food and grow in length.

Objectives

The main objectives of the project are as follows:

  1. Develop a simple and easy-to-understand game using Python.
  2. Implement basic game mechanics such as user input, movement, collision detection, and score tracking.
  3. Create an interactive graphical user interface (GUI) using the Tkinter library.
  4. Enhance user experience by adding sound effects and visual feedback.

Technologies Used

  1. Python programming language
  2. Tkinter library for GUI development
  3. Pygame library for sound effects
  4. IDE (Integrated Development Environment) such as Visual Studio Code or PyCharm

Game Description

The Caterpillar game consists of the following elements:

  1. Caterpillar: The main character controlled by the player.
  2. Food: Appearing randomly on the screen for the caterpillar to eat and grow.
  3. Obstacles: Static objects that the caterpillar must avoid colliding with.
  4. Score: Keeping track of the player's progress.
  5. Game Over: Triggered when the caterpillar collides with an obstacle or itself.

## 🌟 How to run
Running the script is really simple! Just open a terminal in the folder where your script is located and run the following command:

```command
python Caterpillar.py

Download Link

Online Hotel Reservation System Project in Python Django

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Buy Project Code ₹701

Buy Project Report ₹501

The Hotel Reservation System developed using Django is a web-based application designed to streamline the process of booking hotel rooms for guests. It provides a user-friendly interface for both guests and hotel administrators to manage room reservations efficiently.

In the bustling hospitality industry, efficient management of hotel reservations is paramount for ensuring guest satisfaction and maximizing revenue. The Hotel Reservation System developed using Django addresses this need by providing a comprehensive solution for streamlining the booking process.

In today's digital era, guests increasingly prefer the convenience of booking accommodations online. Thus, our system aims to meet this demand by offering a user-friendly web-based platform where guests can effortlessly browse available rooms, make reservations, and manage their bookings from the comfort of their homes or on the go.

For hotel administrators, the system offers robust tools for managing room inventory, tracking reservations, and optimizing occupancy rates. With intuitive features and real-time updates, hotel staff can efficiently handle bookings, ensuring a smooth and seamless experience for both guests and staff alike.

By leveraging the power of Django, a high-level Python web framework known for its scalability, security, and rapid development capabilities, our Hotel Reservation System delivers a reliable and feature-rich solution tailored to the needs of modern hotels and their guests.

Throughout this project report, we will delve into the system's architecture, functionalities, implementation details, and future enhancements, providing a comprehensive overview of how the Hotel Reservation System revolutionizes the way hotels manage bookings and enhance guest experiences.

A web application to manage a hotel. It contains the following features.

  1. Search rooms with check in , check out, room type.
  2. View all rooms, categorywise
  3. Add room to the wishlist
  4. Booking rooms
  5. Sign up, Sign in, profile update.
  6. Booking history.

Technology Used in the project  

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. SQLite : SQLite database has been used as database for the project
  7. Django : Project has been developed over the Django Framework

Supported Operating System

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 3.8, PIP, Django.
  4. Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Project on Django Installation Steps :-

  1. Install Python 3.8
  2. Install Django version 3.1
  3. Install all dependencies cmd -python -m pip install --user -r requirements.txt
  4. Finally run cmd - python manage.py runserver

Online Pizza Ordering System in Python Django

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Buy Source Code ₹701

Welcome to our Online Pizza Ordering System, where you can satisfy your pizza cravings with just a few clicks! This system is designed to streamline the pizza ordering process, offering a user-friendly interface for customers and efficient order management for administrators.

Features:

Pizza Menu:

  • Explore our diverse pizza menu featuring a variety of mouth-watering options. Each pizza comes with a detailed description and price, making it easy for users to choose their favorite flavors.

Order Placement:

  • With a simple click, users can place their pizza orders directly from the menu. The system records the selected pizza, generates a unique order ID, and timestamps the order placement.

Order Status Tracking:

  • Keep tabs on your pizza order with our real-time order status tracking. Users can visit the "Order Status" section, enter their order ID, and view essential information such as the pizza details, order timestamp, and whether the order is completed or pending.

Admin Panel:

  •  The system empowers administrators with a dedicated admin panel to efficiently manage incoming orders. Admins can mark orders as completed and maintain an organized view of both completed and pending orders.

How to Use:

Explore the Menu:

  •  Visit the "Pizza Menu" section to explore our delightful pizza options.
  •  Each pizza is accompanied by its name, description, and price.

Place Your Order:

  •  Click on the "Order" link next to your preferred pizza to initiate the order placement process.
  • Your order is assigned a unique ID, and the system records the timestamp.

Track Your Order:

  • Navigate to the "Order Status" section.
  •  Enter your order ID to retrieve real-time updates on your pizza order, including its current status.

Admin Functions:

  • Admins can access the admin panel to view and manage all incoming orders.
  •  Mark orders as "Completed" once they are ready for delivery or pickup.

Technology Used in the project

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. SQLite : SQLite database has been used as database for the project
  7. Django : Project has been developed over the Django Framework

Supported Operating System

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 2.7, PIP, Django.
  4. Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Project on Django Installation Steps :-

  1. Install Python 3.7 Or Higher
  2. Install Django version 2.2.0
  3. Install all dependencies cmd -python -m pip install --user -r requirements.txt
  4. Finally run cmd - python manage.py runserver

Doctors Appointment System Django Project with source code

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Buy Source Code ₹501

The doctor appointment booking website project aimed to create a user-friendly platform for scheduling medical appointments efficiently. Leveraging modern web technologies such as HTML, CSS, JavaScript, and Django, the website offers a seamless experience for both patients and healthcare providers.

A website built using Django, HTML, CSS and JavaScript that enables booking an appointment with a doctor easily.

It features three modules: Admin Module, Doctor Module, Patient Module

A. The Admin Module

  1. Log In
  2. Verify and approve the patient and doctor accounts created.
  3. View the details of the patient as well as the doctor.
  4. Confirm the appointments booked by the patient.
  5. Generate an Invoice.

B. The Doctor Module

  1. Log In/Sign Up
  2. View the details of the patient (symptoms, name, mobile) assigned to them by admin.
  3. View their Appointments, booked by admin.

C. The Patient Module

  1. Log In/Sign Up
  2. View assigned doctor's details like (specialization, mobile number).
  3. View their booked appointment status (pending/confirmed) by admin.
  4. Book appointments.
  5. View/download Invoice pdf.

Technology Used in the project

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. SQLite : SQLite database has been used as database for the project
  7. Django : Project has been developed over the Django Framework

Django Installation Steps :-

  1. Install Python 3.10 Or Higher
  2. Install all dependencies cmd -python -m pip install  -r requirements.txt --user
  3. Finally run cmd - python manage.py runserver

Blog Website Project Using Python Django Project

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The project aimed to develop a fully functional blog website using the Django web framework. Key features included user authentication, CRUD operations for managing blog posts, a commenting system, rich text editing capabilities, responsive design, and pagination. By leveraging Python, Django, HTML/CSS, and SQLite, the project provided valuable insights into web development. Future improvements were suggested, such as implementing search functionality, categories and tags, social media integration, security enhancements, and performance optimization. Overall, the project offered hands-on experience in building dynamic web applications with Django, empowering users to share their ideas and stories effectively.

Features:

  1. User Authentication: Registration, login, and logout functionalities.
  2. CRUD Operations: Users can create, read, update, and delete blog posts.
  3. Commenting System: Users can comment on posts.
  4. Responsive Design: Ensured the website is accessible across devices.
  5. Pagination: Implemented pagination for listing posts.
  6. Blogs are updated and deleted only by author of that blog.
  7. Profile is only changed by logging user.

Technology Used in the project

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. SQLite : SQLite database has been used as database for the project
  7. Django : Project has been developed over the Django Framework

Supported Operating System

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 3.10, PIP, Django.
  4. Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Project on Django Installation Steps :-

  1. Install Python 3.10
  2. Install Django version 4.1.6
  3. Install all dependencies cmd -python -m pip install --user -r requirements.txt
  4. Finally run cmd - python manage.py runserver

Download Link

Online Taxi Booking Python Django with Real time Map

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Buy Now ₹6501

An online taxi booking Python Django project is a web-based application that allows users to book a taxi ride online through a user-friendly interface. The application integrates with real-time maps to show the location of available taxis and their estimated arrival times.

The project involves designing a database using Django's built-in ORM to store user and ride data. The application's frontend is created using HTML, CSS, and JavaScript to provide an interactive user interface for booking rides, tracking ride progress, and paying for rides.

The Python code interacts with the database to retrieve user data, such as name, email, and payment information, and with real-time map APIs to display the location of available taxis and their estimated arrival times. It uses algorithms to match user requests with available taxis, manage ride progress, and calculate fare amounts.

Some key features of an online taxi booking Python Django project may include:

  1. User registration and login
  2. Ride booking and tracking
  3. Real-time map integration
  4. Payment processing and receipt generation
  5. Ride history and user reviews
  6. Driver and vehicle management
  7. Ride cancellation and refund management
  8. Mobile app integration

Overall, an online taxi booking Python Django project provides a convenient and user-friendly way for users to book and track taxi rides, while providing drivers with a simple way to manage their bookings and pickups. The real-time map integration helps to minimize wait times and improve the overall user experience.

Technology Used in the project :-

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. Django: Project has been developed over the Django Framework

Supported Operating System :-

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 3.7.0, PIP, Django.
  4. Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Installation Step : -

  1. python 3.6.8
  2. command 1 - python -m pip install --user -r requirements.txt
  3. command 2 - python manage.py runserver

Crop Recommendation using Random Forest flask web app

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Buy Now ₹1501

Buy Now Project Report ₹1001

The Crop Recommendation Flask Web App is a web application that recommends the best crop to grow based on soil and climate conditions. The project involves building a machine learning model that can predict the crop yield based on several parameters such as soil pH, temperature, rainfall, humidity, and crop type. The machine learning model is then integrated into a Flask web application to provide farmers with a simple and easy-to-use tool for crop selection.

Here's a general overview of the project:

  1. Data collection: Collect soil and climate data from reliable sources such as the National Soil Information System and the National Oceanic and Atmospheric Administration (NOAA).
  2. Data preprocessing: Clean and prepare the data for use in the machine learning model.
  3. Feature selection: Select the most important features that can affect the crop yield, such as soil pH, temperature, rainfall, humidity, and crop type.
  4. Model training: Train a machine learning model using the preprocessed data and the selected features.
  5. Model evaluation: Evaluate the performance of the machine learning model to ensure it can accurately predict the crop yield.
  6. Flask app development: Develop a Flask web application that allows users to input soil and climate parameters and get a recommendation for the best crop to grow.
  7. Deployment: Deploy the web application to a server so that it can be accessed by users.

Overall, the Crop Recommendation Flask Web App project can be a valuable tool for farmers to increase their crop yield and improve their farming practices.

 Algorithm :

  1. *Random Forest Classifier* is used for development of model.
  2. Only three algorithms are used to predict the output. They are *Logistic Regression*, *XGBoost* and *Random Forest*.\
    1. Accuracy of the model using Logistic Regression is 95%.
    2. Accuracy of the model using Random Forest Classifier is 99%.
    3. Accuracy of the model using XGBoost Classifier is 99%.

Technology Used in the project :-

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. Flask: Project has been developed over the Flask Framework

Supported Operating System :-

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 3.6.10, PIP, Django.
  4. Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Installation Step : -

  1. python 3.6.8
  2. command 1 - python -m pip install --user -r requirements.txt
  3. command 2 - python app.py

Fire Detection Using Surveillence Camera web app Project with Source Code

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Buy Now ₹1501

Introduction:

The objective of this project is to develop a web application that uses surveillance cameras to detect fire and alert users in real-time. The application uses computer vision algorithms and machine learning techniques to analyze video footage from the cameras and detect the presence of fire. The project aims to improve fire safety by detecting potential fire hazards early and allowing users to take appropriate action.

Methods:

The project involved several steps, including collecting and labeling a dataset of video footage that contained both fire and non-fire events, preprocessing the video footage to extract individual frames, and training a machine learning model using the preprocessed dataset. The machine learning model was a convolutional neural network (CNN) that was trained to detect the presence of fire in an image.

Once the machine learning model was trained, a web application was developed that allowed users to upload video footage from their surveillance cameras. The uploaded footage was analyzed frame by frame using the trained machine learning model to detect the presence of fire. If fire was detected, the application triggered an alert and notified the user via email or SMS. The application also provided a live video feed from the surveillance camera and highlighted the region where the fire was detected.

Results:

The developed web application was able to accurately detect the presence of fire in video footage from surveillance cameras. The machine learning model achieved an accuracy of over 95% on the test dataset, indicating that it was able to accurately distinguish between fire and non-fire events. The web application was also able to provide real-time alerts and notifications to users when fire was detected, allowing them to take appropriate action.

Discussion:

The developed web application has several potential applications in improving fire safety in buildings. For example, it can be used in warehouses, factories, and other industrial settings where fire hazards are common. The application can also be used in homes and other residential settings, alerting residents to potential fire hazards in real-time.

The project has several limitations that should be considered. One limitation is the need for high-quality video footage from surveillance cameras. The accuracy of the machine learning model is highly dependent on the quality of the video footage. Another limitation is the need for periodic retraining of the machine learning model to ensure that it continues to accurately detect fire over time.

Conclusion:

The project has demonstrated the feasibility of using surveillance cameras and machine learning algorithms to develop a web application for fire detection. The application has the potential to improve fire safety in various settings, including industrial and residential settings. Further research is needed to optimize the accuracy of the machine learning model and to develop additional features that can enhance the functionality of the application.

Technology Used in the project :-

  1. We have developed this project using the below technology
  2. HTML : Page layout has been designed in HTML
  3. CSS : CSS has been used for all the desigining part
  4. JavaScript : All the validation task and animations has been developed by JavaScript
  5. Python : All the business logic has been implemented in Python
  6. Flask: Project has been developed over the Flask Framework

Supported Operating System :-

  1. We can configure this project on following operating system.
  2. Windows : This project can easily be configured on windows operating system. For running this project on Windows system, you will have to install
  3. Python 3.6.10, PIP, Django.
  4. Linux : We can run this project also on all versions of Linux operating systemMac : We can also easily configured this project on Mac operating system.

Installation Step : -

  1. python 3.6.8
  2. command 1 - python -m pip install --user -r requirements.txt
  3. command 2 - python app.py