SneakerHunt

• A website for sneakerheads where you can search for the best price of your favourite sneaker over the internet

1. Implemented a web-scraper that extracts data from prominent sneaker selling websites.

2. Currently integrated 3 websites namely Superkicks.in, VegNonVeg.com, Nike.com. Keeping the project open for contributions for more websites integration.

3. Integrated a scheduler batch file that runs the scraper on scheduled intervals to update the present data in the database.

4. Information regarding APIs & usage given below.

Tech Stack Used:

1. JavaScript
2. Python
3. Node.js
4. Express.js
5. MongoDB
6. BeautifulSoup
7. Selenium

High Level Design:

1. Simple high level design of the project and its working.

Installation & Setup:

1. Clone the repository locally:

git clone https://github.com/SCube27/SneakerHunt.git

2. Install the dependencies:

npm install

3. Install python libraries:

pip install -r requirements.txt

4. Start the server:

npm run dev

Configurations:

1. Refer the template.env and setup a .env file accordingly for the required environment variables for the project.

APIs (Endpoints) & Usage:

Sneaker Data APIs

1. Get the Sneaker Data:

   • API: localhost:<PORT>/api/v1/sneakers/
   • Req Type: POST
   • Requires: Reqest Body with Sneaker Name String
   • Response:

     // Dummy Response
     [
         {
             name: sneaker name (string),
             price: price of sneaker (number),
             link: url to buy the sneaker (string),
             image: image url (string)  
         },
     ]
     

2. Update Sneaker Data in DB: (Not for users to access)

   • API: localhost:<PORT>/api/v1/sneakers/update_details
   • Req Type: PATCH
   • Requires: No requirement
   • Response:

     {
         success: true,
         message: "updated the data successfully"
     }
     

Auth User APIs

1. Sign Up User:

   • API: localhost:<PORT>/api/v1/auth/signup
   • Req Type: POST
   • Requires: Request body with username, email and password of user
   • Response:

     {
         username: username of the signed up user,
         email: email of the user
     }
     

2. Log In User:

   • API: localhost:<PORT>/api/v1/auth/login
   • Req Type: POST
   • Requires: Request body with username and password of user
   • Response:

     {
         username: username of the signed up user,
         email: email of the user
     }
     

3. Log Out User:

   • API: localhost:<PORT>/api/v1/auth/logout
   • Req Type: POST
   • Requires: No requirements
   • Response:

     {
         message: "Logged Out Successfully"
     }
     

[NOTE] The update sneaker data API is used by the scheduler file to update the sneaker data, its not suppose to be accessed on client side.

Setting Up Automation:

• To automate the collection of prices from this software simply run the scheduler/main.py file at your desired increment while the python flask backend is running.

Windows

• I have created a simple .bat script called win.bat that you can schedule to execute using the Windows Task Scheduler that will automatically run the backend api and send the appropriate request to it.

Contributions:

• The project is open for contribution according to the issues present in the issues tab.