The problem Apna Bazaar solves

To make this the most efficient(All-in-one) app for the citizens of Atmanirbhar Bharat, we have taken into account several major issues faced by us in general. The Features include:

• Pre-order the items from the vendors as your wish. Just visit the marketplace and get your orders without any delay.
• If something is wanted in particular, just search the marketplace online. The vendors having the product would be listed on the go.
• Login and get the monthly/weekly based sales/expenditure analysis based on your data. Say goodbye to handwritten hassles!
• No food will be wasted. With the added relisting feature, vendors can bid farewell to all the losses incurred by wastage.
• Never forget to buy whatever you need.
• Avoid delays and waiting in the shops and thereby prevent unnecessary crowds.
• Equitable system which cares about both the buyers and the vendors
• A working login and logout user functionality with secured password hashing in the database to encrypt user details.
• Authorization for protecting the routes so that a person can't access the other route(using JWT)

With quite a simple, yet an eye-soothing UI and loads of features to aid both the vendors and the users.

The fact is this is a potential long-lasting idea. Fish and vegetable market is an integral part of Indian customs and traditions. With Indian markets and stores not disappearing/dissolving anytime soon. So we can’t envision this product getting out of favour anytime soon.

So, this product can be helpful for years from now.

Our product, if implemented successfully, can emerge as true winners for digitaliizing the Indian Markets and serving the needs of both the buyers and the vendors.

Challenges we ran into

• We had some difficulties in integrating the APIs(deployed in our backend,hosted on HEROKU), while connecting it to the frontend of our web app. But at the end, we managed to rectify our errors and integrate it successfully.
• We had a glitch in our database which restricted data to be entered from our frontend. But we managed to overcome it in a day.
• While making the dataframe, we had a few problems linking Pymongo to the MongoDB Atlas.Soon, we managed to solve this as well.