DEV Community: Suyash Srivastava

Learn Django through Inventory management system

Suyash Srivastava — Wed, 08 Jan 2025 21:33:43 +0000

About project

Youtube : Project Overview
Github : https://github.com/suyash-srivastava-dev/Inventory-Management

This project aims covers application with Database, models, Views, templates with CRUD functionality.

I have implemented an inventory management system using Django to efficiently manage products, stock levels, suppliers and sales. It supports crud operations for product and suppliers, facilitate stock management and enable tracking of sales order.

I have used django as a backend and for front-end it involves HTML CSS JavaScript with the django template that is jinja. For the database I have used mysql or sqlite. You can below settings for postgres & mysql.

# Postgres
DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.postgresql', 
        'NAME': 'your_database_name', 
        'USER': 'your_db_user', 
        'PASSWORD': 'your_db_password', 
        'HOST': 'localhost', 
        'PORT': '5432', 
    }
}

# MySQL
DATABASES = {
    'default': {
        'ENGINE': 'django.db.backends.mysql', 
        'NAME': 'your_database_name', 
        'USER': 'your_db_user', 
        'PASSWORD': 'your_db_password', 
        'HOST': 'localhost', 
        'PORT': '3306', 
    }
}

Database model parameters

product which consists of name description category price stock quantity and supplier
supplier table which contains name email phone number and address
sales order that contains product quantity total price sales data and status
stock movement that contains product quantity movement type movement date and notes

Models : inventory_management/models.py

Tasks

The application is allows you to add product ,list product, add supplier, list supplier, add stock movements ,create sales order, cancel sales order ,complete sales order, list sales order and stock level check.

Run project

Note: Recommended to use virtual environment for the application.

From Project

Install dependecy : pip install -r requirements.txt
Run the django application : python manage.py runserver
check project on http://localhost:8000/

From Docker

Build the application image : docker-compose build
Create container out of the image: docker-compose up -d
check project on http://localhost:8000/

Image Annotation for AI Model training using Pinata

Suyash Srivastava — Sun, 13 Oct 2024 12:51:09 +0000

This is a submission for the The Pinata Challenge

What I Built

I have built an image annotation application using :

FastAPI : Backend
Angular: Frontend
Pinata : Blob/File Storage

This application would help in doing the annotations of the image dataset. Then these annotations could be exported and be used for AI model training.

Demo

My Code

Flow Diagram

Pinata setup

Create an account with Pinata, and fetch the keys.
Install and setup .env files

npm i pinata

PINATA_API_KEY=""
PINATA_API_SECRET=""
PINATA_GATEWAY="*.mypinata.cloud"
PINATA_JWT=""

import { PinataSDK } from "pinata";

const pinata = new PinataSDK({
  pinataJwt: "PINATA_JWT",
  pinataGateway: "example-gateway.mypinata.cloud",
});

Create methods for Upload & Retrieve Files

Upload File

const file = new File(["hello"], "Testing.txt", { type: "text/plain" });
    const upload = await pinata.upload.file(file);
    console.log(upload);

Retrieve Files

const url = await pinata.gateways.createSignedURL({
        cid: "bafkreib4pqtikzdjlj4zigobmd63lig7u6oxlug24snlr6atjlmlza45dq",
        expires: 1800,
    })
    console.log(url)

Backend & Frontend Code Repo

backend Fastapi : https://github.com/suyash-srivastava-dev/annotation-editor-backend
frontend Angular : https://github.com/suyash-srivastava-dev/annotation-editor

More Details

Pinata group was created for each project in the application.
Pinata was used for saving the image dataset, with & without annotations. Also the annotation files are saved as JSON on Pinata. Access to the images & Json file is through the signed SDK.

Very Own bookmarks

Suyash Srivastava — Mon, 24 Jun 2024 06:43:30 +0000

This is a submission for Twilio Challenge v24.06.12

What I Built

Use Case: When scrolling through news articles, blog posts or youtube video. I often send WhatsApp messages to myself with important links I want to bookmark. However, finding the right link later can be challenging, as I have to sift through several sent links before locating the one I need. To solve this problem, I created an application.

This application accepts the links I share and provides a brief description of each one. This feature helps me quickly find the desired link when using the search option in WhatsApp.

Demo

Twilio and AI

I have taken into consideration the type of data that I share, that is generally either an article from web or a youtube video.

So the flow is as below.

Additional Prize Categories

Impactful Innovators: Though it's a simple application but it solves a major problem of finding right content that was bookmarked by the user.