An inventory management application for a shop to keep the track of its products data. It uses Redis as its primary database, Flask as the backend that connects with Redis, and React as the frontend that renders the data on the browser.

hardWareHouse Inventory Dashboard

Way to Add a new Product

Way to Update any Product

Search a Product and the table will render accordingly

Here's a short video that explains the project and how it uses Redis:

• Database: Redis
• Backend: Flask
• Frontend: React

• From redis_om module, following are used to create the Product schema:

  • JsonModel
  • Field

• The product data is stored in various keys and various data types.

  • product_name: str
  • product_desc: str
  • price: PositiveInt
  • units: PositiveInt
  • lower_limit_stock: PositiveInt
  • timestamp: datetime

from redis_om import Field, JsonModel
from pydantic import PositiveInt
from datetime import datetime
# Added Product Schema


class Product(JsonModel):

    product_name: str = Field(index=True, full_text_search=True)
    product_desc: str = Field(index=True)
    price: PositiveInt = Field(index=True)
    units: PositiveInt = Field(index=True)
    lower_limit_stock: PositiveInt = Field(index=True)
    timestamp: datetime = Field(index=True, default=datetime.now())

Way to Add a new Product

• When user clicks on the Add Product button on the dashboard, the addProduct method triggers the following POST request from the frontend.

  const addProduct = async (product_name, product_desc, price, units, lower_limit_stock) => {
    // POST API Call
    try {
      const url = `${host}/product/new`;
      const response = await fetch(url, {
        method: "POST",
        headers: {
          "Content-Type": "application/json",
        },

        body: JSON.stringify({
          product_name,
          product_desc,
          price: parseInt(price),
          units: parseInt(units),
          lower_limit_stock: parseInt(lower_limit_stock),
        }),
      });
      const json = await response.json();
    } catch (error) {
      console.error(error);
    }
  };

• This invokes the create_product() method in the backend that handles the POST request. It performs the relevant validations and then saves the data in the database.

@app.route("/product/new", methods=["POST"])
def create_product():
    try:
        print(request.json)
        new_product = Product(**request.json)
        new_product.save()
        return json.dumps(new_product.pk)

    except ValidationError as e:
        print(e)
        return "Bad request.", 400

• The product update also follows the similar pattern.

• Sample data stored: Key Name: :product.Product:01G9W6KP7S4K3DS3BRD5AEREDX

{
pk: "01G9VZ5C9PPXF3WYYB7JYN8WAR",
product_name: "Mechanical Keyboard",
product_desc: "Built for extensive typing",
price: 8250,
units: 23,
lower_limit_stock: 5,
timestamp: "2022-08-07T16:25:04.834860",
}

• The GET request is initiated from the frontend.

   const getAllProducts = async () => {
    try {
      const url = `${host}/product/fetchall/`;
      const response = await fetch(url, {
        method: "GET",
        headers: {
          "Content-Type": "application/json",
        },
      });
      const json = await response.json();
    } catch (error) {
      console.error(error);
    }
  };

• This invokes the fetch_all_products() method in the backend that handles the GET request. It sorts the data by timestamp in descending order and returns an array of fetched products.

@app.route("/product/fetchall/", methods=["GET"])
def fetch_all_products():
    products = Product.find().sort_by("-timestamp").all()
    return build_results(products)

• Python - v3.8.5
• Docker - v20.10.17
• Nodejs - v8.11.0

1. Clone the repository from github

git clone https://github.com/pranavarora1895/hardWareHouseInventory.git

2. Server Side: Make sure your docker is up and running. Go to hardWareHouseInventory\hardWareHouseInventory\ folder and then:

# Go to server side
cd .\hardWareHouseInventory\hardWareHouseInventory\

# Get redis image
docker compose up -d

# Create virtual env
python -m venv venv

# Activate env for powershell
.\venv\Scripts\Activate.ps1

# Install dependencies
pip install -r requirements.txt

# Run server
flask run

3. To load some sample data, run productsloader.py script in the hardWareHouseInventory\hardWareHouseInventory\ folder:

# Open a new PowerShell window
cd .\hardWareHouseInventory\hardWareHouseInventory\

.\venv\Scripts\Activate.ps1

python .\productsloader.py

# After loading the products, you can close that powershell window

4. Client Side: Go to hardWareHouseInventory\hardwarehouse-dashboard\ folder and then:

# Open another powershell window
cd .\hardWareHouseInventory\hardwarehouse-dashboard\

# Install dependencies
npm install

# Start the client server
npm run start