export const metadata = { title: ${pageNumber} Seed Data with Custom CLI Script, }

{metadata.title}

In this chapter, you'll learn how to seed data using a custom CLI script.

How to Seed Data

To seed dummy data for development or demo purposes, use a custom CLI script.

In the CLI script, use your custom workflows or Medusa's existing workflows, which you can browse in this reference, to seed data.

Example: Seed Dummy Products

In this section, you'll follow an example of creating a custom CLI script that seeds fifty dummy products.

First, install the Faker library to generate random data in your script:

bash

npm install --save-dev @faker-js/faker

Then, create the file src/scripts/demo-products.ts with the following content:

export const highlights = [ ["16", "salesChannelModuleService", "Resolve the Sales Channel Module's service."], ["19", "logger", "Resolve the logger to log messages in the terminal."], ["22", "query", "Resolve Query to retrieve data later."], ["26", "defaultSalesChannel", "Retrieve the default sales channel to associate products with."], ["31", "sizeOptions", "Declare the size options to be used in the products' variants."], ["32", "colorOptions", "Declare the color options to be used in the products' variants."], ["33", "currency_code", "Declare the currency code to use in products' prices."], ["34", "productsNum", "The number of products to seed."] ]

import { ExecArgs } from "@medusajs/framework/types"
import { faker } from "@faker-js/faker"
import { 
  ContainerRegistrationKeys, 
  Modules, 
  ProductStatus,
} from "@medusajs/framework/utils"
import { 
  createInventoryLevelsWorkflow,
  createProductsWorkflow,
} from "@medusajs/medusa/core-flows"

export default async function seedDummyProducts({
  container,
}: ExecArgs) {
  const salesChannelModuleService = container.resolve(
    Modules.SALES_CHANNEL
  )
  const logger = container.resolve(
    ContainerRegistrationKeys.LOGGER
  )
  const query = container.resolve(
    ContainerRegistrationKeys.QUERY
  )

  const defaultSalesChannel = await salesChannelModuleService
    .listSalesChannels({
      name: "Default Sales Channel",
    })

  const sizeOptions = ["S", "M", "L", "XL"]
  const colorOptions = ["Black", "White"]
  const currency_code = "eur"
  const productsNum = 50

  // TODO seed products
}

So far, in the script, you:

Resolve the Sales Channel Module's service to retrieve the application's default sales channel. This is the sales channel the dummy products will be available in.
Resolve the Logger to log messages in the terminal, and Query to later retrieve data useful for the seeded products.
Initialize some default data to use when seeding the products next.

Next, replace the TODO with the following:

const productsData = new Array(productsNum).fill(0).map((_, index) => {
  const title = faker.commerce.product() + "_" + index
  return {
    title,
    is_giftcard: false,
    description: faker.commerce.productDescription(),
    status: ProductStatus.PUBLISHED,
    options: [
      {
        title: "Size",
        values: sizeOptions,
      },
      {
        title: "Color",
        values: colorOptions,
      },
    ],
    images: [
      {
        url: faker.image.urlPlaceholder({
          text: title,
        }),
      },
      {
        url: faker.image.urlPlaceholder({
          text: title,
        }),
      },
    ],
    variants: new Array(10).fill(0).map((_, variantIndex) => ({
      title: `${title} ${variantIndex}`,
      sku: `variant-${variantIndex}${index}`,
      prices: new Array(10).fill(0).map((_, priceIndex) => ({
        currency_code,
        amount: 10 * priceIndex,
      })),
      options: {
        Size: sizeOptions[Math.floor(Math.random() * 3)],
      },
    })),
    shipping_profile_id: "sp_123",
    sales_channels: [
      {
        id: defaultSalesChannel[0].id,
      },
    ],
  }
})

// TODO seed products

You generate fifty products using the sales channel and variables you initialized, and using Faker for random data, such as the product's title or images.

Then, replace the new TODO with the following:

const { result: products } = await createProductsWorkflow(container).run({
  input: {
    products: productsData,
  },
})

logger.info(`Seeded ${products.length} products.`)

// TODO add inventory levels

You create the generated products using the createProductsWorkflow imported previously from @medusajs/medusa/core-flows. It accepts the product data as input, and returns the created products.

The only thing left is to create inventory levels for the product variants. So, replace the last TODO with the following:

logger.info("Seeding inventory levels.")

const { data: stockLocations } = await query.graph({
  entity: "stock_location",
  fields: ["id"],
})

const { data: inventoryItems } = await query.graph({
  entity: "inventory_item",
  fields: ["id"],
})

const inventoryLevels = inventoryItems.map((inventoryItem) => ({
  location_id: stockLocations[0].id,
  stocked_quantity: 1000000,
  inventory_item_id: inventoryItem.id,
}))

await createInventoryLevelsWorkflow(container).run({
  input: {
    inventory_levels: inventoryLevels,
  },
})

logger.info("Finished seeding inventory levels data.")

You use Query to retrieve the first stock location in the application and the inventory items.

Then, you generate inventory levels for each inventory item, associating it with the first stock location.

Finally, you use the createInventoryLevelsWorkflow from Medusa's core workflows to create the inventory levels.

Test Script

To test out the script, run the following command in your project's directory:

bash

npx medusa exec ./src/scripts/demo-products.ts

This seeds the products to your database. If you run your Medusa application and view the products in the dashboard, you'll find fifty new products.