A xlsx based resource validator using Zod schemas
Supports both ESM and CJS
Note: This package requires Zod and xlsx as peer dependencies
# With npm
npm install zod-xlsx xlsx zod
# With yarn
yarn add zod-xlsx xlsx zod
# With pnpm
pnpm add zod-xlsx xlsx zod
The library exports a single function called createValidator
which takes in a xlsx workbook and creates a validator object.
Please make sure your top row of the sheet (xlsx or xls) file contains only header content for the columns as it's required for the library to function properly.
import { createValidator } from "zod-xlsx"
import xlsx from "xlsx"
const workbook = xlsx.readFile(/*path to your file*/)
const validator = createValidator(workbook)
const schema = z.object({
"First Name": z.string(),
"Last Name": z.string(),
Gender: z.enum(["Male", "Female"]),
Country: z.string(),
Age: z.number(),
Date: z.string(),
Id: z.number(),
})
const result = validator.validate(schema)
OUTPUT
{
valid: [
{ issues: [], isValid: true, data: [Object] },
{ issues: [], isValid: true, data: [Object] },
{ issues: [], isValid: true, data: [Object] },
{ issues: [], isValid: true, data: [Object] },
]
invalid: [
{ issues: [Object], isValid: false, data: [Object] },
{ issues: [Object], isValid: false, data: [Object] },
{ issues: [Object], isValid: false, data: [Object] },
]
}
Function to create a new validator object with the given workbook. It takes an options object as the second arguement.
export interface ValidatorOptions {
// Comes from xlsx
header?: Sheet2JSONOpts["header"]
blankrows?: Sheet2JSONOpts["blankrows"]
skipHidden?: Sheet2JSONOpts["skipHidden"]
// Zod-xlsx options
sheetName?: string
onValid?: (data: any) => void
onInvalid?: (data: any) => void
}
-
sheetName: name of the sheet to use, defaults to the first sheet in the document.
-
onValid: hook which gets called after every valid item is processed.
-
onValid: hook which gets called after every invalid item is processed.
For details on what each of the xlsx option does can be found: Here
Synchronously parses all the rows against the given schema and returns the result.
Asynchronously parses all the rows against the given schema without blocking the event loop, it does this using batch processing. (500 is the default batch size)
Depending on your usecase, its possible to configure the batchSize
like so: validateAsync(schema, { batchSize: 500 })
.
MIT © sidwebworks