# `read-excel-file`

Read `.xlsx` files in a browser or Node.js.

It also supports parsing spreadsheet rows into JSON objects using a [schema](#schema).

[Demo](https://catamphetamine.gitlab.io/read-excel-file/)

Also check out [`write-excel-file`](https://www.npmjs.com/package/write-excel-file) for writing `.xlsx` files.

<details>
<summary>Migrating from <code>6.x</code> to <code>7.x</code></summary>

######

* Renamed the default export `"read-excel-file"` to `"read-excel-file/browser"`, and it uses [Web Workers](https://developer.mozilla.org/docs/Web/API/Web_Workers_API/Using_web_workers) now.
  * Old: `import readExcelFile from "read-excel-file"`
  * New: `import readExcelFile from "read-excel-file/browser"`
* The minimum required Node.js version is 18.
</details>

<details>
<summary>Migrating from <code>7.x</code> to <code>8.x</code></summary>

######

* If you were using the default exported function:
  * Renamed the default exported function to a named exported function `readSheet`.
    * Old: `import readExcelFile from "read-excel-file/browser"`
    * New: `import { readSheet } from "read-excel-file/browser"`
    * And same for other exports like `"read-excel-file/node"`, etc.
  * The default exported function now returns a different kind of result. Specifically, now it returns all available sheets — an array of objects: `[{ sheet: "Sheet 1", data: [['a1','b1','c1'],['a2','b2','c2']] }, ...]`.
  * The default exported function used to return sheet names when passed `getSheets: true` parameter. Now, instead of that, the default exported function just returns all available sheets, from which one could get the sheet names.

* If you were using `readSheetNames()` function:
  * Removed exported function `readSheetNames()`. Use the default exported function instead. The default exported function now returns all sheets.

* If you were using `parseExcelDate()` function:
  * Removed exported function `parseExcelDate()` because there seems to be no need to have it exported.

* If you were using `schema` parameter:
  * Removed `schema` parameter. Instead, use exported function `parseData(data, schema)` to map data to an array of objects.
    * Old: `import readXlsxFile from "read-excel-file"` and then `const { rows, errors } = await readXlsxFile(..., { schema })`
    * New: `import { readSheet, parseData } from "read-excel-file/browser"` and then `const result = parseData(await readSheet(...), schema)`
      * The `result` of the function is an array where each element represents a "data row" and has shape `{ object, errors }`.
        * Depending on whether there were any errors when parsing a given "data row", either `object` or `errors` property will be `undefined`.
        * The `errors` don't have a `row` property anymore because it could be derived from "data row" number.
          * In version `9.x`, the `row` property has been re-added, so consider migrating straight to `9.x`.
        * In version `9.x`, the returned result of `parseData()` has been changed back to `{ errors, objects }`, so consider migrating straight to `9.x`. In that case, if there're no errors, `errors` will be `undefined`; otherwise, `errors` will be a non-empty array and `objects` will be `undefined`.
        * In version `9.x`, the `schema` parameter was re-added to `readSheet()` function, so consider migrating straight to `9.x`.
  * Renamed some `schema`-related parameters:
    * `schemaPropertyValueForMissingColumn` → `propertyValueWhenColumnIsMissing`
    * `schemaPropertyValueForMissingValue` → `propertyValueWhenCellIsEmpty`
    * `schemaPropertyShouldSkipRequiredValidationForMissingColumn` → (removed)
    * `getEmptyObjectValue` → `transformEmptyObject`
      * The leading `.` character is now removed from the `path` parameter.
    * `getEmptyArrayValue` → `transformEmptyArray`
      * The leading `.` character is now removed from the `path` parameter.
  * Previously, when using a `schema` to parse comma-separated values, it used to ignore any commas that're surrounded by quotes, similar to how it's done in `.csv` files. Now it no longer does that.
  * Previously, when using a `schema` to parse comma-separated values, it used to allow empty-string elements. Now it no longer does that and such empty-string elements will now result in an error with properties: `{ error: "invalid", reason: "syntax" }`.
  * Previously, when using a `schema` to parse `type: Date` properties, it used to support both `Date` objects and numeric timestamps as the input data for the property value. In the latter case, it simply force-converted those numeric timestamps to corresponding `Date` objects. Now `parseData()` function no longer does that, and demands the input data for `type: Date` schema properties to only be `Date` objects, i.e. it shifts the responsibility to interpret date cell values correctly onto `readSheet()` and `readExcelFile()` functions. And I'd personally assume that in any real-world (i.e. non-contrived) scenario those functions would interpret date cell values correctly, so I personally don't consider this a "breaking change". Still, formally, it is a "breaking change" and therefore should be mentioned. So if, for some strange reason, those two functions happen to not recognize a date cell value correctly, `parseData()` function will return an error for such cell: `"not_a_date"`.
  * Previously, when using a `schema` to parse sheet data, and a given row of data was completely empty, it didn't run any `required` property validations. Now it no longer does that and it will run all `required` property validations regardless of whether it's a completely empty row of data or not.

* If you were using `transformData` parameter:
  * Removed `transformData` parameter because the `schema` parameter was extracted into a separate function called `parseData()`. Now, if required, a developer could transform the `data` manually and then pass it to `parseData()` function.

* If you were using `isColumnOriented` parameter:
  * Removed `isColumnOriented` parameter because it seemed to be of no use.

* If you were using `ignoreEmptyRows` parameter:
  * Removed `ignoreEmptyRows` parameter. Passing `ignoreEmptyRows: true` parameter no longer makes it skip empty rows in the middle of a sheet. Now it's always the default behavior, as it used to be: only empty rows at the end of a sheet are ignored.

* If you were using TypeScript:
  * Renamed some of the exported types:
    * `Type` → `ParseDataCustomType`
    * `Error` or `SchemaParseCellValueError` → `ParseDataError`
    * `CellValueRequiredError` → `ParseDataValueRequiredError`
    * `ParsedObjectsResult` → `ParseDataResult`
</details>

<details>
<summary>Migrating from <code>8.x</code> to <code>9.x</code></summary>

######

* If you were using `parseData()` function:
  * Rewrote the code of the `parseData()` function and renamed it to `parseSheetData()`.
  * The result of `parseSheetData()` function is now `{ errors, objects }`. If there're no errors, `errors` will be `undefined`. Otherwise, `errors` will be a non-empty array and `objects` will be `undefined`.
    * Previously the result of `parseSheetData()` function was `[{ errors, object }, ...]`, i.e. the `errors` were split between each particular data row. Now the `errors` are combined for all data rows. The rationale is that it's simpler to handle the result of the function this way.
    * Re-added `row: number` property to the `error` object. It's the number of the data row that caused the error, starting from `1`.
    * Added `columnIndex: number` property to the `error` object.
  * Renamed some of the exported TypeScript types:
    * `ParseDataCustomType` → `ParseSheetDataCustomType`
    * `ParseDataCustomTypeErrorMessage` → `ParseSheetDataCustomTypeErrorMessage`
    * `ParseDataCustomTypeErrorReason` → `ParseSheetDataCustomTypeErrorReason`
    * `ParseDataError` → `ParseSheetDataError`
    * `ParseDataValueRequiredError` → `ParseSheetDataValueRequiredError`
    * `ParseDataResult` → `ParseSheetDataResult`
  * In a `schema`, a nested object could be declared as: `{ required: true/false, schema: { ... } }`. This is still true but the `required` flag is now only allowed to be either `undefined` or `false`, so `true` value is not allowed. The reason is quite simple. If a nested object as a whole is marked as `required: true`, and then it happens to be empty, a `"required"` error should be returned for it. But that error would also have to include a `column` title, and a nested object simply can't be pinned down to a single column in a sheet because it is by definition spread over multiple columns. So instead of marking a nested object as a whole with `required: true`, mark the specific required properties of it.
  * Re-added `schema` parameter to `readSheet()` function.
    * `const { objects, errors } = readSheet(data, { schema })`
</details>

## Install

```js
npm install read-excel-file --save
```

Alternatively, it could be included on a web page [directly](#cdn) via a `<script/>` tag.

## Use

If your `.xlsx` file only has a single "sheet", or if you only need to read a single "sheet", or if you don't care what a "sheet" is, use `readSheet()` function.

For example, consider the following `.xlsx` file:

| Name       | Date of Birth | Married | Kids |
| ---------- | ------------- | ------- | ---- |
| John Smith | 1/1/1995      | TRUE    | 3    |
| Kate Brown | 3/1/2010      | FALSE   | 0    |

Here's how to read it using `readSheet()` function:

```js
import { readSheet } from 'read-excel-file/node'

await readSheet(file) ===
[
  ['Name', 'Date of Birth', 'Married', 'Kids'],
  ['John Smith', 1995-01-01T00:00:00.000Z, true, 3],
  ['Kate Brown', 2010-03-01T00:00:00.000Z, false, 0]
]
```

The result is an array of rows. Each row is an array of values — `string`, `number`, `boolean` or `Date`.

<!-- It's same as the default exported function shown above with the only difference that it returns just `data` instead of `[{ name: 'Sheet1', data }]`, so it's just a bit simpler to use. It has an optional second argument — `sheet` — which could be a sheet number (starting from `1`) or a sheet name. By default, it reads the first sheet. -->

It also has an optional second argument — `sheet` — which could be a sheet number (starting from `1`) or a sheet name. By default, it reads the first sheet.

But if you need to read all available "sheets" in a file, use the default exported function:

```js
import readExcelFile from 'read-excel-file/node'

await readExcelFile(file) ===
[{
  sheet: 'Sheet1',
  data: [
    ['Name', 'Age'],
    ['John Smith', 30],
    ['Kate Brown', 15]
  ]
}, {
  sheet: 'Sheet2',
  data: ...
}]
```

The result is a non-empty array of "sheets". Each "sheet" is an object with properties:
* `sheet` — Sheet name.
  * Example: `"Sheet1"`
* `data` — Sheet data. An array of rows. Each row is an array of values — `string`, `number`, `boolean` or `Date`.
  * Example: `[ ['Name','Age'], ['John Smith',30], ['Kate Brown',15] ]`

Also, a very common use case is to read a list of JSON objects from an `.xlsx` file. To do that, pass a [`schema`](#schema) parameter to `readSheet()` function.

## Import

This package provides a separate `import` path for each different environment, as described below.

### Browser

`read-excel-file/browser`

It can read from a [`File`](https://developer.mozilla.org/en-US/docs/Web/API/File), a [`Blob`](https://developer.mozilla.org/en-US/docs/Web/API/Blob) or an [`ArrayBuffer`](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/ArrayBuffer).

Example: User chooses a file and the web application reads it.

```html
<input type="file" id="input" />
```

```js
import { readSheet } from 'read-excel-file/browser'

const input = document.getElementById('input')

input.addEventListener('change', () => {
  const data = await readSheet(input.files[0])
})
```

Note: Internet Explorer 11 is an old browser that doesn't support [`Promise`](https://developer.mozilla.org/ru/docs/Web/JavaScript/Reference/Global_Objects/Promise), and hence requires a [polyfill](https://www.npmjs.com/package/promise-polyfill).

<details>
<summary>Example 2: Reading from a URL</summary>

######

```js
const response = await fetch('https://example.com/spreadsheet.xlsx')
const block = await response.blob()
const data = await readSheet(blob)
```
</details>

<details>
<summary>Example 3: Using <code>read-excel-file</code> in a Web Worker</summary>

######

All exports of `read-excel-file` already use a [Web Worker](https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers) under the hood when reading `.xlsx` file contents. This is in order to avoid freezing the UI when reading large files. So using an additional Web Worker on top of that isn't really necessary. Still, for those who require it, this example shows how a user chooses a file and the web application reads it in a [Web Worker](https://developer.mozilla.org/en-US/docs/Web/API/Web_Workers_API/Using_web_workers) using `read-excel-file/web-worker` import path.

```js
// Step 1: Initialize Web Worker.

const worker = new Worker('web-worker.js')

worker.onmessage = function(event) {
  // `event.data` is a `File`.
  console.log(event.data)
}

worker.onerror = function(event) {
  console.error(event.message)
}

// Step 2: User chooses a file and the application sends it to the Web Worker.

const input = document.getElementById('input')

input.addEventListener('change', () => {
  worker.postMessage(input.files[0])
})
```

##### `web-worker.js`

```js
import { readSheet } from 'read-excel-file/web-worker'

onmessage = async function(event) {
  const sheetData = await readSheet(event.data)
  postMessage(sheetData)
}
```
</details>

### Node.js

`read-excel-file/node`

It can read from a file path, a [`Stream`](https://nodejs.org/api/stream.html), a [`Buffer`](https://nodejs.org/api/buffer.html) or a [`Blob`](https://developer.mozilla.org/docs/Web/API/Blob).

Example 1: Read from a file path.

```js
import { readSheet } from 'read-excel-file/node'

const data = await readSheet('/path/to/file')
```

Example 2: Read from a [`Stream`](https://nodejs.org/api/stream.html)

```js
import { readSheet } from 'read-excel-file/node'

const data = await readSheet(fs.createReadStream('/path/to/file'))
```

### Universal

`read-excel-file/universal`

This one works both in a web browser and Node.js. It can only read from a [`Blob`](https://developer.mozilla.org/en-US/docs/Web/API/Blob) or an [`ArrayBuffer`](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/ArrayBuffer), which could be a bit less convenient for general use.

```js
import { readSheet } from 'read-excel-file/universal'

const data = await readSheet(blob)
```

## Strings

By default, it automatically trims all string values. To disable this behavior, pass `trim: false` option.

```js
readExcelFile(file, { trim: false })
```

## Dates

`.xlsx` file format originally had no dedicated "date" type, so dates are in almost all cases stored simply as numbers, equal to the count of days since `01/01/1900` (with a few [quirks](https://www.reddit.com/r/AskStatistics/comments/7uk40z/excel_calculates_dates_wrong_so_please_be_careful/)). To correctly interpret such numbers as dates, each date cell in an `.xlsx` file specifies a certain ["format"](https://xlsxwriter.readthedocs.io/format.html#format-set-num-format) — for example, `"d mmm yyyy"` — that instructs a spreadsheet viewer application to interpret the numeric value in the cell as a date rather than a number, and display it using the specified format.

Being no different from a generic spreadsheet viewer application, this package follows the same practice: it attempts to guess whether a given cell value is a date or a number by looking at the cell's "format" — if the "format" is one of the known [standard date formats](https://docs.microsoft.com/en-us/dotnet/api/documentformat.openxml.spreadsheet.numberingformat?view=openxml-2.8.1) then the cell value is interpreted as a date rather than a number. So usually there's no need to configure anything and it usually "just works" out-of-the-box.

Although there's still a possibility for an `.xlsx` file to specify a totally-custom non-standard date format. In such case, a developer could pass a `dateFormat` parameter to tell this package to parse cells having that specific "format" as date ones rather than numeric ones: `readExcelFile(file, { dateFormat: 'mm/dd/yyyy' })`.

## Numbers

When reading an `.xlsx` file, any numeric values are parsed from a string to a javascript `number`. But there's an inherent issue with javascript `number`s in general — their [floating-point precision](https://www.youtube.com/watch?v=2gIxbTn7GSc) is sometimes less than ideal. For example, `0.1 + 0.2 != 0.3`. Yet, applications in areas such as finance or banking usually require 100% floating-point precision, which is usually worked around by using a custom implementation of a "decimal" data type such as [`decimal.js`](https://www.npmjs.com/package/decimal.js).

This package supports passing a custom `parseNumber(string)` function as an option when reading an `.xlsx` file. By default, it parses a `string` to a javascript `number`, but one could pass any custom implementation.

Example: Use "decimal" data type to perform further calculations on fractional numbers with 100% precision.

```js
import Decimal from 'decimal.js'

readExcelFile(file, {
  parseNumber: (string) => new Decimal(string)
})
```

## Formulas

This package doesn't support reading cells that use formulas to calculate the value: `SUM`, `AVERAGE`, etc.

## Performance

Here're the results of reading [sample `.xlsx` files](https://examplefile.com/document/xlsx) of different size:

|File Size| Browser |  Node.js  |
|---------|---------|-----------|
|   1 MB  | 0.2 sec.| 0.25 sec. |
|  10 MB  | 1.5 sec.|    2 sec. |
|  50 MB  | 8.5 sec.|   14 sec. |

## Schema

Oftentimes, the task is not just to read the "raw" spreadsheet data but also to convert each row of that data to a JSON object having a certain structure. Because it's such a common task, this package provides an easy way to do that — just pass a `schema` parameter when calling `readSheet()` function and it will automatically parse sheet data into an array of JSON objects according to that `schema` (which basically describes all properties of the object and which column should be mapped to which property). The only requirement is that the sheet data should adhere to a simple structure: the first row should be a header row with just column titles, and each following row should specify the values for those columns.

```js
import { readSheet } from 'read-excel-file/node'

const schema = { ... }

const { objects, errors } = await readSheet(file, { schema })

if (errors) {
  console.error(errors)
} else {
  console.log(objects)
}
```

The result is `{ objects, errors }`
* If there were any errors, `objects` will be `undefined` and `errors` will be a list of errors.
* If there were no errors, `errors` will be `undefined` and `objects` will be a list of objects.

`schema` should describe the structure of the resulting JSON objects. An example of a `schema` is provided at the end of this section.

Specifically, a `schema` should be an object having the same keys as a resulting JSON object, with values being nested objects having the following properties:

* `column` — The title of the column to read the value from.
  * If the column is missing from the spreadsheet, the property value will be `undefined`.
    * This can be overridden by passing `propertyValueWhenColumnIsMissing` option. Is `undefined` by default.
  * If the column is present in the spreadsheet but is empty, the property value will be `null`.
    * This can be overridden by passing `propertyValueWhenCellIsEmpty` option. Is `null` by default.
* `required` — (optional) Is the value required?
  * Could be one of:
    * `required: boolean`
      * `true` — The column must not be missing from the spreadsheet and the cell value must not be empty.
      * `false` — The column can be missing from the spreadsheet, or the cell value can be empty.
    * `required: (object) => boolean` — A function returning `true` or `false` depending on the other properties of the object.
  <!-- * To skip `required` validation for a column that is missing from a spreadsheet, one could pass `shouldSkipRequiredValidationWhenColumnIsMissing` option. It should be a function: `(columnTitle, { object }) => boolean`. By default it always returns `false` meaning that when `columnTitle` is missing from the spreadsheet, it will not skip performing the `required` validation for it. -->
* `validate(value)` — (optional) Validates the value. Is only called for non-empty cells. If the value is invalid, this function should throw an error.
* `schema` — (optional) If the value is going to be a nested object, `schema` should describe that nested object.
  * If when parsing such nested object, all of its property values happen to be empty — `undefined` or `null` — then the nested object will be itself set to `null`.
    * This can be overridden by passing `transformEmptyObject(object, { path? })` function as an option. By default, it returns `null`.
    * This applies both to nested objects and to the top-level object itself.
* `type` — (optional) If the value is not going to be a nested object, `type` should describe the type of the value. It will determine how the cell value will be converted to a property value. If no `type` is specified then the property value will be same as the cell value.
  * Valid `type`s:
    * Standard types:
      * `String`
      * `Number`
      * `Boolean`
      * `Date`
    * One of the "utility" types that're exported from this package:
      * `Integer`
      * `Email`
      * `URL`
    * Custom type:
      * A function that receives a cell value and returns any kind of a parsed value. Returning `undefined` will have same effect as returning `null`. If the value is invalid, it should throw an error.
  * If the cell value is comprised of comma-separated values (example: `"a, b, c"`) and if it should be parsed as an array of such values, then the property `type` could be specified as an array — `type: [elementType]` — where `elementType` could be any valid `type` described above. For example, if a property is defined as `{ type: [String] }` and the cell value is `"a, b, c"` then the property value will be parsed as `["a", "b", "c"]`.
    * If the cell is empty, or if every element of the parsed array is `null` or `undefined`, then the property value itself will be set to `null`.
      * This can be overridden by passing `transformEmptyArray(array, { path })` function as an option. By default, it returns `null`.
    * The separator could be specified by passing `arrayValueSeparator` option. By default, it's `","`.
    * The separated parts of a cell value will be trimmed.

If there're any errors during the conversion process, the `errors` property returned from the function will be a non-empty array (by default, it's an empty array). Each `error` object has properties:

* `error: string` — The error code. Examples: `"required"`, `"invalid"`.
  * If a custom `validate()` function is defined and it throws a `new Error(message)` then the `error` property will be the same as the `message` argument.
  * If a custom `type()` function is defined and it throws a `new Error(message)` then the `error` property will be the same as the `message` argument.
* `reason?: string` — An optional secondary error code providing more details about the error. I.e. "`error.error` happened specifically because of `error.reason`". Currently, it could only be returned for the standard `type`s.
  * Example: `{ error: "invalid", reason: "not_a_number" }` for a `type: Number` property means that "the cell value is _invalid_ **because** it's _not a number_".
* `row: number` — The row number, starting from `1`.
  * `row: 1` means "first row of data", etc.
  * Don't mind the header row.
* `column: string` — The column title.
* `columnIndex: number` — The column index.
  * `columnIndex: 0` means "first column", etc.
* `value?: any` — The cell value.
* `type?: any` — The `type` of the property, as defined by the `schema`.

Example:

```js
// An example .xlsx document:
// --------------------------------------------------------------------------------------------------------
// | START DATE | SEATS |   STATUS  |    CONTACT     | COURSE TITLE  | COURSE CATEGORY   | COURSE IS FREE |
// --------------------------------------------------------------------------------------------------------
// | 03/24/2018 |   10  | SCHEDULED | (123) 456-7890 | Basic Algebra | Math, Arithmetic  |     TRUE       |
// --------------------------------------------------------------------------------------------------------

const schema = {
  startDate: {
    column: 'START DATE',
    type: Date
  },
  seats: {
    column: 'SEATS',
    type: Number,
    required: true
  },
  status: {
    column: 'STATUS',
    type: String,
    // An example of using `oneOf`
    oneOf: [
      'SCHEDULED',
      'STARTED',
      'FINISHED'
    ]
  },
  contact: {
    column: 'CONTACT',
    required: true,
    // An example of using a custom `type`
    type: PhoneNumber
  },
  // Nested object example
  course: {
    // A nested object could be declared as completely optional by specifying `required: false`.
    // In that case, when all of its properties are missing from the input data, it wouldn't throw any error
    // regardless of whether some of its properties are declared as `required: true` or not.
    required: false,
    schema: {
      title: {
        column: 'COURSE TITLE',
        type: String,
        // When course data is present, the course title must be specified.
        required: true
      },
      categories: {
        column: 'COURSE CATEGORY',
        // An example of parsing comma-separated values.
        type: [String]
      },
      isFree: {
        column: 'COURSE IS FREE',
        type: Boolean
      }
    }
  }
}

// If this code was written in TypeScript, `schema` would've been declared as:
// const schema: Schema<Object, ColumnTitle> = { ... }

// Read `data` from an `.xlsx` file and parse it using a `schema`.
const { objects, errors } = await readSheet(file, { schema })

// There have been no errors when parsing the sheet data, so `errors` is `undefined`.
// Should there have been any errors when parsing the sheet data, `errors` would've been
// an array of items having shape: `{ row, column, error, reason?, value?, type? }`.
errors === undefined

// There's one data row in the `.xlsx` file.
objects.length === 1

// The parsed data row.
objects[0] === {
  startDate: new Date(Date.UTC(2018, 3 - 1, 24)),
  seats: 10,
  status: 'SCHEDULED',
  contact: '+11234567890',
  course: {
    title: 'Basic Algebra',
    categories: ['Math', 'Arithmetic']
    isFree: true
  }
}

// An example of a custom `type` parser function.
// It will parse the cell value when it's not empty.
function PhoneNumber(value) {
  const number = parsePhoneNumber(value)
  if (!number) {
    throw new Error('invalid')
  }
  return number
}
```

Also, for convenience, this package exports the same feature as a separate function — `parseSheetData(sheetData, schema)`.

```js
import { readSheet, parseSheetData } from 'read-excel-file/node'

const schema = { ... }
const sheetData = await readSheet(file)
const { objects, errors } = parseSheetData(sheetData, schema)
if (errors) {
  console.error(errors)
} else {
  console.log(objects)
}
```

<details>
<summary>An example of defining a <strong>custom <code>type</code></strong> in <strong>TypeScript</strong></summary>

#####

```ts
import type {
  Schema,
  CellValue,
  ParseSheetDataError,
  ParseSheetDataCustomType,
  ParseSheetDataCustomTypeErrorMessage
} from 'read-excel-file/node'

type ColumnTitle = 'COLUMN TITLE 1' | 'COLUMN TITLE 2'

type CustomTypeValue = string

function CustomType(value: CellValue): CustomTypeValue {
  if (typeof value !== 'string') {
    throw new Error('not_a_string')
  }
  return '~' + value + '~'
}

type CustomTypeErrorMessage<Type extends ParseSheetDataCustomType<unknown>> =
  Type extends typeof CustomType
    ? 'not_a_string'
    : never

// type CustomTypeErrorReason<
//   Type extends ParseSheetDataCustomType<unknown>,
//   ErrorMessage extends ParseSheetDataCustomTypeErrorMessage<Type>
// > =
//   Type extends typeof CustomType
//     ? (ErrorMessage extends 'not_a_string' ? undefined : never)
//     : never

type PossibleError = ParseSheetDataError<
  ColumnTitle,
  typeof CustomType,
  CustomTypeErrorMessage<typeof CustomType>
  // CustomTypeErrorReason<typeof CustomType, CustomTypeErrorMessage<typeof CustomType>>
>

interface Object {
  property1: CustomTypeValue;
  property2?: string;
}

const schema: Schema<Object, ColumnTitle> = {
  property1: {
    column: 'COLUMN TITLE 1',
    type: CustomType,
    required: true
  },
  property2: {
    column: 'COLUMN TITLE 2',
    type: String
  }
}

const { objects, errors } = parseSheetData<Object, ColumnTitle, PossibleError>([
  ['COLUMN TITLE 1', 'COLUMN TITLE 2'],
  ['Value 1', 'Value 2']
], schema)

if (errors) {
  for (const error of errors) {
    console.error('Error in data row', error.row, 'column', error.column, ':', error.error, error.reason || '')
  }
} else {
  console.log('Objects', objects)
}
```
</details>

<!-- A schema entry for a column may also define an optional `validate(value)` function for validating the parsed value: in that case, it must `throw` an `Error` if the `value` is invalid. The `validate(value)` function is only called when `value` is not empty (not `null` / `undefined`). -->

<details>
<summary>An example of a <strong>React component to output <code>errors</code></strong></summary>

#####

```js
function ErrorsList({ errors }) {
  return (
    <ul>
      {errors.map((error, i) => (
        <li key={i}>
          <ErrorItem error={error}>
        </li>
      ))}
    </ul>
  )
}

function ErrorItem({ error }) {
  const {
    error: errorMessage,
    reason,
    row,
    column,
    columnIndex,
    value,
    type
  } = error

  // Error summary.
  return (
    <div>
      <code>"{errorMessage}"</code>
      {reason && ' '}
      {reason && <code>("{reason}")</code>}
      {' for value '}
      <code>{stringifyValue(value)}</code>
      {' in column '}
      <code>"{column}"</code>
      {' in data row '}
      <code>{row}</code>
      {' of the spreadsheet'}
    </div>
  )
}

function stringifyValue(value) {
  // Wrap strings in quotes.
  if (typeof value === 'string') {
    return '"' + value + '"'
  }
  return String(value)
}
```
</details>

## Browser Support

An `.xlsx` file is just a `.zip` archive with an `.xslx` file extension. This package uses [`fflate`](https://www.npmjs.com/package/fflate) for `.zip` decompression. See `fflate`'s [browser support](https://www.npmjs.com/package/fflate#browser-support) for further details.

## CDN

To include this library directly via a `<script/>` tag on a page, one can use any npm CDN service, e.g. [unpkg.com](https://unpkg.com) or [jsdelivr.com](https://jsdelivr.com)

```html
<script src="https://unpkg.com/read-excel-file@5.x/bundle/read-excel-file.min.js"></script>

<script>
  var input = document.getElementById('input')
  input.addEventListener('change', function() {
    readXlsxFile(input.files[0]).then(function(rows) {
      // `rows` is an array of rows
      // each row being an array of cells.
    })
  })
</script>
```

## GitHub

On March 9th, 2020, GitHub, Inc. silently [banned](https://medium.com/@catamphetamine/how-github-blocked-me-and-all-my-libraries-c32c61f061d3) my account (erasing all my repos, issues and comments, even in my employer's private repos) without any notice or explanation. Because of that, all source codes had to be promptly moved to GitLab. The [GitHub repo](https://github.com/catamphetamine/read-excel-file) is now only used as a backup (you can star the repo there too), and the primary repo is now the [GitLab one](https://gitlab.com/catamphetamine/read-excel-file). Issues can be reported in any repo.

## License

[MIT](LICENSE)