--- pagination_prev: getting-started/installation/index pagination_next: getting-started/roadmap sidebar_position: 2 --- import current from '/version.js'; import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem'; import CodeBlock from '@theme/CodeBlock'; # Export Tutorial Many modern data sources provide an API to download data in JSON format. Many users prefer to work in spreadsheet software. SheetJS libraries help bridge the gap by translating programmer-friendly JSON to user-friendly workbooks. The goal of this example is to generate a XLSX workbook of US President names and birthdates. We will download and wrangle a JSON dataset using standard JavaScript functions. Once we have a simple list of names and birthdates, we will use SheetJS API functions to build a workbook object and export to XLSX. The ["Live Demo"](#live-demo) section includes a working demo in this page! ["Run the Demo Locally"](#run-the-demo-locally) shows how to run the workflow in iOS / Android apps, desktop apps, NodeJS scripts and other environments. The following sequence diagram shows the process: ```mermaid sequenceDiagram actor U as User participant P as Page participant A as API U->>P: click button P->>A: fetch data A->>P: raw data Note over P: process data Note over P: make workbook Note over P: export file P->>U: download workbook ``` ## Acquire Data The raw data is available in JSON form[^1]. It has been mirrored at ### Raw Data Acquiring the data is straightforward with `fetch`: ```js const url = "https://sheetjs.com/data/executive.json"; const raw_data = await (await fetch(url)).json(); ```
Code Explanation (click to show) `fetch` is a low-level API for downloading data from an endpoint. It separates the network step from the response parsing step. **Network Step** `fetch(url)` returns a `Promise` representing the network request. The browser will attempt to download data from the URL. If the network request succeeded, the `Promise` will "return" with a `Response` object. Using modern syntax, inside an `async` function, code should `await` the fetch: ```js const response = await fetch(url); ``` **Checking Status Code** If the file is not available, the `fetch` will still succeed. The status code, stored in the `status` property of the `Response` object, is a standard HTTP status code number. Code should check the result. Typically servers will return status `404` "File not Found" if the file is not available. A successful request should have status `200` "OK". **Extracting Data** `Response#json` will try to parse the data using `JSON.parse`. Like `fetch`, the `json` method returns a `Promise` that must be `await`-ed: ```js const raw_data = await response.json(); ``` :::note pass The `Response` object has other useful methods. `Response#arrayBuffer` will return the raw data as an `ArrayBuffer`, suitable for parsing workbook files. ::: **Production Use** Functions can test each part independently and report different errors: ```js async function get_data_from_endpoint(url) { /* perform network request */ let response; try { response = await fetch(url); } catch(e) { /* network error */ throw new Error(`Network Error: ${e.message}`); } /* check status code */ if(response.status == 404) { /* server 404 error -- file not found */ throw new Error("File not found"); } if(response.status != 200) { /* for most servers, a successful response will have status 200 */ throw new Error(`Server status ${response.status}: ${response.statusText}`); } /* parse JSON */ let data; try { data = await response.json(); } catch(e) { /* parsing error */ throw new Error(`Parsing Error: ${e.message}`); } return data; } ```
The raw data is an Array of objects[^2]. For this discussion, the relevant data for John Adams is shown below: ```js { "name": { "first": "John", // <-- first name "last": "Adams" // <-- last name }, "bio": { "birthday": "1735-10-19", // <-- birthday }, "terms": [ // <-- array of presidential terms { "type": "viceprez", "start": "1789-04-21", }, { "type": "viceprez", "start": "1793-03-04", }, { "type": "prez", "start": "1797-03-04", } // <-- presidential term ] } ``` ### Filtering for Presidents The dataset includes Aaron Burr, a Vice President who was never President! The `terms` field of each object is an array of terms. A term is a Presidential term if the `type` property is `"prez"`. We are interested in Presidents that served at least one term. The following line creates an array of Presidents: ```js const prez = raw_data.filter(row => row.terms.some(term => term.type === "prez")); ``` :::caution pass JavaScript code can be extremely concise. The "Code Explanation" blocks explain the code in more detail. :::
Code Explanation (click to show) **Verifying if a person was a US President** `Array#some` takes a function and calls it on each element of an array in order. If the function ever returns `true`, `Array#some` returns `true`. If each call returns `false`, `Array#some` returns `false`. The following function tests if a term is presidential: ```js const term_is_presidential = term => term.type == "prez"; ``` To test if a person was a President, that function should be tested against every term in the `terms` array: ```js const person_was_president = person => person.terms.some(term => term.type == "prez"); ``` **Creating a list of US Presidents** `Array#filter` takes a function and returns an array. The function is called on each element in order. If the function returns `true`, the element is added to the final array. If the function returns false, the element is not added. Using the previous function, this line filters the dataset for Presidents: ```js const prez = raw_data.filter(row => person_was_president(row)); ``` Placing the `person_was_president` function in-line, the final code is: ```js const prez = raw_data.filter(row => row.terms.some(term => term.type == "prez")); ```
### Sorting by First Term The dataset is sorted in chronological order by the first presidential or vice presidential term. The Vice President and President in a given term are sorted alphabetically. Joe Biden and Barack Obama were Vice President and President respectively in 2009. Since "Biden" is alphabetically before "Obama", Biden's data point appears first. The goal is to sort the presidents in order of their presidential term. The first step is adding the first presidential term start date to the dataset. The following code looks at each president and creates a `start` property that represents the start of the first presidential term. ```js prez.forEach(row => row.start = row.terms.find(term => term.type === "prez").start); ```
Code Explanation (click to show) **Finding the first presidential term** `Array#find` will find the first value in an array that matches a criterion. The first presidential term can be found with the following function: ```js const first_prez_term = prez => prez.terms.find(term => term.type === "prez"); ``` :::note pass If no element in the array matches the criterion, `Array#find` does not return a value. In this case, since `prez` was created by filtering for people that served at least one presidential term, the code assumes a term exists. ::: The start of a President's first Presidential term is therefore ```js const first_prez_term_start = prez => first_prez_term(prez).start; ``` **Adding the first start date to one row** The following function creates the desired `start` property: ```js const prez_add_start = prez => prez.start = first_prez_term_start(prez); ``` **Adding the first start date to each row** `Array#forEach` takes a function and calls it for every element in the array. Any modifications to objects affect the objects in the original array. The previous function can be used directly: ```js prez.forEach(row => prez_add_start(row)); ``` Working in reverse, each partial function can be inserted in place. These lines of code are equivalent: ```js /* start */ prez.forEach(row => prez_add_start(row)); /* put `prez_add_start` definition into the line */ prez.forEach(row => row.start = first_prez_term_start(row)); /* put `first_prez_term_start` definition into the line */ prez.forEach(row => row.start = first_prez_term(row).start); /* put `first_prez_term` definition into the line */ prez.forEach(row => row.start = row.terms.find(term => term.type === "prez").start); ```
At this point, each row in the `prez` array has a `start` property. Since the `start` properties are strings, the following line sorts the array: ```js prez.sort((l,r) => l.start.localeCompare(r.start)); ```
Code Explanation (click to show) **Comparator Functions and Relative Ordering in JavaScript** A comparator takes two arguments and returns a number that represents the relative ordering. `comparator(a,b)` should return a negative number if `a` should be placed before `b`. If `b` should be placed before `a`, the comparator should return a positive number. If the `start` properties were numbers, the following comparator would suffice: ```js const comparator_numbers = (a,b) => a - b; ``` For strings, JavaScript comparison operators can work: ```js const comparator_string_simple = (a,b) => a == b ? 0 : a < b ? -1 : 1; ``` However, that comparator does not handle diacritics. For example, `"z" < "é"`. It is strongly recommended to use `String#localeCompare` to compare strings: ```js const comparator_string = (a,b) => a.localeCompare(b); ``` **Comparing two Presidents** The `start` properties of the Presidents should be compared: ```js const compare_prez = (a,b) => (a.start).localeCompare(b.start); ``` **Sorting the Array** `Array#sort` takes a comparator function and sorts the array in place. Using the Presidential comparator: ```js prez.sort((l,r) => compare_prez(l,r)); ``` Placing the `compare_prez` function in the body: ```js prez.sort((l,r) => l.start.localeCompare(r.start)); ```
### Reshaping the Array For this example, the name will be the first name combined with the last name (`row.name.first + " " + row.name.last`) and the birthday will be available at `row.bio.birthday`. Using `Array#map`, the dataset can be massaged in one call: ```js const rows = prez.map(row => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday })); ```
Code Explanation (click to show) **Wrangling One Data Row** The key fields for John Adams are shown below: ```js { "name": { "first": "John", // <-- first name "last": "Adams" // <-- last name }, "bio": { "birthday": "1735-10-19", // <-- birthday } } ``` If `row` is the object, then - `row.name.first` is the first name ("John") - `row.name.last` is the last name ("Adams") - `row.bio.birthday` is the birthday ("1735-10-19") The desired object has a `name` and `birthday` field: ```js function get_data(row) { var name = row.name.first + " " + row.name.last; var birthday = row.bio.birthday; return ({ name: name, birthday: birthday }); } ``` This can be shortened by adding the fields to the object directly: ```js function get_data(row) { return ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday }); } ``` When writing an arrow function that returns an object, parentheses are required: ```js // open paren required --V const get_data = row => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday }); // ^-- close paren required ``` **Wrangling the entire dataset** `Array#map` calls a function on each element of an array and returns a new array with the return values of each function. Using the previous method: ```js const rows = prez.map(row => get_data(row)); ``` The `get_data` function can be added in place: ```js const rows = prez.map(row => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday })); ```
The result is an array of "simple" objects with no nesting: ```js [ { name: "George Washington", birthday: "1732-02-22" }, { name: "John Adams", birthday: "1735-10-19" }, // ... one row per President ] ``` ## Create a Workbook With the cleaned dataset, `XLSX.utils.json_to_sheet`[^3] generates a worksheet: ```js const worksheet = XLSX.utils.json_to_sheet(rows); ``` `XLSX.utils.book_new`[^4] creates a new workbook and `XLSX.utils.book_append_sheet`[^5] appends a worksheet to the workbook. The new worksheet will be called "Dates": ```js const workbook = XLSX.utils.book_new(); XLSX.utils.book_append_sheet(workbook, worksheet, "Dates"); ``` ## Clean up Workbook The data is in the workbook and can be exported. ![Rough export](pathname:///example/rough.png) There are multiple opportunities for improvement: the headers can be renamed and the column widths can be adjusted. :::tip pass [SheetJS Pro](https://sheetjs.com/pro) offers additional styling options like cell styling and frozen rows. :::
Changing Header Names (click to show) By default, `json_to_sheet` creates a worksheet with a header row. In this case, the headers come from the JS object keys: "name" and "birthday". The headers are in cells `A1` and `B1`. `XLSX.utils.sheet_add_aoa`[^6] can write text values to the existing worksheet starting at cell `A1`: ```js XLSX.utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" }); ```
Changing Column Widths (click to show) Some of the names are longer than the default column width. Column widths are set by setting the `"!cols"` worksheet property.[^7] The following line sets the width of column A to approximately 10 characters: ```js worksheet["!cols"] = [ { wch: 10 } ]; // set column A width to 10 characters ``` One `Array#reduce` call over `rows` can calculate the maximum width: ```js const max_width = rows.reduce((w, r) => Math.max(w, r.name.length), 10); worksheet["!cols"] = [ { wch: max_width } ]; ```
After cleanup, the generated workbook looks like the screenshot below: ![Final export](pathname:///example/final.png) ## Export a File `XLSX.writeFile`[^8] creates a spreadsheet file and tries to write it to the system. In the browser, it will try to prompt the user to download the file. In NodeJS, it will write to the local directory. ```js XLSX.writeFile(workbook, "Presidents.xlsx", { compression: true }); ``` ## Live Demo This demo runs in the web browser! Click "Click to Generate File!" and the browser should try to create `Presidents.xlsx` ```jsx live function Presidents() { return ( ); } ``` is a hosted version of this demo. ## Run the Demo Locally Save the following script to `SheetJSStandaloneDemo.html`: {`\ `} After saving the file, run a local web server in the folder with the HTML file. For example, if NodeJS is installed: ```bash npx http-server . ``` The server process will display a URL (typically `http://127.0.0.1:8080`). Open `http://127.0.0.1:8080/SheetJSStandaloneDemo.html` in your browser. Install the dependencies: {`\ npm i --save https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz`} {`\ bun install https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz`} Save the following script to `SheetJSNodeJS.js`: ```js title="SheetJSNodeJS.js" const XLSX = require("xlsx"); (async() => { /* fetch JSON data and parse */ const url = "https://sheetjs.com/data/executive.json"; const raw_data = await (await fetch(url)).json(); /* filter for the Presidents */ const prez = raw_data.filter(row => row.terms.some(term => term.type === "prez")); /* sort by first presidential term */ prez.forEach(row => row.start = row.terms.find(term => term.type === "prez").start); prez.sort((l,r) => l.start.localeCompare(r.start)); /* flatten objects */ const rows = prez.map(row => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday })); /* generate worksheet and workbook */ const worksheet = XLSX.utils.json_to_sheet(rows); const workbook = XLSX.utils.book_new(); XLSX.utils.book_append_sheet(workbook, worksheet, "Dates"); /* fix headers */ XLSX.utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" }); /* calculate column width */ const max_width = rows.reduce((w, r) => Math.max(w, r.name.length), 10); worksheet["!cols"] = [ { wch: max_width } ]; /* create an XLSX file and try to save to Presidents.xlsx */ XLSX.writeFile(workbook, "Presidents.xlsx", { compression: true }); })(); ``` After saving the script, run the script: ```bash node SheetJSNodeJS.js ``` ```bash bun run SheetJSNodeJS.js ``` This script will write a new file `Presidents.xlsx` in the same folder. :::caution pass Native `fetch` support was added in NodeJS 18. For older versions of NodeJS, the script will throw an error `fetch is not defined`. A third-party library like `axios` presents a similar API for fetching data:
Example using axios (click to show) Install the dependencies: {`\ npm i --save https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz axios`} Save the following script to `SheetJSAxios.js` (differences are highlighted): ```js title="SheetJSAxios.js" const XLSX = require("xlsx"); // highlight-next-line const axios = require("axios"); (async() => { /* fetch JSON data and parse */ const url = "https://sheetjs.com/data/executive.json"; // highlight-next-line const raw_data = (await axios(url, {responseType: "json"})).data; /* filter for the Presidents */ const prez = raw_data.filter(row => row.terms.some(term => term.type === "prez")); /* sort by first presidential term */ prez.forEach(row => row.start = row.terms.find(term => term.type === "prez").start); prez.sort((l,r) => l.start.localeCompare(r.start)); /* flatten objects */ const rows = prez.map(row => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday })); /* generate worksheet and workbook */ const worksheet = XLSX.utils.json_to_sheet(rows); const workbook = XLSX.utils.book_new(); XLSX.utils.book_append_sheet(workbook, worksheet, "Dates"); /* fix headers */ XLSX.utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" }); /* calculate column width */ const max_width = rows.reduce((w, r) => Math.max(w, r.name.length), 10); worksheet["!cols"] = [ { wch: max_width } ]; /* create an XLSX file and try to save to Presidents.xlsx */ XLSX.writeFile(workbook, "Presidents.xlsx", { compression: true }); })(); ``` After saving the script, run the script: ```bash node SheetJSAxios.js ``` This script will write a new file `Presidents.xlsx` in the same folder.
:::
Other Server-Side Platforms (click to show) Save the following script to `SheetJSDeno.ts`: {`\ // @deno-types="https://cdn.sheetjs.com/xlsx-${current}/package/types/index.d.ts" import * as XLSX from 'https://cdn.sheetjs.com/xlsx-${current}/package/xlsx.mjs'; \n\ /* fetch JSON data and parse */ const url = "https://sheetjs.com/data/executive.json"; const raw_data = await (await fetch(url)).json(); \n\ /* filter for the Presidents */ const prez = raw_data.filter((row: any) => row.terms.some((term: any) => term.type === "prez")); \n\ /* sort by first presidential term */ prez.forEach(row => row.start = row.terms.find(term => term.type === "prez").start); prez.sort((l,r) => l.start.localeCompare(r.start)); \n\ /* flatten objects */ const rows = prez.map((row: any) => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday })); \n\ /* generate worksheet and workbook */ const worksheet = XLSX.utils.json_to_sheet(rows); const workbook = XLSX.utils.book_new(); XLSX.utils.book_append_sheet(workbook, worksheet, "Dates"); \n\ /* fix headers */ XLSX.utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" }); \n\ /* calculate column width */ const max_width = rows.reduce((w: number, r: any) => Math.max(w, r.name.length), 10); worksheet["!cols"] = [ { wch: max_width } ]; \n\ /* create an XLSX file and try to save to Presidents.xlsx */ XLSX.writeFile(workbook, "Presidents.xlsx", { compression: true });`} After saving the script, run the script: ```bash deno run -A SheetJSDeno.ts ``` This script will write a new file `Presidents.xlsx` in the same folder.
Save the following script to `SheetJSNW.html`: {`\ `} Save the following to `package.json`: {`\ { "name": "sheetjs-nwjs", "author": "sheetjs", "version": "0.0.0", "main": "SheetJSNW.html", "dependencies": { "nw": "0.77.0", "xlsx": "https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz" } }`} Install dependencies and run: ```bash npm i npx nw . ``` The app will show a save dialog. After selecting a path, it will write the file. :::note Initial Setup Follow the [Environment Setup](https://reactnative.dev/docs/environment-setup) of the React Native documentation before testing the demo. ::: :::caution pass For Android testing, React Native requires Java 11. It will not work with current Java releases. ::: Create a new project by running the following commands in the Terminal: {`\ npx -y react-native@0.72.4 init SheetJSPres --version="0.72.4" cd SheetJSPres \n\ npm i -S https://cdn.sheetjs.com/xlsx-${current}/xlsx-${current}.tgz react-native-blob-util@0.17.1`} Save the following to `App.tsx` in the project: ```js title="App.tsx" import React from 'react'; import { Alert, Button, SafeAreaView, Text, View } from 'react-native'; import { utils, version, write } from 'xlsx'; import RNBU from 'react-native-blob-util'; const make_workbook = async() => { /* fetch JSON data and parse */ const url = "https://sheetjs.com/data/executive.json"; const raw_data = await (await fetch(url)).json(); /* filter for the Presidents */ const prez = raw_data.filter(row => row.terms.some(term => term.type === "prez")); /* sort by first presidential term */ prez.forEach(row => row.start = row.terms.find(term => term.type === "prez").start); prez.sort((l,r) => l.start.localeCompare(r.start)); /* flatten objects */ const rows = prez.map(row => ({ name: row.name.first + " " + row.name.last, birthday: row.bio.birthday })); /* generate worksheet and workbook */ const worksheet = utils.json_to_sheet(rows); const workbook = utils.book_new(); utils.book_append_sheet(workbook, worksheet, "Dates"); /* fix headers */ utils.sheet_add_aoa(worksheet, [["Name", "Birthday"]], { origin: "A1" }); /* calculate column width */ const max_width = rows.reduce((w, r) => Math.max(w, r.name.length), 10); worksheet["!cols"] = [ { wch: max_width } ]; /* React Native does not support `writeFile`. This is a low-level write ! */ /* write workbook to buffer */ const buf = write(workbook, {type:'buffer', bookType:"xlsx"}); /* write buffer to file */ const filename = RNBU.fs.dirs.DocumentDir + "/Presidents.xlsx"; await RNBU.fs.writeFile(filename, Array.from(buf), 'ascii'); /* Copy to downloads directory (android) */ try { await RNBU.MediaCollection.copyToMediaStore({ parentFolder: "", mimeType: "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", name: "Presidents.xlsx" }, "Download", filename); } catch(e) {} return filename; }; const App = () => ( SheetJS {version} Export Demo