6.9 KiB
| title | pagination_prev | pagination_next | sidebar_custom_props | ||
|---|---|---|---|---|---|
| IndexedDB API | demos/desktop/index | demos/local/index |
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:::warning pass
IndexedDB is a very low-level API.
Browser vendors recommend using WebSQL or wrapper libraries in production applications.
:::
The IndexedDB API provides an in-browser sandboxed local data store for JSON objects. Like the Local Storage API, IndexedDB is a popular choice for offline storage.
Wrapper Libraries
A number of popular wrapper libraries seek to simplify IndexedDB operations.
:::note pass
The wrapper libraries in this section have been used by SheetJS users in production sites.
:::
localForage
:::note Tested Deployments
This demo was last tested in the following environments:
| Browser | Date | localForage |
|---|---|---|
| Chrome 122 | 2024-03-21 | 1.10.0 |
| Safari 17.4 | 2024-03-23 | 1.10.0 |
:::
localForage is a IndexedDB wrapper that presents an async Storage interface.
Arrays of objects can be stored using setItem using row index as key:
const aoo = XLSX.utils.sheet_to_json(ws);
for(var i = 0; i < aoo.length; ++i) await localForage.setItem(i, aoo[i]);
Recovering the array of objects involves an iteration over the storage:
const aoo = [];
await localforage.iterate((v, k) => { aoa[+k] = v; });
const ws = XLSX.utils.json_to_sheet(aoo);
Demo
This demo prepares a small IndexedDB database with some sample data.
After saving the exported file, the IndexedDB database can be inspected in the "IndexedDB" section of the "Application" Tab of Developer Tools:
function SheetJSLocalForage() {
const data = [
{ Name: "Barack Obama", Index: 44 },
{ Name: "Donald Trump", Index: 45 },
{ Name: "Joseph Biden", Index: 46 }
];
const xport = React.useCallback(async() => {
/* force use of IndexedDB and connect to DB */
localforage.config({
driver: [ localforage.INDEXEDDB ],
name: "SheetQL",
size: 2097152
});
/* create sample data */
await localforage.clear();
for(var i = 0; i < data.length; ++i) await localforage.setItem(i, data[i]);
/* pull data and generate aoa */
const aoo = [];
await localforage.iterate((v, k) => { aoo[+k] = v; });
/* export */
const ws = XLSX.utils.json_to_sheet(aoo);
const wb = XLSX.utils.book_new();
XLSX.utils.book_append_sheet(wb, ws, "Presidents");
XLSX.writeFile(wb, "SheetJSLocalForage.xlsx");
});
return ( <pre><button onClick={xport}><b>Do it!</b></button></pre> );
}
DexieJS
:::note Tested Deployments
This demo was last tested in the following environments:
| Browser | Date | DexieJS |
|---|---|---|
| Chrome 122 | 2024-03-21 | 3.2.4 |
:::
DexieJS is a minimalistic wrapper for IndexedDB. It provides a convenient interface for creating multiple logical tables, well-suited for workbooks.
Importing Data
When configuring tables, DexieJS needs a schema. The schema definition supports primary keys and other properties, but they are not required:
/* assuming `wb` is a workbook from XLSX.read */
var db = new Dexie("SheetJSDexie");
db.version(1).stores(Object.fromEntries(wb.SheetNames.map(n => ([n, "++"]))));
After the database is configured, bulkPut can insert arrays of objects:
/* loop over worksheet names */
for(let i = 0; i <= wb.SheetNames.length; ++i) {
/* get the worksheet for the specified index */
const wsname = wb.SheetNames[i];
const ws = wb.Sheets[wsname];
if(!ws) continue;
/* generate an array of objects */
const aoo = XLSX.utils.sheet_to_json(ws);
/* push to idb */
await db[wsname].bulkPut(aoo);
}
This demo inserts all data from a selected worksheet into a database, then fetches the data from the first worksheet in reverse.
After saving the exported file, the "IndexedDB" section of the "Application" Tab of Developer Tools will include a database named "SheetJSDexie".
/* The live editor requires this function wrapper */
function SheetJSDexieImport(props) {
const [__html, setHTML] = React.useState("Select a spreadsheet");
return ( <>
<input type="file" onChange={async(e) => { try {
/* get data as an ArrayBuffer */
const file = e.target.files[0];
const data = await file.arrayBuffer();
/* parse worksheet */
const wb = XLSX.read(data);
/* load into indexeddb */
await Dexie.delete("SheetJSDexie");
const db = new Dexie("SheetJSDexie");
const wsnames = wb.SheetNames.map(n => ([n, "++"]));
db.version(1).stores(Object.fromEntries(wsnames));
/* loop over worksheet names */
for(let i = 0; i <= wb.SheetNames.length; ++i) {
/* get the worksheet for the specified index */
const wsname = wb.SheetNames[i];
const ws = wb.Sheets[wsname];
if(!ws) continue;
/* generate an array of objects */
const aoo = XLSX.utils.sheet_to_json(ws);
/* push to idb */
await db[wsname].bulkPut(aoo);
}
/* fetch the first table in reverse order */
const rev = await db[wb.SheetNames[0]].reverse().toArray();
setHTML(rev.map(r => JSON.stringify(r)).join("\n"));
} catch(e) { setHTML(e && e.message || e); }}}/>
<pre dangerouslySetInnerHTML={{ __html }}/>
</> );
}
Exporting Data
db.tables is a plain array of table objects. toArray fetches data:
/* create blank workbook */
const wb = XLSX.utils.book_new();
/* loop tables */
for(const table of db.tables) {
/* get data */
const aoo = await table.toArray();
/* create worksheet */
const ws = XLSX.utils.json_to_sheet(aoo);
/* add to workbook */
XLSX.utils.book_append_sheet(wb, ws, table.name);
}
This demo prepares a small database with some sample data.
function SheetJSDexieExport() {
const data = [
{ Name: "Barack Obama", Index: 44 },
{ Name: "Donald Trump", Index: 45 },
{ Name: "Joseph Biden", Index: 46 }
];
const xport = React.useCallback(async() => {
/* prepare db */
await Dexie.delete("SheetJSDexie");
var db = new Dexie("SheetJSDexie");
db.version(1).stores({ Presidents: "++" });
db.Presidents.bulkPut(data);
/* pull data and generate workbook */
const wb = XLSX.utils.book_new();
for(const table of db.tables) {
const aoo = await table.toArray();
const ws = XLSX.utils.json_to_sheet(aoo);
XLSX.utils.book_append_sheet(wb, ws, table.name);
}
XLSX.writeFile(wb, "SheetJSDexie.xlsx");
});
return ( <pre><button onClick={xport}><b>Do it!</b></button></pre> );
}