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@rowsncolumns/loro

v9.0.1

Published

Loro CRDT-based real-time collaboration adapter for Rows n Columns Spreadsheet.

Downloads

55

Readme

@rowsncolumns/loro

Loro CRDT-based real-time collaboration adapter for Rows n Columns Spreadsheet.

This adapter stores spreadsheet data directly in a Loro document using CRDTs (Conflict-free Replicated Data Types) for real-time synchronization.

Features

  • Real-time collaboration with CRDT-based conflict resolution
  • Flat map data structure for efficient cell operations
  • Presence awareness (see other users' cursors)
  • Leader election for recalc coordination
  • Full offline support - work offline and sync later
  • Full support for sheets, tables, charts, embeds, named ranges, and more

Why Loro for Spreadsheets?

Loro is a high-performance CRDT library that provides automatic conflict resolution without requiring a central server.

Comparison with ShareDB (OT)

| Aspect | Loro (CRDT) | ShareDB (OT) | | ----------------------- | ------------------------------------- | --------------------------------- | | Conflict resolution | Automatic merge, eventual consistency | Server determines canonical order | | Offline support | Full offline-first support | Requires server connection | | Server required | Optional (can sync peer-to-peer) | Yes, server is mandatory | | Performance | Highly optimized Rust core (WASM) | JavaScript-based | | History/Time travel | Built-in version history | Manual operation log | | Recalculation | Leader election for coordination | Leader election for coordination |

When to Choose Loro

  • Offline-first requirements - Users need to work without connectivity
  • High performance - Loro's Rust core provides excellent performance
  • Flexible sync - Can work with any transport (WebSocket, WebRTC, etc.)
  • Version history - Built-in support for time travel and history

When to Choose ShareDB

  • Server authority - Need central server to be source of truth
  • Existing infrastructure - Already using MongoDB/PostgreSQL with ShareDB
  • Simpler mental model - OT's sequential operations may be easier to reason about

Installation

npm install @rowsncolumns/loro loro-crdt

Quick Start

import { useLoro } from "@rowsncolumns/loro";
import { LoroDoc } from "loro-crdt";

// Create a Loro document
const doc = new LoroDoc();

function SpreadsheetEditor() {
  const [sheetData, setSheetData] = useState({});
  const [sheets, setSheets] = useState([]);
  const [tables, setTables] = useState([]);

  const { onBroadcastPatch, users, synced, isLeader, importUpdate } = useLoro({
    doc,
    userId: "user-123",
    title: "John Doe",
    sheetId: 1,
    activeCell: { rowIndex: 1, columnIndex: 1 },
    initialSheets: [],
    onChangeSheetData: setSheetData,
    onChangeSheets: setSheets,
    onChangeTables: setTables,
    enqueueGraphOperation: (op) => {
      // Handle dependency graph updates
    },
    calculateNow: async () => {
      // Trigger recalculation
    },
    // Optional: handle sync updates for broadcasting to other clients
    onSyncUpdate: (update) => {
      // Send update to server/peers
      websocket.send(update);
    },
    // Optional: handle presence updates
    onPresenceUpdate: (presence) => {
      websocket.send(JSON.stringify({ type: "presence", data: presence }));
    },
    remotePresences: {}, // Presences from other clients
  });

  // Pass onBroadcastPatch to your spreadsheet component
  return (
    <Spreadsheet
      sheetData={sheetData}
      sheets={sheets}
      onBroadcastPatch={onBroadcastPatch}
      users={users}
    />
  );
}

Setting Up a Sync Server

Basic WebSocket Server

Create a file server.ts:

import http from "http";
import express from "express";
import { WebSocketServer, WebSocket } from "ws";
import { LoroDoc } from "loro-crdt";

// Store documents in memory (use a database in production)
const documents = new Map<string, Uint8Array>();
const documentClients = new Map<string, Set<WebSocket>>();
const documentPresences = new Map<string, Map<string, unknown>>();

const app = express();
const server = http.createServer(app);
const wss = new WebSocketServer({ server });

wss.on("connection", (ws) => {
  let currentDocId: string | null = null;
  let currentUserId: string | null = null;

  ws.on("message", (rawData) => {
    const message = JSON.parse(rawData.toString());

    switch (message.type) {
      case "join": {
        currentDocId = message.docId;
        currentUserId = message.userId;

        // Add client to document
        if (!documentClients.has(message.docId)) {
          documentClients.set(message.docId, new Set());
        }
        documentClients.get(message.docId)!.add(ws);

        // Send current document state
        const state = documents.get(message.docId);
        if (state) {
          ws.send(
            JSON.stringify({
              type: "snapshot",
              docId: message.docId,
              data: Buffer.from(state).toString("base64"),
            }),
          );
        }

        // Send existing presences
        const presences = documentPresences.get(message.docId);
        if (presences) {
          for (const [userId, data] of presences.entries()) {
            if (userId !== message.userId) {
              ws.send(JSON.stringify({ type: "presence", userId, data }));
            }
          }
        }
        break;
      }

      case "update": {
        if (!message.docId) break;

        // Decode and apply update
        const update = Buffer.from(message.data, "base64");

        // Update server's copy
        let serverDoc = new LoroDoc();
        const existingState = documents.get(message.docId);
        if (existingState) {
          serverDoc.import(existingState);
        }
        serverDoc.import(update);
        documents.set(message.docId, serverDoc.export({ mode: "snapshot" }));

        // Broadcast to other clients
        const clients = documentClients.get(message.docId);
        if (clients) {
          for (const client of clients) {
            if (client !== ws && client.readyState === WebSocket.OPEN) {
              client.send(JSON.stringify(message));
            }
          }
        }
        break;
      }

      case "presence": {
        // Store and broadcast presence
        if (!documentPresences.has(message.docId)) {
          documentPresences.set(message.docId, new Map());
        }
        documentPresences.get(message.docId)!.set(message.userId, message.data);

        const clients = documentClients.get(message.docId);
        if (clients) {
          for (const client of clients) {
            if (client !== ws && client.readyState === WebSocket.OPEN) {
              client.send(JSON.stringify(message));
            }
          }
        }
        break;
      }
    }
  });

  ws.on("close", () => {
    if (currentDocId && currentUserId) {
      // Remove client and broadcast presence leave
      documentClients.get(currentDocId)?.delete(ws);
      documentPresences.get(currentDocId)?.delete(currentUserId);

      const clients = documentClients.get(currentDocId);
      if (clients) {
        for (const client of clients) {
          client.send(
            JSON.stringify({
              type: "presence-leave",
              userId: currentUserId,
            }),
          );
        }
      }
    }
  });
});

server.listen(8081, () => {
  console.log("Loro sync server running on port 8081");
});

Run the Server

npx tsx server.ts

Or add to your package.json:

{
  "scripts": {
    "server": "tsx server.ts"
  }
}

Document Structure

The Loro document uses V3 format with a flat map for cell data:

type LoroSpreadsheetDoc = {
  // Cell data: flat map with keys like "1!A1" -> CellDataV3
  sheetData: Record<string, CellDataV3>;

  // Sheet definitions
  sheets: Sheet[];

  // Tables, charts, embeds
  tables: TableView[];
  charts: EmbeddedChart[];
  embeds: EmbeddedObject[];

  // Named ranges, protected ranges
  namedRanges: NamedRange[];
  protectedRanges: ProtectedRange[];

  // Conditional formats, data validations
  conditionalFormats: ConditionalFormatRule[];
  dataValidations: DataValidationRuleRecord[];

  // Pivot tables
  pivotTables: PivotTable[];

  // Cell formats and shared strings
  cellXfs: Record<string, CellFormat>;
  sharedStrings: Record<string, string>;

  // Recalc coordination
  recalcCells: RecalcCellEntry[];
};

Cell Key Format (V3)

Cell keys follow the pattern ${sheetId}!${A1Address}:

  • "1!A1" - Cell A1 on sheet 1
  • "2!B5" - Cell B5 on sheet 2
  • "1!AA100" - Cell AA100 on sheet 1

CellDataV3 Structure

Each cell value is wrapped in a CellDataV3 object with flattened position:

type CellDataV3<T> = {
  value: T; // The cell data (formula, value, formatting, etc.)
  sId: number; // Sheet ID
  r: number; // Row index
  c: number; // Column index
};

API Reference

useLoro

const {
  onBroadcastPatch,
  users,
  synced,
  isLeader,
  importUpdate,
  exportUpdate,
  exportSnapshot,
} = useLoro(props);

Props

| Prop | Type | Required | Description | | ---------------------------- | -------------------------------------- | -------- | -------------------------------------- | | doc | LoroDoc | Yes | Loro document instance | | userId | string \| number | Yes | Current user's ID | | title | string | Yes | User's display name | | sheetId | number | Yes | Currently active sheet ID | | activeCell | CellInterface | No | Current active cell position | | initialSheets | Sheet[] | Yes | Initial sheets if document is empty | | disable | boolean | No | Disable collaboration | | onChangeSheetData | Dispatch<SetStateAction> | Yes | Sheet data state setter | | onChangeSheets | Dispatch<SetStateAction> | Yes | Sheets state setter | | onChangeTables | Dispatch<SetStateAction> | Yes | Tables state setter | | onChangeCharts | Dispatch<SetStateAction> | No | Charts state setter | | onChangeEmbeds | Dispatch<SetStateAction> | No | Embeds state setter | | onChangeNamedRanges | Dispatch<SetStateAction> | No | Named ranges setter | | onChangeProtectedRanges | Dispatch<SetStateAction> | No | Protected ranges setter | | onChangeConditionalFormats | Dispatch<SetStateAction> | No | Conditional formats setter | | onChangeDataValidations | Dispatch<SetStateAction> | No | Data validations setter | | onChangePivotTables | Dispatch<SetStateAction> | No | Pivot tables setter | | onChangeCellXfs | Dispatch<SetStateAction> | No | Cell formats setter | | onChangeSharedStrings | Dispatch<SetStateAction> | No | Shared strings setter | | onChangeActiveSheet | (sheetId: number) => void | No | Active sheet change handler | | enqueueGraphOperation | (op: CalculationOperation) => void | Yes | Graph operation handler | | calculateNow | (options?) => Promise<void> | Yes | Trigger recalculation | | onSyncUpdate | (update: Uint8Array) => void | No | Callback for sync updates to broadcast | | onPresenceUpdate | (presence: LoroPresenceData) => void | No | Callback for presence updates | | remotePresences | Record<string, LoroPresenceData> | No | Remote presences from other clients | | onError | (err: unknown) => void | No | Error callback |

Return Value

| Property | Type | Description | | ------------------ | ------------------------------ | ----------------------------------- | | onBroadcastPatch | Function | Callback to broadcast local changes | | users | Collaborator[] | List of connected collaborators | | synced | boolean | Whether initial sync is complete | | isLeader | boolean | Whether this client is the leader | | importUpdate | (update: Uint8Array) => void | Import an update from a remote peer | | exportUpdate | () => Uint8Array \| null | Export current state as update | | exportSnapshot | () => Uint8Array \| null | Export current state as snapshot |

Leader Election

The adapter uses a simple leader election mechanism based on user IDs. The client with the alphabetically first user ID becomes the leader. The leader is responsible for:

  • Coordinating recalc cell cleanup
  • Full recalculation operations
const { isLeader } = useLoro({ ... });

if (isLeader) {
  // This client is responsible for leader tasks
}

Presence Awareness

Connected users are exposed via the users array:

const { users } = useLoro({ ... });

// users: Collaborator[]
// Each collaborator has: { userId, title, sheetId, activeCell }

Offline Support

Loro CRDTs work fully offline. Changes made while offline are stored locally and automatically merged when reconnecting:

// Work offline - changes are stored locally
onBroadcastPatch(patches);

// When back online, export and sync
const update = exportUpdate();
if (update) {
  websocket.send(update);
}

// Import updates from server
websocket.onmessage = (event) => {
  importUpdate(new Uint8Array(event.data));
};

Error Handling

Provide an onError callback to handle errors:

useLoro({
  // ...
  onError: (err) => {
    console.error("Loro error:", err);
    // Handle error (show toast, reconnect, etc.)
  },
});

Helper Functions

The adapter exports helper functions for working with Loro documents:

import {
  applyLoroUpdate,
  exportLoroUpdate,
  exportLoroSnapshot,
} from "@rowsncolumns/loro";

// Apply an update from a remote peer
applyLoroUpdate(doc, update);

// Export current state as update (for incremental sync)
const update = exportLoroUpdate(doc);

// Export current state as snapshot (for full sync)
const snapshot = exportLoroSnapshot(doc);

License

MIT