Lokalise Performance Tuning

Lokalise Performance Tuning

Overview

Optimize Lokalise API throughput for translation pipelines by implementing cursor pagination, local caching, batch key operations (500/​request), request throttling under the 6 req/​s rate limit, and selective language downloads.

Prerequisites

• @lokalise/​node-api SDK v9+ (ESM) or REST API access
• LOKALISE_API_TOKEN environment variable set
• Understanding of project size (key count, language count) to calibrate batch sizes
• Optional: Redis or LRU cache library for persistent caching

Instructions

Step 1: Use Cursor Pagination for Large Datasets

Cursor pagination is significantly faster than offset pagination for projects with 5K+ keys. Offset pagination degrades as page numbers increase because the server must skip rows; cursor pagination uses a pointer.

import { LokaliseApi } from '@lokalise/​node-api';
const lok = new LokaliseApi({ apiKey: process.env.LOKALISE_API_TOKEN! });

// Generator that yields all keys using cursor pagination
async function* getAllKeys(projectId: string) {
  let cursor: string | undefined;
  do {
    const result = await lok.keys().list({
      project_id: projectId,
      limit: 500,              // Maximum allowed per request
      pagination: 'cursor',
      cursor,
    });
    for (const key of result.items) yield key;
    cursor = result.hasNextCursor() ? result.nextCursor : undefined;
  } while (cursor);
}

// Usage: 10,000 keys = 20 API calls (vs 100 with default limit=100)
let count = 0;
for await (const key of getAllKeys('PROJECT_ID')) {
  count++;
}
console.log(`Fetched ${count} keys`);

Offset pagination comparison (avoid for large projects):

Step 2: Cache Translation Downloads Locally

Translation file downloads are the most expensive Lokalise operation. Cache them locally and use project last_activity timestamps to invalidate.

import { LokaliseApi } from '@lokalise/​node-api';
import { readFileSync, writeFileSync, existsSync, mkdirSync } from 'fs';

const lok = new LokaliseApi({ apiKey: process.env.LOKALISE_API_TOKEN! });
const CACHE_DIR = '.lokalise-cache';

interface CacheEntry {
  url: string;
  timestamp: string;
  languages: string[];
}

function getCachePath(projectId: string, langIso: string): string {
  return `${CACHE_DIR}/​${projectId}/​${langIso}.json`;
}

function getMetaPath(projectId: string): string {
  return `${CACHE_DIR}/​${projectId}/​meta.json`;
}

async function downloadWithCache(projectId: string, langIso: string, format = 'json') {
  mkdirSync(`${CACHE_DIR}/​${projectId}`, { recursive: true });
  const cachePath = getCachePath(projectId, langIso);
  const metaPath = getMetaPath(projectId);

  // Check if project was modified since last cache
  const project = await lok.projects().get(projectId);
  const lastActivity = project.statistics?.last_activity ?? project.created_at;

  if (existsSync(metaPath)) {
    const meta: CacheEntry = JSON.parse(readFileSync(metaPath, 'utf8'));
    if (meta.timestamp === lastActivity && existsSync(cachePath)) {
      console.log(`Cache hit: ${langIso} (unchanged since ${lastActivity})`);
      return JSON.parse(readFileSync(cachePath, 'utf8'));
    }
  }

  // Cache miss — download fresh
  const bundle = await lok.files().download(projectId, {
    format,
    filter_langs: [langIso],
    original_filenames: false,
  });

  // bundle.bundle_url contains a temporary download URL
  const response = await fetch(bundle.bundle_url);
  const data = await response.arrayBuffer();

  writeFileSync(cachePath, Buffer.from(data));
  writeFileSync(metaPath, JSON.stringify({
    url: bundle.bundle_url,
    timestamp: lastActivity,
    languages: [langIso],
  }));

  console.log(`Cache miss: downloaded ${langIso} (${data.byteLength} bytes)`);
  return data;
}

Step 3: Batch Key Operations

Lokalise supports creating, updating, and deleting up to 500 keys per request. Always batch instead of making individual requests.

// Bulk create keys — 500 per batch with rate limit awareness
async function createKeysBatched(projectId: string, keys: any[]) {
  const BATCH_SIZE = 500;
  const results = [];

  for (let i = 0; i < keys.length; i += BATCH_SIZE) {
    const batch = keys.slice(i, i + BATCH_SIZE);
    const result = await lok.keys().create({
      project_id: projectId,
      keys: batch,
    });
    results.push(...result.items);
    console.log(`Batch ${Math.floor(i / BATCH_SIZE) + 1}: created ${result.items.length} keys`);
    await new Promise(r => setTimeout(r, 200)); // Stay under 6 req/​s
  }

  return results;
}

// Bulk update keys — same 500-key batch limit
async function updateKeysBatched(projectId: string, updates: Array<{key_id: number; [k: string]: any}>) {
  const BATCH_SIZE = 500;
  for (let i = 0; i < updates.length; i += BATCH_SIZE) {
    const batch = updates.slice(i, i + BATCH_SIZE);
    await lok.keys().bulk_update({
      project_id: projectId,
      keys: batch,
    });
    await new Promise(r => setTimeout(r, 200));
  }
}

// Bulk delete — up to 500 key IDs per request
async function deleteKeysBatched(projectId: string, keyIds: number[]) {
  const BATCH_SIZE = 500;
  for (let i = 0; i < keyIds.length; i += BATCH_SIZE) {
    const batch = keyIds.slice(i, i + BATCH_SIZE);
    await lok.keys().bulk_delete({
      project_id: projectId,
      keys: batch,
    });
    await new Promise(r => setTimeout(r, 200));
  }
}

// 2,000 keys: 4 batched requests instead of 2,000 individual ones

Step 4: Implement Request Throttling

A proper request queue prevents 429 Too Many Requests errors and makes your integration resilient under load.

import PQueue from 'p-queue';

// Lokalise rate limit: 6 requests/​second
// Use 5 concurrent with 1s interval for safety margin
const queue = new PQueue({
  concurrency: 5,
  interval: 1000,
  intervalCap: 5,
});

async function throttledRequest<T>(fn: () => Promise<T>): Promise<T> {
  return queue.add(fn) as Promise<T>;
}

// All API calls go through the queue automatically
const project = await throttledRequest(() => lok.projects().get(projectId));
const keys = await throttledRequest(() => lok.keys().list({
  project_id: projectId,
  limit: 500,
  pagination: 'cursor',
}));

// Works for parallel operations too — queue enforces the rate limit
const projectIds = ['PROJ_1', 'PROJ_2', 'PROJ_3', 'PROJ_4', 'PROJ_5'];
const allProjects = await Promise.all(
  projectIds.map(id => throttledRequest(() => lok.projects().get(id)))
);

Step 5: Async File Operations with Webhooks

File uploads and downloads are processed asynchronously by Lokalise. Instead of polling the process status endpoint, use webhooks to get notified when processing completes.

set -euo pipefail
# Set up a webhook for file operation events
curl -s -X POST "https://api.lokalise.com/​api2/​projects/​${PROJECT_ID}/​webhooks" \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  -H "Content-Type: application/​json" \
  -d '{
    "url": "https://hooks.company.com/​lokalise",
    "events": [
      "project.imported",
      "project.exported",
      "project.keys_added"
    ]
  }' | jq '{webhook_id: .webhook.webhook_id, url: .webhook.url, events: .webhook.events}'

If you must poll (no webhook endpoint available):

async function waitForProcess(projectId: string, processId: string, timeoutMs = 120_000) {
  const start = Date.now();
  while (Date.now() - start < timeoutMs) {
    const proc = await throttledRequest(() =>
      lok.queuedProcesses().get(projectId, processId)
    );
    if (proc.status === 'finished') return proc;
    if (proc.status === 'cancelled' || proc.status === 'failed') {
      throw new Error(`Process ${processId} ${proc.status}: ${proc.message}`);
    }
    await new Promise(r => setTimeout(r, 2000)); // Poll every 2s
  }
  throw new Error(`Process ${processId} timed out after ${timeoutMs}ms`);
}

Step 6: Selective Language Downloads (Delta Exports)

Downloading all languages when you only need one wastes bandwidth and API time. Always filter by language and, when possible, by modification timestamp.

// Download only changed translations since last sync
async function downloadDelta(projectId: string, langIso: string, sinceTimestamp: string) {
  // Filter keys modified after the given timestamp
  const keys = await lok.keys().list({
    project_id: projectId,
    limit: 500,
    pagination: 'cursor',
    filter_translation_lang_ids: langIso,
    // Unfortunately, Lokalise doesn't support filter_modified_after on keys endpoint.
    // Workaround: download full file and diff locally, or use webhooks for real-time sync.
  });

  return keys.items;
}

// Download a single language file instead of all languages
async function downloadSingleLanguage(projectId: string, langIso: string) {
  const result = await lok.files().download(projectId, {
    format: 'json',
    filter_langs: [langIso],        // Only this language
    original_filenames: false,       // Flat structure
    bundle_structure: '%LANG_ISO%.%FORMAT%', // e.g., fr.json
    export_empty_as: 'base',         // Fall back to base language for untranslated
    include_tags: ['production'],    // Only production-tagged keys
  });
  return result.bundle_url;
}

Step 7: Measure and Benchmark

set -euo pipefail
# Benchmark API response times across endpoints
echo "=== Lokalise API Benchmarks ==="

echo -n "Projects list: "
curl -s -o /​dev/​null -w "%{time_total}s" \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/​api2/​projects?limit=10"
echo ""

echo -n "Keys list (limit=500): "
curl -s -o /​dev/​null -w "%{time_total}s" \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/​api2/​projects/​${PROJECT_ID}/​keys?limit=500"
echo ""

echo -n "File download trigger: "
curl -s -o /​dev/​null -w "%{time_total}s" \
  -X POST -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  -H "Content-Type: application/​json" \
  "https://api.lokalise.com/​api2/​projects/​${PROJECT_ID}/​files/​download" \
  -d '{"format":"json","filter_langs":["en"],"original_filenames":false}'
echo ""

echo -n "Rate limit headers: "
curl -s -D - -o /​dev/​null \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/​api2/​projects?limit=1" \
  | grep -i x-ratelimit

Output

• Cursor pagination implemented for all list operations (80% fewer API calls)
• Translation download cache with timestamp-based invalidation
• Batch key operations (create/​update/​delete) using 500-key batches
• Request queue with PQueue throttling at 5 req/​s (safety margin under 6 req/​s limit)
• Webhooks configured for async file operations (replacing polling)
• Selective language downloads reducing bandwidth and processing time
• Benchmark results for baseline performance measurement

Error Handling

Examples

Quick Rate Limit Check

set -euo pipefail
# See how much rate limit headroom you have right now
curl -s -D - -o /​dev/​null \
  -H "X-Api-Token: ${LOKALISE_API_TOKEN}" \
  "https://api.lokalise.com/​api2/​system/​languages?limit=1" 2>/​dev/​null \
  | grep -iE 'x-ratelimit' | while read -r line; do echo "  $line"; done

Resources

• Lokalise Rate Limits
• Cursor Pagination Docs
• File Download API
• Bulk Key Operations
• Webhook Events
• p-queue (npm)

Next Steps

• For debugging performance issues, collect diagnostics with lokalise-debug-bundle.
• For SDK upgrade to get latest pagination improvements, see lokalise-upgrade-migration.
• For setting up CI pipelines with optimized API usage, see lokalise-ci-integration.