evernote-rate-limits

Evernote Rate Limits

Overview

Evernote enforces rate limits per API key, per user. When exceeded, the API throws EDAMSystemException with errorCode: RATE_LIMIT_REACHED and rateLimitDuration (seconds to wait). Production integrations must handle this gracefully.

Prerequisites

• Evernote SDK setup
• Understanding of async/await patterns
• Error handling implementation

Instructions

Step 1: Rate Limit Handler

Catch EDAMSystemException and check for rateLimitDuration. Implement exponential backoff: wait the specified duration, then retry. Track retry attempts to avoid infinite loops.

async function withRateLimitRetry(operation, maxRetries = 3) {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await operation();
    } catch (error) {
      if (error.rateLimitDuration && attempt < maxRetries - 1) {
        const waitMs = error.rateLimitDuration * 1000;
        console.log(`Rate limited. Waiting ${error.rateLimitDuration}s...`);
        await new Promise(r => setTimeout(r, waitMs));
        continue;
      }
      throw error;
    }
  }
}

Step 2: Rate-Limited Client Wrapper

Wrap the NoteStore with a class that adds configurable delays between API calls. Use a request queue to prevent bursts. Track request timestamps for monitoring.

class RateLimitedClient {
  constructor(noteStore, minDelayMs = 100) {
    this.noteStore = noteStore;
    this.minDelayMs = minDelayMs;
    this.lastRequestTime = 0;
  }

  async call(method, ...args) {
    const elapsed = Date.now() - this.lastRequestTime;
    if (elapsed < this.minDelayMs) {
      await new Promise(r => setTimeout(r, this.minDelayMs - elapsed));
    }
    this.lastRequestTime = Date.now();
    return withRateLimitRetry(() => this.noteStore[method](...args));
  }
}

Step 3: Batch Operations with Rate Limiting

Process items sequentially with delay between each operation. On rate limit, wait and retry the failed item. Report progress via callback. Collect successes and failures.

Step 4: Avoiding Rate Limits

Strategies to minimize API calls: cache listNotebooks() and listTags() results, use findNotesMetadata() instead of getNote() for listings, request only needed fields in NotesMetadataResultSpec, batch reads with sync chunks instead of individual fetches.

Step 5: Rate Limit Monitoring

Track request counts, rate limit hits, average response times, and wait times. Log statistics periodically to identify optimization opportunities.

For the complete rate limiter, batch processor, monitoring dashboard, and optimization examples, see Implementation Guide.

Output

• Automatic retry with exponential backoff on rate limit errors
• Request queue with configurable minimum delay between calls
• Batch processor with progress tracking and failure collection
• Rate limit monitoring with request/error statistics
• API call optimization strategies (caching, metadata-only queries)

Error Handling

Scenario	Response
First rate limit hit	Wait rateLimitDuration seconds, retry
Repeated rate limits	Increase minDelayMs, reduce batch size
Rate limit during sync	Pause sync, wait, resume from last USN
Rate limit on initial setup	Request rate limit boost from Evernote support

Resources

• Rate Limits Overview
• API Best Practices
• Webhooks (reduce polling)

Next Steps

For security considerations, see evernote-security-basics.

Examples

Batch note export: Export 1,000 notes with 200ms delay between API calls and automatic retry on rate limits. Track progress and report failures at the end.

High-throughput sync: Use getFilteredSyncChunk() to fetch changes in bulk (100 entries per call) instead of individual getNote() calls, reducing API call count by 100x.