Best Practices

Master the art of building secure, performant, and maintainable applications with CocoBase.

Security Best Practices

API Key Management

Never Hard-Code API Keys:

Flutter
JavaScript
Python
Go

// Bad - hardcoded credentials
final config = CocobaseConfig(
  apiKey: "hardcoded-key",  // DON'T DO THIS
);

// Good - use environment variables
const apiKey = String.fromEnvironment('COCOBASE_API_KEY');
final config = CocobaseConfig(apiKey: apiKey);

// Good - load from secure storage
final prefs = await SharedPreferences.getInstance();
final apiKey = prefs.getString('cocobase_api_key');
final config = CocobaseConfig(apiKey: apiKey!);

// Bad - hardcoded credentials
const config = {
  apiKey: "hardcoded-key",  // DON'T DO THIS
};

// Good - use environment variables
const config = {
  apiKey: process.env.COCOBASE_API_KEY,
};

// Good - use .env file
import dotenv from 'dotenv';
dotenv.config();

const config = {
  apiKey: process.env.COCOBASE_API_KEY,
};

# Bad - hardcoded credentials
config = CocobaseConfig(
    api_key="hardcoded-key"  # DON'T DO THIS
)

# Good - use environment variables

import os

config = CocobaseConfig(
api_key=os.getenv('COCOBASE_API_KEY')
)

// Bad - hardcoded credentials
config := cocobase.Config{
    APIKey: "hardcoded-key",  // DON'T DO THIS
}

// Good - use environment variables
config := cocobase.Config{
    APIKey: os.Getenv("COCOBASE_API_KEY"),
}

Rotate API Keys Regularly:

Generate new API keys every 90 days
Revoke old keys after migration
Use different keys for development, staging, and production
Never commit API keys to version control

Add to .gitignore:

# .gitignore
.env
.env.local
config/secrets.json
**/secrets/

Authentication Security

Always Verify User Authentication:

Python Cloud Functions
Flutter
JavaScript

def main():
    # Check if user is authenticated
    user = req.user

    if not user:
        return {"error": "Authentication required"}, 401

    # Proceed with authenticated operations
    return {"user_id": user.id}

Future<void> performSecureOperation() async {
  // Check authentication first
  final isAuth = await db.isAuthenticated();
  if (!isAuth) {
    throw Exception('Authentication required');
  }

  // Proceed with operation
  await db.createDocument("posts", data);
}

async function performSecureOperation() {
  // Check authentication first
  const isAuth = await db.isAuthenticated();
  if (!isAuth) {
    throw new Error('Authentication required');
  }

// Proceed with operation
await db.createDocument('posts', data);
}

Implement Role-Based Access Control:

def main():
    user = req.user

    if not user:
        return {"error": "Authentication required"}, 401

    # Check user roles
    if 'admin' not in user.roles:
        return {"error": "Forbidden - admin access required"}, 403

    # Perform admin operation
    result = perform_admin_action()
    return {"result": result}

Input Validation

Always Validate User Input:

Python
Flutter

def main():
    email = req.get('email', '').strip()
    password = req.get('password', '')

    # Validate email
    if not email or '@' not in email:
        return {"error": "Invalid email format"}, 400

    # Validate password strength
    if len(password) < 8:
        return {"error": "Password must be at least 8 characters"}, 400

    # Proceed with registration
    user = db.create_app_user(email, password)
    return {"user": user}

Future<void> createPost(String title, String content) async {
  // Validate title
  if (title.trim().isEmpty) {
    throw ArgumentError('Title is required');
  }

  if (title.length > 200) {
    throw ArgumentError('Title too long (max 200 characters)');
  }

  // Validate content
  if (content.trim().isEmpty) {
    throw ArgumentError('Content is required');
  }

  if (content.length > 10000) {
    throw ArgumentError('Content too long (max 10000 characters)');
  }

  // Create post
  await db.createDocument('posts', {
    'title': title.trim(),
    'content': content.trim(),
  });
}

Sanitize User Input:

function sanitizeInput(input) {
  // Remove HTML tags
  return input.replace(/<[^>]*>/g, "");
}

function createPost(title, content) {
  const sanitizedTitle = sanitizeInput(title.trim());
  const sanitizedContent = sanitizeInput(content.trim());

  return db.createDocument("posts", {
    title: sanitizedTitle,
    content: sanitizedContent,
  });
}

Data Modeling Best Practices

Schema Design

Use Clear, Descriptive Field Names:

// Good - clear intent
{
  "author_id": "user-123",        // Obviously a user reference
  "product_ids": ["p1", "p2"],    // Obviously multiple products
  "is_published": true,           // Boolean clarity
}

// Bad - ambiguous names
{
  "related": "...",      // Related to what?
  "ids": ["..."],        // IDs of what?
  "flag": true,          // Flag for what?
}

Normalize Data Appropriately:

// Good - normalized structure
const user = {
  id: "user-123",
  name: "John Doe",
  company_id: "company-456", // Reference to company
};

const company = {
  id: "company-456",
  name: "TechCorp",
  address: "123 Main St",
};

// Bad - denormalized (duplicated data)
const user = {
  id: "user-123",
  name: "John Doe",
  company_name: "TechCorp", // Duplicated
  company_address: "123 Main St", // Duplicated
};

Use Appropriate Data Types:

# Good - appropriate types
document = {
    "price": 29.99,           # Number, not string
    "quantity": 5,            # Integer
    "is_available": True,     # Boolean, not string
    "tags": ["tech", "new"],  # Array
    "created_at": "2024-01-15T10:30:00Z"  # ISO 8601 timestamp
}

# Bad - wrong types
document = {
    "price": "29.99",         # String instead of number
    "quantity": "5",          # String instead of int
    "is_available": "true",   # String instead of boolean
    "tags": "tech,new",       # String instead of array
    "created_at": "01/15/2024"  # Non-standard date format
}

Relationship Management

Follow Naming Conventions:

// Single references use id suffix
{
  "author_id": "user-123",
  "category_id": "cat-456",
  "company_id": "comp-789"
}

// Multiple references use _ids suffix
{
  "tag_ids": ["tag-1", "tag-2"],
  "follower_ids": ["user-4", "user-5"],
  "product_ids": ["prod-1", "prod-2", "prod-3"]
}

Cache Relationship Counts:

# Store counts for quick access
user_data = {
    "followers_count": 1500,  # Update when changed
    "following_count": 300,
    "posts_count": 42
}

# Instead of counting every time
# followers = db.get_user_relationships(user_id, "followers")
# count = followers["total"]  # Expensive!

Efficient Queries

Use Specific Queries:

// Good - specific query
final query = QueryBuilder()
  .where('status', 'published')
  .where('author_id', userId)
  .limit(50);

final docs = await db.listDocuments("posts", queryBuilder: query);

// Bad - fetching everything then filtering
final all = await db.listDocuments("posts");
final filtered = all.where((doc) =>
  doc.data['status'] == 'published' &&
  doc.data['author_id'] == userId
).toList();

Always Set Limits:

# Good - limited results
posts = db.list_documents("posts",
    status="published",
    limit=20  # Prevent loading too much
)

# Bad - no limit (could return millions)
posts = db.list_documents("posts",
    status="published"
)

Use Pagination:

// Good - paginate results
async function getAllUsers() {
  const users = [];
  let page = 1;
  const perPage = 100;
  let hasMore = true;

  while (hasMore) {
    const result = await db.listDocuments("users", {
      filters: {
        limit: perPage,
        offset: (page - 1) * perPage,
      }
    });

    users.push(...result);
    hasMore = result.length === perPage;
    page++;
  }

  return users;
}

// Bad - fetch everything at once
const users = await db.listDocuments("users");

Select Only Needed Fields:

// Good - select specific fields
final docs = await db.listDocuments(
  "books",
  queryBuilder: QueryBuilder()
    .select('id')
    .select('title')
    .select('price')
    .limit(100),
);

// Bad - fetch all fields
final docs = await db.listDocuments("books");

Use Populate Wisely:

# Good - selective population
posts = db.query("posts",
    populate=["author"],  # Only what's needed
    limit=20
)

# Bad - populate everything
posts = db.query("posts",
    populate=["author", "category", "tags", "comments", "likes"],  # Too much
    limit=20
)

Error Handling Patterns

Comprehensive Error Handling

Flutter
JavaScript
Python
Go

Future<void> performOperation() async {
  try {
    final result = await db.createDocument("posts", data);
    print('Success: ${result.id}');
  } on DioException catch (e) {
    if (e.response?.statusCode == 400) {
      print('Bad request - check your data');
    } else if (e.response?.statusCode == 401) {
      print('Unauthorized - login required');
      await handleSessionExpired();
    } else if (e.response?.statusCode == 403) {
      print('Forbidden - insufficient permissions');
    } else if (e.response?.statusCode == 404) {
      print('Not found');
    } else if (e.response?.statusCode == 429) {
      print('Rate limited - slow down');
      await Future.delayed(Duration(seconds: 5));
    } else {
      print('Error: ${e.message}');
    }
  } catch (e) {
    print('Unexpected error: $e');
  }
}

async function performOperation() {
  try {
    const result = await db.createDocument('posts', data);
    console.log('Success:', result.id);
  } catch (error) {
    if (error.response) {
      switch (error.response.status) {
        case 400:
          console.error('Bad request - check your data');
          break;
        case 401:
          console.error('Unauthorized - login required');
          await handleSessionExpired();
          break;
        case 403:
          console.error('Forbidden - insufficient permissions');
          break;
        case 404:
          console.error('Not found');
          break;
        case 429:
          console.error('Rate limited - slow down');
          await sleep(5000);
          break;
        default:
          console.error('Error:', error.message);
      }
    } else {
      console.error('Unexpected error:', error);
    }
  }
}

def main():
    try:
        user_id = req.get("user_id")

        if not user_id:
            return {"error": "user_id is required"}, 400

        posts = db.query("posts",
            author_id=user_id,
            limit=20
        )

        return {"posts": posts["data"]}

    except ValueError as e:
        return {"error": str(e)}, 400
    except Exception as e:
        print(f"Error: {str(e)}")
        return {"error": "Internal server error"}, 500

func performOperation() error {
    doc, err := client.CreateDocument(ctx, "posts", data)
    if err != nil {
        if apiErr, ok := err.(*cocobase.APIError); ok {
            switch apiErr.StatusCode {
            case 400:
                return fmt.Errorf("bad request: %w", err)
            case 401:
                return fmt.Errorf("unauthorized: %w", err)
            case 403:
                return fmt.Errorf("forbidden: %w", err)
            case 404:
                return fmt.Errorf("not found: %w", err)
            case 429:
                time.Sleep(5 * time.Second)
                return fmt.Errorf("rate limited: %w", err)
            default:
                return fmt.Errorf("error: %w", err)
            }
        }
        return err
    }

    fmt.Printf("Success: %s\n", doc.ID)
    return nil
}

Retry Logic

Implement Exponential Backoff:

Future<T> withRetry<T>(
  Future<T> Function() operation, {
  int maxAttempts = 3,
}) async {
  for (int i = 0; i < maxAttempts; i++) {
    try {
      return await operation();
    } catch (e) {
      if (i == maxAttempts - 1) rethrow;

      // Exponential backoff: 2^i seconds
      await Future.delayed(Duration(seconds: 1 << i));
    }
  }
  throw Exception('Max retries exceeded');
}

// Use it
final books = await withRetry(() => db.listDocuments<Book>("books"));

Rate Limiting

Respect API Limits

Implement Client-Side Rate Limiting:

class RateLimiter {
  constructor(maxRequests = 100, windowMs = 60000) {
    this.requests = [];
    this.maxRequests = maxRequests;
    this.windowMs = windowMs;
  }

  async acquire() {
    const now = Date.now();

    // Remove old requests outside the window
    this.requests = this.requests.filter((time) => now - time < this.windowMs);

    // Check if we're at the limit
    if (this.requests.length >= this.maxRequests) {
      const oldestRequest = this.requests[0];
      const waitTime = this.windowMs - (now - oldestRequest);
      await sleep(waitTime);
      return this.acquire(); // Retry
    }

    this.requests.push(now);
  }
}

// Use it
const limiter = new RateLimiter(100, 60000); // 100 requests per minute

async function makeRequest() {
  await limiter.acquire();
  return db.listDocuments("posts");
}

Batch Requests When Possible:

# Good - batch operations
def import_books(books_data):
    batch_size = 100
    for i in range(0, len(books_data), batch_size):
        batch = books_data[i:i + batch_size]
        db.bulk_create_documents("books", batch)

# Bad - individual requests
def import_books(books_data):
    for book in books_data:
        db.create_document("books", book)  # Too many requests!

Production Checklist

Before deploying to production, verify:

Security

API keys are stored securely (environment variables, not hardcoded)
HTTPS is enabled for all API calls
User authentication is properly validated
Input validation is implemented
Sensitive data is encrypted
Rate limiting is configured
Error messages don’t leak sensitive information

Performance

Indexes are created on frequently queried fields
Pagination is implemented for large datasets
Query limits are set appropriately
Caching is implemented where appropriate
Only necessary fields are selected/populated
Batch operations are used for bulk actions

Code Quality

Error handling is comprehensive
Logging is implemented
Code follows naming conventions
Tests are written and passing
Documentation is up to date
Type safety is enforced (where applicable)

Data Management

Database schema is properly designed
Relationships are clearly defined
Backup strategy is in place
Data migration plan exists
Soft deletes are used where appropriate

Monitoring

Error tracking is set up (e.g., Sentry)
Performance monitoring is enabled
Logs are centralized and searchable
Alerts are configured for critical issues

Performance Tips

1. Use Connection Pooling

// Good - custom HTTP client with connection pooling
httpClient := &http.Client{
    Timeout: 30 * time.Second,
    Transport: &http.Transport{
        MaxIdleConns:        100,
        MaxIdleConnsPerHost: 10,
        IdleConnTimeout:     90 * time.Second,
    },
}

client := cocobase.NewClient(cocobase.Config{
    APIKey:     apiKey,
    HTTPClient: httpClient,
})

2. Minimize Network Requests

// Bad - N+1 query problem
final posts = await db.listDocuments("posts", limit: 10);
for (var post in posts) {
  final author = await db.getDocument("users", post.data['author_id']);
  print('Author: ${author.data['name']}');
}

// Good - use populate
final posts = await db.listDocuments(
  "posts",
  queryBuilder: QueryBuilder().populate('author'),
  limit: 10
);
for (var post in posts) {
  print('Author: ${post.data['author']['name']}');
}

3. Use Bulk Operations

// Bad - individual creates
for (const book of books) {
  await db.createDocument("books", book);
}

// Good - batch create
await db.batchCreateDocuments("books", books);

4. Implement Lazy Loading

Load data only when needed to improve initial load time.

5. Optimize Images and Files

Compress images before upload
Use appropriate formats (WebP for web)
Implement lazy loading for images
Use CDN for static assets

Testing Best Practices

Unit Testing

// Flutter example
void main() {
  group('Book operations', () {
    late Cocobase db;

    setUp(() {
      final config = CocobaseConfig(apiKey: 'test-key');
      db = Cocobase(config);
    });

    test('should create a book', () async {
      final book = await db.createDocument('books', {
        'title': 'Test Book',
        'author': 'Test Author',
        'price': 19.99,
      });

      expect(book.data['title'], 'Test Book');
      expect(book.data['price'], 19.99);
    });

    test('should handle validation errors', () async {
      expect(
        () => db.createDocument('books', {}),
        throwsA(isA<ValidationError>()),
      );
    });
  });
}

Next Steps

Troubleshooting - Common issues and solutions
Cloud Functions - Build serverless functions
Advanced Features - Batch operations and aggregations
Examples - Real-world code examples

Getting Started

Core Concepts

Features

Cloud Functions

SDK Reference

Guides

API Reference

Best Practices

Best Practices

Security Best Practices

API Key Management

Authentication Security

Input Validation

Data Modeling Best Practices

Schema Design

Relationship Management

Efficient Queries

Error Handling Patterns

Comprehensive Error Handling

Retry Logic

Rate Limiting

Respect API Limits

Production Checklist

Security

Performance

Code Quality

Data Management

Monitoring

Performance Tips

1. Use Connection Pooling

2. Minimize Network Requests

3. Use Bulk Operations

4. Implement Lazy Loading

5. Optimize Images and Files

Testing Best Practices

Unit Testing

Next Steps

Getting Started

Core Concepts

Features

Cloud Functions

SDK Reference

Guides

API Reference

Documentation Index

​Best Practices

​Security Best Practices

​API Key Management

​Authentication Security

​Input Validation

​Data Modeling Best Practices

​Schema Design

​Relationship Management

​Efficient Queries

​Error Handling Patterns

​Comprehensive Error Handling

​Retry Logic

​Rate Limiting

​Respect API Limits

​Production Checklist

​Security

​Performance

​Code Quality

​Data Management

​Monitoring

​Performance Tips

​1. Use Connection Pooling

​2. Minimize Network Requests

​3. Use Bulk Operations

​4. Implement Lazy Loading

​5. Optimize Images and Files

​Testing Best Practices

​Unit Testing

​Next Steps

Best Practices

Security Best Practices

API Key Management

Authentication Security

Input Validation

Data Modeling Best Practices

Schema Design

Relationship Management

Efficient Queries

Error Handling Patterns

Comprehensive Error Handling

Retry Logic

Rate Limiting

Respect API Limits

Production Checklist

Security

Performance

Code Quality

Data Management

Monitoring

Performance Tips

1. Use Connection Pooling

2. Minimize Network Requests

3. Use Bulk Operations

4. Implement Lazy Loading

5. Optimize Images and Files

Testing Best Practices

Unit Testing

Next Steps