Kafka-based distributed task processing SDK
Project description
Ninja Kafka SDK
Simple SDK for distributed task processing with Kafka messaging.
Send tasks to Ninja services and get results back with just 3 lines of code instead of managing complex Kafka setup.
🚀 Quick Start - Send Your First Task
from ninja_kafka_sdk import NinjaClient
# Configure your Kafka connection
client = NinjaClient(
kafka_servers="your-kafka-servers:9092",
consumer_group="your-service-name"
)
# Send task and wait for result
result = await client.execute_task(
task="data_processing",
account_id=123,
email="user@example.com"
)
if result.is_success:
print("✅ Task completed successfully!")
print(f"Result data: {result.data}")
else:
print(f"❌ Failed: {result.error_message}")
📦 Installation
# Copy to your project
cp -r ninja_kafka_sdk/ /your/project/
# Install dependencies (already in requirements.txt)
pip install kafka-python
⚙️ Configuration
Explicit Configuration (Recommended)
from ninja_kafka_sdk import NinjaClient
client = NinjaClient(
kafka_servers="your-kafka-servers:9092", # Change for your environment
consumer_group="your-service-name" # Unique name for your service
)
Configuration from Variables
import os
from ninja_kafka_sdk import NinjaClient
# Read from your application configuration
kafka_servers = os.getenv('MY_KAFKA_SERVERS', 'localhost:9092')
consumer_group = os.getenv('MY_CONSUMER_GROUP', 'my-service')
client = NinjaClient(
kafka_servers=kafka_servers,
consumer_group=consumer_group
)
Configuration with Config Object
from ninja_kafka_sdk import NinjaClient, NinjaKafkaConfig
# Create configuration object
config = NinjaKafkaConfig(
kafka_servers="b-1.msk-cluster.amazonaws.com:9092,b-2.msk-cluster.amazonaws.com:9092",
consumer_group="my-service",
environment="stage",
tasks_topic="ninja-tasks",
results_topic="ninja-results"
)
# Use with client
client = NinjaClient(config=config)
Auto-Detection Fallback
If no explicit configuration is provided, the SDK will attempt to auto-detect from:
- Environment variables (
KAFKA_CONNECTION) - Local configuration files (
app/local.py) - AWS metadata (if running on EC2)
- Smart defaults (
localhost:9092for local development)
💡 How to Send Tasks
Basic Task Execution
from ninja_kafka_sdk import NinjaClient
async def verify_linkedin_account():
# Explicit configuration for production
client = NinjaClient(
kafka_servers="b-1.msk-cluster.amazonaws.com:9092,b-2.msk-cluster.amazonaws.com:9092",
consumer_group="auto-login-service",
environment="prod"
)
try:
# Send task and wait for result (one method call)
result = await client.execute_task(
task="linkedin_verification",
account_id=12345,
email="user@example.com",
timeout=300 # 5 minutes
)
if result.is_success:
print("✅ Verification successful!")
return result.cookies
else:
print(f"❌ Failed: {result.error_message}")
return None
finally:
client.stop()
Advanced Usage Patterns
Fire and Forget
async def send_multiple_tasks():
client = NinjaClient()
# Send task without waiting for result
correlation_id = await client.send_task(
task="linkedin_verification",
account_id=123
)
print(f"Task sent: {correlation_id}")
client.stop()
Batch Processing
async def process_multiple_accounts():
client = NinjaClient()
accounts = [123, 456, 789]
try:
# Send all tasks
task_ids = []
for account_id in accounts:
task_id = await client.send_task("linkedin_verification", account_id=account_id)
task_ids.append(task_id)
# Listen for all results
completed = 0
async for result in client.listen_results(correlation_ids=task_ids):
completed += 1
print(f"Account {result.account_id}: {result.status}")
if completed >= len(accounts):
break
finally:
client.stop()
Synchronous Usage (Non-async Applications)
def sync_verification():
client = NinjaClient()
try:
# Synchronous task execution
result = client.execute_task_sync(
task="linkedin_verification",
account_id=123,
email="user@example.com",
timeout=60
)
print(f"Result: {result.status}")
return result.is_success
finally:
client.stop()
Environment-Specific Usage
# Force specific environment
async def production_verification():
# Explicitly use production configuration
client = NinjaClient(environment="prod")
# Will use KAFKA_PROD_SERVERS if set, otherwise shows warning
result = await client.execute_task("linkedin_verification", account_id=123)
client.stop()
return result
# Auto-detect environment
async def auto_verification():
# Uses environment detection (local/dev/stage/prod)
client = NinjaClient()
result = await client.execute_task("linkedin_verification", account_id=123)
client.stop()
return result
🏗️ Available Tasks
LinkedIn Verification
result = await client.execute_task(
task="linkedin_verification",
account_id=123,
email="user@example.com", # Optional but highly recommended
timeout=300 # 5 minutes
)
Future Tasks
More task types will be added for different platforms:
twitter_verificationinstagram_verificationfacebook_verification
📝 Message Models
Task Request
@dataclass
class NinjaTaskRequest:
task: str # "linkedin_verification"
account_id: int # Account ID
correlation_id: str # Auto-generated UUID
email: Optional[str] # Account email
user_id: Optional[int] # User ID
metadata: Dict[str, Any] # Additional parameters
Task Result
@dataclass
class NinjaTaskResult:
correlation_id: str # Matches request
task: str # Task type
status: str # "VERIFIED", "FAILED", etc.
success: bool # True if successful
account_id: int # Account ID
cookies: Optional[str] # Extracted cookies
data: Optional[Dict] # Additional result data
error: Optional[Dict] # Error details if failed
@property
def is_success(self) -> bool:
return self.success or self.status == 'VERIFIED'
🚨 Error Handling
from ninja_kafka_sdk import (
NinjaClient, NinjaTaskTimeoutError,
NinjaTaskError, NinjaKafkaConnectionError
)
try:
result = await client.execute_task("linkedin_verification", account_id=123)
except NinjaTaskTimeoutError:
print("Task took too long")
except NinjaTaskError as e:
print(f"Ninja couldn't complete task: {e.details}")
except NinjaKafkaConnectionError:
print("Can't connect to Kafka")
🔌 Extending for New Services
# Add new task types easily
await client.send_task(
task="twitter_scraping",
account_id=123,
parameters={"target_user": "@elonmusk"}
)
# SDK handles routing to appropriate Ninja service
🔧 Troubleshooting
Common Configuration Issues
Issue: "Can't connect to Kafka"
# Check your servers configuration
from ninja_kafka_sdk.config import NinjaKafkaConfig
config = NinjaKafkaConfig()
print(f"Environment: {config.environment}")
print(f"Kafka servers: {config.kafka_servers}")
print(f"Consumer group: {config.consumer_group}")
Solutions:
- Local Development: Ensure Kafka is running on
localhost:9092 - Stage/Prod: Verify
KAFKA_STAGE_SERVERSorKAFKA_PROD_SERVERSare set - Custom Provider: Use
KAFKA_BOOTSTRAP_SERVERSfor explicit override
Issue: "No messages received"
# Check consumer group conflicts
import os
print(f"Consumer group: {os.getenv('KAFKA_CONSUMER_GROUP', 'auto-detected')}")
# Force specific consumer group
os.environ['KAFKA_CONSUMER_GROUP'] = 'my-unique-group'
client = NinjaClient()
Issue: "Task timeout"
# Increase timeout for slow operations
client = NinjaClient(timeout=600) # 10 minutes
result = await client.execute_task("linkedin_verification", account_id=123, timeout=300)
Environment Detection Debug
from ninja_kafka_sdk.config import NinjaKafkaConfig
# Debug environment detection
config = NinjaKafkaConfig()
print(f"Environment: {config.environment}")
print(f"Servers: {config.kafka_servers}")
# Force specific environment
config = NinjaKafkaConfig(environment='stage')
print(f"Forced stage servers: {config.kafka_servers}")
Quick Health Check
from ninja_kafka_sdk import NinjaClient
import asyncio
async def health_check():
client = NinjaClient()
try:
# Test connection by sending a test message
correlation_id = await client.send_task("health_check", account_id=0)
print(f"✅ Connection OK - Test message sent: {correlation_id}")
return True
except Exception as e:
print(f"❌ Connection failed: {e}")
return False
finally:
client.stop()
# Run health check
asyncio.run(health_check())
📚 Appendix: For Service Implementers
This section contains information for developers implementing Ninja services (like browser-ninja) that process tasks and send results back.
Sending Task Results
If you're building a service that processes Ninja tasks, use these methods to send results:
from ninja_kafka_sdk import NinjaClient
async def send_verification_result():
# Configure client for service that processes tasks
client = NinjaClient(
kafka_servers="your-kafka-servers:9092",
consumer_group="browser-ninja", # Service-specific consumer group
environment="prod"
)
try:
# Send success result
await client.send_success_result(
correlation_id="task-123-456",
account_id=12345,
email="user@example.com",
cookies="extracted_cookies_data",
screenshot="base64_screenshot"
)
# Or send error result
await client.send_error_result(
correlation_id="task-123-457",
account_id=12346,
email="user2@example.com",
error_code="LOGIN_FAILED",
error_message="Invalid credentials"
)
finally:
client.stop()
Listening for Tasks (Future Feature)
from ninja_kafka_sdk import NinjaClient
async def process_ninja_tasks():
client = NinjaClient(
kafka_servers="your-kafka-servers:9092",
consumer_group="browser-ninja"
)
try:
# Listen for incoming tasks
async for task in client.listen_tasks():
print(f"📥 Received task: {task.task} for account {task.account_id}")
# Process the task
if task.task == "linkedin_verification":
result = await process_linkedin_verification(task)
# Send result back
if result["success"]:
await client.send_success_result(
correlation_id=task.correlation_id,
account_id=task.account_id,
email=task.email,
cookies=result["cookies"]
)
else:
await client.send_error_result(
correlation_id=task.correlation_id,
account_id=task.account_id,
email=task.email,
error_code=result["error_code"],
error_message=result["error_message"]
)
finally:
client.stop()
The Ninja Kafka SDK simplifies task-based communication while maintaining enterprise-grade reliability.
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