Connection Management

Learn how to connect to QilbeeDB, manage connection pools, and configure client settings for optimal performance.

Basic Connection#

Python SDK#

from qilbeedb import QilbeeDB

# Simple connection
db = QilbeeDB("http://localhost:7474")

# Use context manager for automatic cleanup
with QilbeeDB("http://localhost:7474") as db:
    graph = db.graph("my_graph")
    # Operations...
# Connection automatically closed

HTTP REST API#

# Direct HTTP requests
curl http://localhost:7474/health

# Check server status
curl http://localhost:7474/graphs

Connection Configuration#

Connection URL Formats#

HTTP:

db = QilbeeDB("http://localhost:7474")
db = QilbeeDB("https://qilbeedb.example.com:7474")

Bolt (Coming Soon):

db = QilbeeDB("bolt://localhost:7687")

Connection Options#

db = QilbeeDB(
    url="http://localhost:7474",
    timeout=30,              # Request timeout in seconds
    max_retries=3,           # Retry failed requests
    verify_ssl=True,         # Verify SSL certificates
)

Authentication#

Basic Authentication#

db = QilbeeDB(
    "http://localhost:7474",
    auth=("username", "password")
)

Token Authentication#

db = QilbeeDB(
    "http://localhost:7474",
    token="your-api-token"
)

Connection Pooling#

This page is under development. Full documentation coming soon.

Connection pooling helps manage multiple concurrent connections efficiently:

# Configure connection pool
db = QilbeeDB(
    "http://localhost:7474",
    pool_size=10,           # Max connections
    pool_timeout=30         # Wait time for available connection
)

Error Handling#

Connection Errors#

from qilbeedb import QilbeeDB
from qilbeedb.exceptions import ConnectionError

try:
    db = QilbeeDB("http://localhost:7474")
    db.list_graphs()
except ConnectionError as e:
    print(f"Failed to connect: {e}")
    # Handle connection failure

Timeout Handling#

from qilbeedb.exceptions import TimeoutError

try:
    result = graph.query("MATCH (n) RETURN n", timeout=5)
except TimeoutError:
    print("Query timed out")

Connection Best Practices#

1. Use Context Managers#

Always use context managers for automatic resource cleanup:

# Good: Automatic cleanup
with QilbeeDB("http://localhost:7474") as db:
    graph = db.graph("my_graph")
    # Operations...

# Bad: Manual management
db = QilbeeDB("http://localhost:7474")
# Operations...
db.close()  # Easy to forget!

2. Reuse Connections#

Create one connection and reuse it:

# Good: Reuse connection
db = QilbeeDB("http://localhost:7474")
graph1 = db.graph("graph1")
graph2 = db.graph("graph2")

# Bad: Multiple connections
db1 = QilbeeDB("http://localhost:7474")
db2 = QilbeeDB("http://localhost:7474")

3. Configure Timeouts#

Set appropriate timeouts for your use case:

# Long-running analytics
db = QilbeeDB("http://localhost:7474", timeout=300)

# Interactive queries
db = QilbeeDB("http://localhost:7474", timeout=10)

4. Handle Connection Failures#

Always handle connection failures gracefully:

from qilbeedb.exceptions import ConnectionError
import time

def connect_with_retry(url, max_attempts=3):
    for attempt in range(max_attempts):
        try:
            return QilbeeDB(url)
        except ConnectionError as e:
            if attempt < max_attempts - 1:
                time.sleep(2 ** attempt)  # Exponential backoff
            else:
                raise

Health Checks#

Check if QilbeeDB is healthy:

# Python
try:
    db = QilbeeDB("http://localhost:7474")
    # Connection successful
except ConnectionError:
    # Server not available
    pass

# HTTP
curl http://localhost:7474/health

Next Steps#

Edit this page on GitHub