sterling-server 0.1.0

Sterling Server - In memory caching database

Sterling Server

A high-performance, in-memory cache server written in Python with persistence support and multi-client capability.

Features

• In-Memory Data Store: Fast key-value storage with O(1) access time
• Persistence Options:
  • RDB (Database) snapshotting
  • AOF (Append-Only File) logging
• Multi-Client Support: Handle concurrent connections via asyncio
• Memory Management:
  • Configurable maxmemory limits
  • LRU eviction policy support
• TTL Expiration: Automatic key expiration with time-to-live
• Flexible Logging: Console or file-based logging with append/fresh modes
• Thread-Safe Operations: Async locks for concurrent access

Installation

Via PyPI

pip install sterling-server

Via TestPyPI

pip install -i https://test.pypi.org/simple/ sterling-server

From Source

git clone https://github.com/ghosecorp/sterling.git
cd sterling
pip install -e .

Quick Start

Basic Usage

from sterling_server import SterlingServer

# Create server with default settings
server = SterlingServer()
server.run()

Advanced Configuration

from sterling_server import SterlingServer

server = SterlingServer(
    host='0.0.0.0',              # Listen on all interfaces
    port=9162,                    # Custom port
    persistence_mode='RDB',       # 'RDB' or 'AOF'
    maxmemory=10000,              # Max keys before eviction
    eviction_policy='lru',        # 'lru', 'allkeys-lru', or 'noeviction'
    log_to_file=True,             # Enable file logging
    log_file_path='log/sterling.log',
    fresh_logs=False              # Append to existing logs
)

server.run()

Configuration Options

Parameter	Type	Default	Description
host	str	'localhost'	Server bind address
port	int	9162	Server port
persistence_mode	str	'RDB'	Persistence strategy (RDB or AOF)
maxmemory	int	None	Maximum keys in memory (None = unlimited)
eviction_policy	str	'noeviction'	How to handle memory limits
log_to_file	bool	False	Log to file instead of console
log_file_path	str	None	Custom log file path (default: log/server_logs.log)
fresh_logs	bool	False	Start with fresh log file (True) or append (False)

Persistence Strategies

RDB (Snapshot)

• Affects: ✅ Disk only
• Periodic snapshots of entire dataset
• Fast recovery, potential minor data loss
• Best for: Speed and simplicity

AOF (Append-Only File)

• Affects: ✅ Disk only
• Logs every write operation
• Maximum durability, larger files
• Best for: Critical data requiring minimal loss

Memory Management

Feature	Affects RAM?	Affects Disk?	Purpose
Persistence (RDB/AOF)	❌	✅	Recovery after restart
maxmemory	✅	❌	Limit RAM usage
Eviction policy	✅	❌	Auto-delete old keys
TTL expiration	✅	❌	Auto-delete expired data

Examples

See the examples/ directory for complete examples:

• basic_server.py - Minimal server setup
• production_server.py - Production configuration with logging
• custom_persistence.py - Different persistence strategies

Future Development

Performance Roadmap: Sterling Server will be gradually rewritten in C or Go (decision pending) to unlock:

• Hardware-level optimizations
• Native system integration
• Enhanced performance characteristics
• Advanced memory management

Commitment: We will continue maintaining and actively developing the Python version, incorporating features from the C/Go implementation whenever possible. The Python server remains our primary focus for users who prefer Python integration and ease of deployment.

Documentation

Full documentation available at: https://github.com/ghosecorp/sterling/blob/main/README.md

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Changelog

See CHANGELOG.md for version history and updates.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [e-mail]

Related Projects

• sterling - Python client library
• Sterling clients for other languages (coming soon)

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