A high-performance parallel task processing framework for solving IO-bound (Redis queue, file system, command execution) and CPU-bound (computation) workloads. Designed for scalability, efficiency, and seamless distributed execution."
Project description
Gatling
A high-performance parallel task processing framework for solving IO-bound (Redis queue, file system, command execution) and CPU-bound (computation) workloads. Designed for scalability, efficiency, and seamless distributed execution.
Features
-
Redis DataType in Python Way
Provides a Pythonic interface for interacting with Redis data types, enabling you to manipulate Redis data structures as if they were native Python objects. -
Redis Queue Executor
Utilizes Redis as a backend for task queuing and scheduling. It supports both synchronous and asynchronous execution along with built-in error handling and retry mechanisms for robust task processing. -
Super File System
Offers an advanced file system module that supports high-performance, distributed file operations. This module makes it easy to manage and process large volumes of files across different nodes. -
Modular Architecture
The framework is designed with modularity in mind, making it easy to extend and customize for various IO-bound and CPU-bound workloads. -
Distributed Execution
Built-in support for cross-node task scheduling and execution helps you build scalable, distributed systems effortlessly. -
High Performance Optimizations
Optimized to handle both IO-intensive and CPU-intensive tasks efficiently, ensuring optimal resource utilization.
Installation
Install the package using pip:
pip install gatling
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