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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

Project details


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