sogou/workflow

C++ Parallel Computing and Asynchronous Networking Framework

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Summary Information

Updated 58 minutes ago
Added to GitGenius on September 4th, 2026
Created on July 29th, 2020
Open Issues & Pull Requests: 27 (+0)
GitHub issues: Enabled
Number of forks: 2,560
Total Stargazers: 14,421 (+0)
Total Subscribers: 240 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 1.1 hours
Mean response time: 8.0 days
90th percentile: 12.2 hours
Tracked items: 90

How this project is maintained

Around half of the issues opened in the past year never receive a reply. Only 7% of issues opened in the past year have been closed. Three people close 73% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 14
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 572 days
Stale 30+ days: 14
Stale 90+ days: 13

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • documentation (5)
  • enhancement (3)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Workflow is a C++ parallel computing and asynchronous networking framework that enables developers to build concurrent applications with task-based parallelism and non-blocking I/O operations.

The framework addresses the challenge of writing efficient concurrent systems by providing abstractions for task scheduling, workflow composition, and asynchronous network communication. It uses a task-based model where computations are expressed as directed acyclic graphs that can be executed in parallel, combined with event-driven networking primitives for handling I/O without blocking threads. This approach allows developers to express complex concurrent logic while the framework manages thread pools and event loops transparently.

The tool suits C++ projects that require high-performance concurrent processing, particularly those involving network services, data processing pipelines, or systems that coordinate multiple asynchronous operations. It integrates with common infrastructure components including HTTP, MySQL, Redis, and Kafka, making it applicable to backend services and data pipeline applications. Developers building systems that need to balance parallelism with resource efficiency will find the task graph model particularly useful for expressing dependencies between operations.

The project shows sustained development activity with regular commits addressing bug fixes and feature enhancements. Pull requests are reviewed and merged consistently, indicating an active maintenance process. The codebase receives updates that extend its capabilities and improve stability, with attention paid to both core framework functionality and integration with external services. Documentation and examples are maintained alongside the code, supporting ongoing usability for new adopters.