A lightweight, header-only C++20 graph library designed as a simpler alternative to the Boost Graph Library.
Graaf is a lightweight, header-only graph library implemented in C++20. It provides essential graph data structures and algorithms, serving as a simpler alternative to the Boost Graph Library. The library enables developers to easily create, manipulate, and analyze graphs for applications like route planning, network analysis, and data mining.
C++ developers working on projects that require graph modeling and algorithms, such as network analysis, route planning, or data mining applications. It is particularly suitable for those seeking a lightweight, easy-to-integrate alternative to heavier graph libraries.
Developers choose Graaf for its simplicity, header-only design, and modern C++20 implementation. It offers a straightforward API, supports user-defined vertex and edge types, and includes a comprehensive set of graph algorithms, making it an accessible and extensible choice for graph-related tasks.
A general-purpose lightweight C++ graph library
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No separate compilation or linking is needed, simplifying integration into any C++ project as highlighted in the installation section.
Supports custom vertex and edge classes, enabling flexible modeling as demonstrated with structs like User and Connection in the usage examples.
Includes a wide range of algorithms from shortest path to cycle detection, covering common graph tasks as listed in the algorithms section.
Built with C++20 standards for performance and safety, ensuring compatibility with modern C++ codebases.
Provides DOT format support for graph visualization, making it easy to generate visual representations without external tools.
As a lightweight alternative to BGL, it may lack advanced functionalities like sophisticated property maps or algorithm variants found in more mature libraries.
Being a newer project, it has a smaller community and fewer third-party integrations compared to established options like Boost Graph Library.
Designed for simplicity, it might not include optimizations for handling extremely large graphs or high-concurrency scenarios, potentially limiting scalability.
Graaf is an open-source alternative to the following products: