lszeremeta/knows

Property graph benchmark with node and edges generation, multiple output formats, and visualization

Knows is a user-friendly tool for benchmarking property graphs. These graphs are crucial in many fields. Knows supports multiple output formats and visualization capabilities, making it a go-to tool for educators, researchers, and data enthusiasts.

Key Features 🚀

• Customizable Graph Generation: Tailor your graphs by specifying the number of nodes and edges.
• Diverse Output Formats: Export graphs in formats like GraphML, YARS-PG, GEXF, GML, SVG, JSON, and others.
• Integrated Graph Visualization: Conveniently visualize your graphs in SVG format.
• Intuitive Command-Line Interface (CLI): A user-friendly CLI for streamlined graph generation and visualization.
• Docker Compatibility: Deploy Knows in Docker containers for a consistent and isolated runtime environment.

Graph Structure

• Generates graphs with specified or random nodes and edges.
• Creates directed graphs.
• Nodes are labeled Person with unique IDs (N1, N2, N3, ..., Nn).
• Nodes feature firstName and lastName properties with randomly assigned names.
• Edges are labeled knows and include a createDate property with a random date.
• Edges have random nodes, avoiding cycles.

Installation 🛠️

You can install knows via PyPI Docker or run it from the source code.

Install via PyPI

1. Installation:

   pip install knows[draw]

   The draw installs a matplotlib library for graph visualization. You can omit the [draw] if you don't need visualization and svg output generation.

2. Running Knows:

   knows [nodes] [edges] [options]

Docker Deployment 🐳

From Docker Hub

1. Pull Image:

   docker pull lszeremeta/knows

2. Run Container:

   docker run --rm lszeremeta/knows [nodes] [edges] [options]

Building from Source

1. Build Image:

   docker build -t knows .

2. Run Container:

   docker run --rm knows [nodes] [edges] [options]

Python from Source

1. Clone Repository:

   git clone git@github.com:lszeremeta/knows.git
   cd knows

2. Install Requirements:

   pip install -r requirements.txt

3. Execute Knows:

   python -m knows [nodes] [edges] [options]

Usage 💡

Basic Usage

knows [nodes] [edges] [options]

To view all available options, use:

knows -h

Positional Arguments

1. nodes: Specify the number of nodes in the graph. Selected randomly if not specified.
2. edges: Specify the number of edges in the graph. Selected randomly if not specified.

Options

• -h, --help: Display the help message and exit the program.
• -f {graphml,yarspg,gexf,gml,svg,adjacency_list,multiline_adjacency_list,edge_list,json}, --format {graphml,yarspg,gexf,gml,svg,adjacency_list,multiline_adjacency_list,edge_list,json}: Choose the format to output the graph. Default: graphml.
• -d, --draw: Generate an image of the graph (default is no image). This option may not work in the Docker.

Practical Examples 🌟

1. Create a random graph in GraphML format:

   knows

2. Create a 100-node, 70-edge graph in YARS-PG format:

   knows 100 70 -f yarspg > graph.yarspg

3. Create a 100-node, 50-edge graph in GraphML format:

    knows 100 50 > graph.graphml

4. Create, save, and visualize a 100-node, 50-edge graph in SVG:

   knows 100 50 -f svg -d > graph.svg

5. Create, save a 100-node, 50-edge graph in SVG with a custom filename:

    knows 100 50 -f svg > graph.svg

6. Create a graph in JSON format:

   knows -f json > graph.json

Contribute to Knows 👥

Your ideas and contributions can make Knows even better! If you're new to open source, read How to Contribute to Open Source and CONTRIBUTING.md.

License 📜

Knows is licensed under the MIT License.