# <img src="https://raw.githubusercontent.com/lszeremeta/knows/main/logo/knows-logo.png" alt="Knows logo" width="300">
[](https://pypi.org/project/knows/) [](https://hub.docker.com/r/lszeremeta/knows)
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**:
```shell
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**:
```shell
knows [nodes] [edges] [options]
```
### Docker Deployment 🐳
#### From Docker Hub
1. **Pull Image**:
```shell
docker pull lszeremeta/knows
```
2. **Run Container**:
```shell
docker run --rm lszeremeta/knows [nodes] [edges] [options]
```
#### Building from Source
1. **Build Image**:
```shell
docker build -t knows .
```
2. **Run Container**:
```shell
docker run --rm knows [nodes] [edges] [options]
```
### Python from Source
1. **Clone Repository**:
```shell
git clone git@github.com:lszeremeta/knows.git
cd knows
```
2. **Install Requirements**:
```shell
pip install -r requirements.txt
```
3. **Execute Knows**:
```shell
python -m knows [nodes] [edges] [options]
```
## Usage 💡
### Basic Usage
```shell
knows [nodes] [edges] [options]
```
To view all available options, use:
```shell
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:
```shell
knows
```
2. Create a 100-node, 70-edge graph in [YARS-PG format](https://github.com/lszeremeta/yarspg):
```shell
knows 100 70 -f yarspg > graph.yarspg
```
3. Create a 100-node, 50-edge graph in GraphML format:
```shell
knows 100 50 > graph.graphml
```
4. Create, save, and visualize a 100-node, 50-edge graph in SVG:
```shell
knows 100 50 -f svg -d > graph.svg
```
5. Create, save a 100-node, 50-edge graph in SVG with a custom filename:
```shell
knows 100 50 -f svg > graph.svg
```
6. Create a graph in JSON format:
```shell
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](https://opensource.guide/how-to-contribute/)
and [CONTRIBUTING.md](https://github.com/lszeremeta/knows/blob/main/CONTRIBUTING.md).
## License 📜
Knows is licensed under the [MIT License](https://github.com/lszeremeta/knows/blob/main/LICENSE).
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"description": "# <img src=\"https://raw.githubusercontent.com/lszeremeta/knows/main/logo/knows-logo.png\" alt=\"Knows logo\" width=\"300\">\n\n[](https://pypi.org/project/knows/) [](https://hub.docker.com/r/lszeremeta/knows)\n\nKnows is a user-friendly tool for benchmarking property graphs. These graphs are crucial in many fields. Knows supports\nmultiple output formats and visualization capabilities, making it a go-to tool for educators, researchers, and data\nenthusiasts.\n\n## Key Features \ud83d\ude80\n\n- **Customizable Graph Generation**: Tailor your graphs by specifying the number of nodes and edges.\n- **Diverse Output Formats**: Export graphs in formats like GraphML, YARS-PG, GEXF, GML, SVG, JSON, and others.\n- **Integrated Graph Visualization**: Conveniently visualize your graphs in SVG format.\n- **Intuitive Command-Line Interface (CLI)**: A user-friendly CLI for streamlined graph generation and visualization.\n- **Docker Compatibility**: Deploy Knows in Docker containers for a consistent and isolated runtime environment.\n\n## Graph Structure\n\n- Generates graphs with specified or random nodes and edges.\n- Creates directed graphs.\n- Nodes are labeled `Person` with unique IDs (`N1, N2, N3, ..., Nn`).\n- Nodes feature `firstName` and `lastName` properties with randomly assigned names.\n- Edges are labeled `knows` and include a `createDate` property with a random date.\n- Edges have random nodes, avoiding cycles.\n\n## Installation \ud83d\udee0\ufe0f\n\nYou can install knows via PyPI Docker or run it from the source code.\n\n### Install via PyPI\n\n1. **Installation**:\n ```shell\n pip install knows[draw]\n ```\n The `draw` installs a `matplotlib` library for graph visualization. You can omit the `[draw]` if you don't need visualization and `svg` output generation.\n\n2. **Running Knows**:\n ```shell\n knows [nodes] [edges] [options]\n ```\n\n### Docker Deployment \ud83d\udc33\n\n#### From Docker Hub\n\n1. **Pull Image**:\n ```shell\n docker pull lszeremeta/knows\n ```\n\n2. **Run Container**:\n ```shell\n docker run --rm lszeremeta/knows [nodes] [edges] [options]\n ```\n\n#### Building from Source\n\n1. **Build Image**:\n ```shell\n docker build -t knows .\n ```\n\n2. **Run Container**:\n ```shell\n docker run --rm knows [nodes] [edges] [options]\n ```\n\n### Python from Source\n\n1. **Clone Repository**:\n ```shell\n git clone git@github.com:lszeremeta/knows.git\n cd knows\n ```\n\n2. **Install Requirements**:\n ```shell\n pip install -r requirements.txt\n ```\n\n3. **Execute Knows**:\n ```shell\n python -m knows [nodes] [edges] [options]\n ```\n\n## Usage \ud83d\udca1\n\n### Basic Usage\n\n```shell\nknows [nodes] [edges] [options]\n```\n\nTo view all available options, use:\n\n```shell\nknows -h\n```\n\n### Positional Arguments\n\n1. `nodes`: Specify the number of nodes in the graph. Selected randomly if not specified.\n2. `edges`: Specify the number of edges in the graph. Selected randomly if not specified.\n\n### Options\n\n- `-h`, `--help`: Display the help message and exit the program.\n- `-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}`:\n Choose the format to output the graph. Default: `graphml`.\n- `-d`, `--draw`: Generate an image of the graph (default is no image). This option may not work in the Docker.\n\n### Practical Examples \ud83c\udf1f\n\n1. Create a random graph in GraphML format:\n ```shell\n knows\n ```\n2. Create a 100-node, 70-edge graph in [YARS-PG format](https://github.com/lszeremeta/yarspg):\n ```shell\n knows 100 70 -f yarspg > graph.yarspg\n ```\n3. Create a 100-node, 50-edge graph in GraphML format:\n ```shell\n knows 100 50 > graph.graphml\n ```\n4. Create, save, and visualize a 100-node, 50-edge graph in SVG:\n ```shell\n knows 100 50 -f svg -d > graph.svg\n ```\n5. Create, save a 100-node, 50-edge graph in SVG with a custom filename:\n ```shell\n knows 100 50 -f svg > graph.svg\n ```\n6. Create a graph in JSON format:\n ```shell\n knows -f json > graph.json\n ```\n\n## Contribute to Knows \ud83d\udc65\n\nYour ideas and contributions can make Knows even better! If you're new to open source,\nread [How to Contribute to Open Source](https://opensource.guide/how-to-contribute/)\nand [CONTRIBUTING.md](https://github.com/lszeremeta/knows/blob/main/CONTRIBUTING.md).\n\n## License \ud83d\udcdc\n\nKnows is licensed under the [MIT License](https://github.com/lszeremeta/knows/blob/main/LICENSE).\n",
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