# networkx-gdf
Python package to read and write NetworkX graphs as GDF (Graph Data Format).
GDF is a compact file format originally implemented by [GUESS](http://graphexploration.cond.org). Although the software itself is not anymore maintained, the format is still supported by active open-source projects such as [Gephi](https://gephi.org/) (see details [here](https://gephi.org/users/supported-graph-formats/gdf-format/)).
## Requirements
* **Python>=3.7**
* networkx>=2.1
* pandas>=1.1.0
## Install
Package is available to install on [PyPI](https://pypi.org/project/networkx-gdf/):
```bash
pip install networkx-gdf
```
## Usage
Just two functions are implemented, for reading from and writing data to file.
```python
from networkx_gdf import read_gdf, write_gdf
# Builds NetworkX graph object from file.
G = read_gdf("input_file.gdf")
# Writes NetworkX graph object to file.
write_gdf(G, "output_file.gdf")
```
### Detailed usage
A few additional arguments are available both for reading and writing files:
#### Building NetworkX graph object from file
```python
G = read_gdf(
"input_file.gdf",
# Required; file path to read data from.
directed=None,
# Optional; consider edges as directed or undirected.
# True: returns a <nx.DiGraph> or <nx.MultiDiGraph> object.
# False: returns a <nx.Graph> or <nx.MultiGraph> object.
# None (default): decides based on "directed" edge attribute in file.
multigraph=None,
# Optional; consider multiple or single edges among nodes.
# True: always returns a <nx.MultiGraph> or <nx.MultiDiGraph> object.
# False: sums edge weights and returns a <nx.Graph> or <nx.DiGraph> object.
# None (default): decides based on number of edges among the same pair of nodes.
node_attr=None,
# Optional; node attributes to import data from.
# Accepts either a list containing attribute names or a boolean (True, False).
# Defaults to True, which considers all node attributes.
edge_attr=None,
# Optional; edge attributes to import data from.
# Accepts either a list containing attribute names or a boolean (True, False).
# Defaults to True, which considers all edge attributes.
)
```
#### Writing NetworkX graph object to file
```python
write_gdf(
G,
# Required; graph object from NetworkX.
"output_file.gdf",
# Required; file path to write data to.
node_attr=None,
# Optional; node attributes to export data from.
# Accepts either a list containing attribute names or a boolean (True, False).
# Defaults to True, which considers all node attributes.
edge_attr=None,
# Optional; edge attributes to export data from.
# Accepts either a list containing attribute names or a boolean (True, False).
# Defaults to True, which considers all edge attributes.
)
```
Note that any object types beyond integers/longs, floats/doubles, and booleans will be considered as strings.
### Importing as a class
Alternatively, the module can also be imported as a class and inherited:
```python
from networkx_gdf import GDF
class MyClass(GDF):
...
G = MyClass.read_gdf("input_file.gdf")
MyClass.write_gdf(G, "output_file.gdf")
```
Both functions are implemented as static methods, so initializing the class as an object is not required.
___
### References
* [NetworkX](https://networkx.github.io)
* [Pandas](https://pandas.pydata.org/)
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"description": "# networkx-gdf\n\nPython package to read and write NetworkX graphs as GDF (Graph Data Format).\n\nGDF is a compact file format originally implemented by [GUESS](http://graphexploration.cond.org). Although the software itself is not anymore maintained, the format is still supported by active open-source projects such as [Gephi](https://gephi.org/) (see details [here](https://gephi.org/users/supported-graph-formats/gdf-format/)).\n\n## Requirements\n\n* **Python>=3.7**\n* networkx>=2.1\n* pandas>=1.1.0\n\n## Install\n\nPackage is available to install on [PyPI](https://pypi.org/project/networkx-gdf/):\n\n```bash\npip install networkx-gdf\n```\n\n## Usage\n\nJust two functions are implemented, for reading from and writing data to file.\n\n```python\nfrom networkx_gdf import read_gdf, write_gdf\n\n# Builds NetworkX graph object from file.\nG = read_gdf(\"input_file.gdf\")\n\n# Writes NetworkX graph object to file.\nwrite_gdf(G, \"output_file.gdf\")\n```\n\n### Detailed usage\n\nA few additional arguments are available both for reading and writing files:\n\n#### Building NetworkX graph object from file\n\n```python\nG = read_gdf(\n \"input_file.gdf\",\n # Required; file path to read data from.\n\n directed=None,\n # Optional; consider edges as directed or undirected.\n # True: returns a <nx.DiGraph> or <nx.MultiDiGraph> object.\n # False: returns a <nx.Graph> or <nx.MultiGraph> object.\n # None (default): decides based on \"directed\" edge attribute in file.\n\n multigraph=None,\n # Optional; consider multiple or single edges among nodes.\n # True: always returns a <nx.MultiGraph> or <nx.MultiDiGraph> object.\n # False: sums edge weights and returns a <nx.Graph> or <nx.DiGraph> object.\n # None (default): decides based on number of edges among the same pair of nodes.\n\n node_attr=None,\n # Optional; node attributes to import data from.\n # Accepts either a list containing attribute names or a boolean (True, False).\n # Defaults to True, which considers all node attributes.\n\n edge_attr=None,\n # Optional; edge attributes to import data from.\n # Accepts either a list containing attribute names or a boolean (True, False).\n # Defaults to True, which considers all edge attributes.\n)\n```\n\n#### Writing NetworkX graph object to file\n\n```python\nwrite_gdf(\n G,\n # Required; graph object from NetworkX.\n\n \"output_file.gdf\",\n # Required; file path to write data to.\n\n node_attr=None,\n # Optional; node attributes to export data from.\n # Accepts either a list containing attribute names or a boolean (True, False).\n # Defaults to True, which considers all node attributes.\n\n edge_attr=None,\n # Optional; edge attributes to export data from.\n # Accepts either a list containing attribute names or a boolean (True, False).\n # Defaults to True, which considers all edge attributes.\n)\n```\n\nNote that any object types beyond integers/longs, floats/doubles, and booleans will be considered as strings.\n\n### Importing as a class\n\nAlternatively, the module can also be imported as a class and inherited:\n\n```python\nfrom networkx_gdf import GDF\n\nclass MyClass(GDF):\n ...\n\nG = MyClass.read_gdf(\"input_file.gdf\")\nMyClass.write_gdf(G, \"output_file.gdf\")\n```\n\nBoth functions are implemented as static methods, so initializing the class as an object is not required.\n\n___\n\n### References\n\n* [NetworkX](https://networkx.github.io)\n* [Pandas](https://pandas.pydata.org/)\n",
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