cwl2nx 0.0.7

Lightweight python module to load, validate and visualize CWL (Common Workflow Language) files through networkx graphs.

CWL2Nx

Lightweight python module to load, validate and visualize CWL (Common Workflow Language) files through networkx graphs. It uses cwl_utils for parsing and validation.

Installation

pip install cwl2nx

Example Usage

You will find an example of workflow in the GitHub repository : workflow_example.cwl.yaml. Other examples can be found here : https://workflowhub.org

Straightforward conversion

from cwl2nx import CWLToNetworkxConnector

dir = "workflow_example.cwl.yaml"
dag = CWLToNetworkxConnector(dir).convert_to_networkx() # dag is networkx.DiGraph
print(dag.nodes, dag.edges)

Using dagviz

You'll need to install dagviz before

/!\ you need to run the code below in a jupyter notebook

from cwl2nx import CWLToNetworkxConnector
import networkx as nx
import dagviz

dir = "workflow_example.cwl.yaml"
connector = CWLToNetworkxConnector(dir)
dag = connector.convert_to_networkx()


dagviz.Dagre(dag)

dagviz.Metro(dag) # github tree dag style

Visualization in the terminal

To get a light visualization of the workflow in the terminal, just use the code from this GitHub repo https://github.com/ctongfei/py-dagviz/blob/main/dagviz.py and import visualize_dag function :

from cwl2nx import CWLToNetworkxConnector
import networkx as nx

dir = "workflow_example.cwl.yaml"
dag = CWLToNetworkxConnector(dir).convert_to_networkx(datasets_as_node=True)
print(visualization_function(dag))

output :

• #nsbas.proc
│ • #nsbas_config.json
│ │ • #parameter.py
╰─┴─│─• #tache_init
    │ ╰─• ivwgayim.dep
    ╰───┼─• #tache_inter1
        ╰─│─• #tache_inter2
          │ ╰─• azbouvks2.dep
          ╰───│─• azbouvks1.dep
              ╰─┴─• #tache_end
                  ╰─• agxlvirt.dep

Basic networkx display

from cwl2nx import CWLToNetworkxConnector
import networkx as nx
import matplotlib.pyplot as plt

dir = "workflow_example.cwl.yaml"
connector = CWLToNetworkxConnector(dir)
dag = connector.convert_to_networkx(datasets_as_nodes=True)
nx.draw_networkx(dag)
plt.show()

License

Apache 2.0