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

Project description

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

Dagre

Metro

Visualization in the terminal

To get a string representing the graph (code from: https://github.com/ctongfei/py-dagviz):

from cwl2nx import cwl_to_str

dir = "workflow_example.cwl.yaml"
print(cwl_to_str(dir))

output :

• input_file_1.json
│ • parameter.py
│ │ • config.yaml
╰─│─┴─• init_task
  │   ╰─• init_task/initialized_dataset.json
  ╰─────┼─• inter_task_1
        ╰─│─• inter_task_2
          ╰─│─• inter_task_1/output_inter_1
            ╰─│─• inter_task_2/output_inter_2
              ╰─┴─• end_task
                  ╰─• wf_output

Link with cwl-utils

Each node of the parsed networkx graph object has an attribute cwl_utils_object containing the cwl_utils object, among the following :

  • WorkflowStep
  • WorkflowStepInput
  • WorkflowStepOutput
  • WorkflowInputParameter
  • WorkflowOutputParameter

License

Apache 2.0

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