pm4py: PM4PY for R

In pm4py: Interface to the 'PM4py' Process Mining Library

Description

This package provides access to the Python Process Mining library PM4PY in R and provides conversion between bupaR and PM4PY data structures.

Usage

pm4py

Format

An object of class python.builtin.module (inherits from python.builtin.object) of length 2.

Details

To use this package, you need to have a Python environment (Conda or virtualenv) installed and install the PM4PY package and its dependencies. You can use the convenience function install_pm4py to let reticulate take care of install the right version. See the documentation of this function for further information.

When loaded, the object pm4py provides the low-level interface to the main PM4PY module. Use $ to access sub modules of PM4PY as described in the reticulate documentation:

vignette("calling_python", package = "reticulate")

For parts of PM4PY wrapper functions are provided to transparently convert parameters and results to and from the corresponding bupaR S3 classes.

Examples

# Print the PM4PY version loaded
if (pm4py_available()) {
  print(pm4py$`__version__`)
}

pm4py documentation built on Jan. 8, 2020, 1:08 a.m.