It is great honor and responsibility for the PM4Py team to announce the first official release of the Process Mining for Python library (PM4Py), i.e. PM4Py 1.0. The main motivations for this new library are:
- Providing more freedom in performing a process mining analysis w.r.t. existing academical tools such as ProM, RapidProM and AproMore.
- Allowing to combine process mining algorithms with algorithms from other data science fields, implemented in various state-of-the-art python packages.
- Reducing the time needed for the replication of scientific experiments regarding Process Mining, in comparison to other open-source Process Mining tools.
- Reducing the entry level needed to apply and develop Process Mining techniques.
- Creating a collaborative eco-system (through the git repo) that easily allows researchers and practitioners to share valuable code and results with the process mining world.
The library is well-documented (let us be honest, this is sometimes lacking in academic software) and, furthermore, we have developed a large body of tests to guarantee the stability of the code. A baseline set of features has been implemented to ease the use of Process Mining algorithms in python, including process discovery, conformance checking, log importing/exporting, models importing/exporting, visualization, frequency/performance annotation, scalability to big logs.
During informal bench-marking, we have found that the library achieves better performance than other Process Mining open-source solutions, especially when bigger logs are taken into account.
Some comments from Alessandro Berti, a Software Engineer of the PADS and lead-developer of the PM4Py project:
“This is a wonderful moment, the culmination of the work of the team, to release a first version of this library achieving the goals of reducing the entry level, increase documentation and tests, and also increase performance in comparison to the state-of-the-art Process Mining open-source tools. As my personal experience, depending on the programming skills of a person, it may take months to be able to develop Process Mining techniques in other open-source Process Mining environments. The amount of time needed for being able to program in PM4Py is averagely less than two weeks! This thanks to the documentation provided to the users, both at the code level and in the examples provided. It’s still early days, but things look promising over all fronts.”.