# MicroPM4Py
## Introduction
MicroPM4Py is a Python 3/Micropython library that aims to take Process Mining features in power/feature constrained environments, including microcontrollers and embedded systems.
The set of supported features is minimal in comparison to other process mining libraries, like PM4Py, and require no Python dependencies to work.
Official website: [https://www.micropm4py.org](https://www.micropm4py.org)
Micropython website: [https://micropython.org](https://micropython.org)
## Target Hardware
MicroPM4Py can be virtually run on any hardware, even very old or with very low resources/power consumption or embedded systems, since it is compatible with the Python3/Micropython stacks.
MicroPM4Py has been tested at less than 1 MHz on the Unicorn emulator (CPU: Cortex M3, stack: 8 kb, RAM: 64 kb).
MicroPM4Py has been physically tested on a Raspberry Pi 3 B+ (4xA53 @ 1.4 GHz, 1 GB LPDDR2 RAM).
## Installation
On any platform running Python 3: the installation can be easily performed using PIP: pip install -U micropm4py
On Micropython controllers / embedded systems: follow the instructions of your specific board (see the Micropython website). In particular, given the resource constrained environments, some ad-hoc cutting-and-paste of code needs to be done (for example, combining in a single script the XES, PNML and token-based replay).
## Features
Log importing/exporting
XES importer (level A-1, only case ID and activity)
XES exporter (level A-1, only case ID and activity)
CSV importer (only case ID and activity, support for the specification of the separator)
CSV exporter (only case ID and activity, support for the specification of th separator
Importing of DFGs from XES (without keeping the log in-memory)
Importing of DFGs from CSV (without keeping the log in-memory)
Importing/Exporting of .dfg files
Support for the insertion of artificial start-end activities
Conversion of log to DFG
Petri Nets
Execution semantics * Token-based replay (without support for invisible transitions) * Alignments (without support for invisible transitions) * Importing of PNML files * Exporting of PNML files * Conversions
Conversion of DFG to Petri net (DFG mining) * Conversion of MicroPM4Py DFG to PM4Py DFG * Conversion from/to MicroPM4Py log to PM4Py log * Conversion from/to MicroPM4Py Petri nets to PM4Py Petri nets * Visualizations
Visualizations * DOT visualization of DFGS * DOT visualization of Petri nets
1 maintainer
Metadata
1 maintainer
Release files for micropm4py 0.2.1
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