pypowsybl 1.15.0

A PowSyBl Python API

PyPowSyBl

Python code quality :

Java code quality :

The PyPowSyBl project gives access PowSyBl Java framework to Python developers. This Python integration relies on GraalVM to compile Java code to a native library.

Documentation

Latest version of the documentation with API reference and many code samples is here.

To contribute to the documentation follow the instructions in the documentation README page.

Notebooks

Notebooks demonstrating PyPowSyBl features can be found in this repository.

Installation

PyPowSyBl is released on PyPi for Python 3.10 to 3.14, on Linux, Windows and MacOS.

First, make sure you have an up-to-date version of pip and setuptools:

pip install --upgrade setuptools pip

Then you can install PyPowSyBl using pip:

pip install pypowsybl

Contributing

See Contributing.md for explanations on how to contribute to the code.

See Security.md to read about the security policy.

Getting started

First, we have to import pypowsybl:

import pypowsybl as pp

We can create an IEEE 14 buses network and run a load flow computation:

n = pp.network.create_ieee14()
results = pp.loadflow.run_ac(n)
print(results)

[ComponentResult(connected_component_num=0, synchronous_component_num=0, status=CONVERGED, status_text=CONVERGED, iteration_count=3, reference_bus_id='VL1_0', slack_bus_results=[SlackBusResult(id='VL1_0', active_power_mismatch=-0.006730108618313579)], distributed_active_power=0.0)]

We can now get buses data (like any other network elements) as a Pandas dataframe:

buses = n.get_buses()
print(buses)

        v_mag  v_angle
VL1_0   1.060     0.00
VL2_0   1.045    -4.98
VL3_0   1.010   -12.72
VL4_0   1.019   -10.33
VL5_0   1.020    -8.78
VL6_0   1.070   -14.22
VL7_0   1.062   -13.37
VL8_0   1.090   -13.36
VL9_0   1.056   -14.94
VL10_0  1.051   -15.10
VL11_0  1.057   -14.79
VL12_0  1.055   -15.07
VL13_0  1.050   -15.16
VL14_0  1.036   -16.04

This is just a quick appetizer of PyPowSyBl features. PyPowsybl provides a lot more features: security analysis, sensitivity analysis, handling of multiple file formats (including CGMES), substation and network diagrams generation, ... For more details and examples, go to the documentation and Jupyter notebooks.

Build from sources

That section is intended for developers who wish to build pypowsybl from the sources in this repository.

Requirements:

• Maven >= 3.1
• Cmake >= 3.20
• C++11 compiler
• Python >= 3.10 for Linux, Windows and MacOS (amd64 and arm64)
• Oracle GraalVM Java 21

To build from sources and install PyPowSyBl package:

git clone https://github.com/powsybl/pypowsybl.git
cd pypowsybl
export JAVA_HOME=<path to GraalVM>
pip install --upgrade setuptools pip
pip install -r requirements.txt
pip install .

While developing, you may find it convenient to use the developer (or editable) mode of installation:

pip install -e .
# or, to build the C extension with debug symbols:
python setup.py build --debug develop --user

Please refer to pip and setuptools documentations for more information.

To run unit tests:

pytest tests

To run static type checking with mypy:

mypy -p pypowsybl

To run linting inspection with pylint:

pylint pypowsybl