MIKE IO: input/output of MIKE files in Python
Read, write and manipulate dfs0, dfs1, dfs2, dfs3, dfsu and mesh files.
MIKE IO facilitates common data processing workflows for MIKE files using Python.
Requirements
- Windows or Linux operating system
- Python x64 3.12 - 3.15
- (Windows) VC++ redistributables (already installed if you have MIKE)
Installation
pip install mikeio
:warning: Don't use conda to install MIKE IO! The version on conda-forge is several major versions behind.
Getting started
Read a file into a Dataset — a collection of named DataArrays sharing time and geometry:
>>> import mikeio
>>> ds = mikeio.read("HD2D.dfsu")
>>> ds
<mikeio.Dataset>
title: Output 1
dims: (time:9, element:884)
time: 1985-08-06 07:00:00 - 1985-08-07 03:00:00 (9 records)
geometry: Dfsu2D (884 elements, 529 nodes)
items:
0: Surface elevation <Surface Elevation> (meter)
1: U velocity <u velocity component> (meter per sec)
2: V velocity <v velocity component> (meter per sec)
3: Current speed <Current Speed> (meter per sec)
Select an item and extract a time series at a point:
>>> da = ds["Surface elevation"]
>>> da.sel(x=606200, y=6905480)
<mikeio.DataArray>
name: Surface elevation
dims: (time:9)
time: 1985-08-06 07:00:00 - 1985-08-07 03:00:00 (9 records)
geometry: GeometryPoint2D(x=606202.7806372638, y=6905474.639383219)
values: [0.4595, 0.807, ..., -0.6322]
Convert to pandas, or write the result back to a dfs file:
>>> df = mikeio.read("da_diagnostic.dfs0").to_dataframe()
>>> ds.to_dfs("output.dfsu")
See the user guide for more.
Where can I get help?
Testing
MIKE IO is tested extensively, with an overall statement coverage of ~95%. The test suite runs on every pull request against Python 3.12 and 3.15, and on a schedule on both Linux and Windows.
uv run pytest --cov=mikeio
Contributing
Contributions are welcome — see CONTRIBUTING.md. Key architectural decisions are documented as ADRs.
License
BSD-3-Clause
