asammdf is a fast parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF (Measurement Data Format) files.

asammdf supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4).

asammdf works on Python >= 3.6 (for Python 2.7, 3.4 and 3.5 see the 4.x.y releases)

Project goals

The main goals for this library are:

  • to be faster than the other Python based mdf libraries
  • to have clean and easy to understand code base
  • to have minimal 3-rd party dependencies


  • create new mdf files from scratch
  • append new channels
  • read unsorted MDF v3 and v4 files
  • read CAN and LIN bus logging files
  • extract CAN and LIN signals from anonymous bus logging measurements
  • filter a subset of channels from original mdf file
  • cut measurement to specified time interval
  • convert to different mdf version
  • export to HDF5, Matlab (v4, v5 and v7.3), CSV and parquet
  • merge multiple files sharing the same internal structure
  • read and save mdf version 4.10 files containing zipped data blocks
  • space optimizations for saved files (no duplicated blocks)
  • split large data blocks (configurable size) for mdf version 4
  • full support (read, append, save) for the following map types (multidimensional array channels):
  • mdf version 3 channels with CDBLOCK
  • mdf version 4 structure channel composition
  • mdf version 4 channel arrays with CNTemplate storage and one of the array types:
  • 0 - array
  • 1 - scaling axis
  • 2 - look-up
  • add and extract attachments for mdf version 4
  • handle large files (for example merging two fileas, each with 14000 channels and 5GB size, on a RaspberryPi)
  • extract channel data, master channel and extra channel information as Signal objects for unified operations with v3 and v4 files
  • time domain operation using the Signal class
  • Pandas data frames are good if all the channels have the same time based
  • a measurement will usually have channels from different sources at different rates
  • the Signal class facilitates operations with such channels
  • graphical interface to visualize channels and perform operations with the files

Major features not implemented (yet)

  • for version 3
  • functionality related to sample reduction block: the samples reduction blocks are simply ignored
  • for version 4
  • experiemental support for MDF v4.20 column oriented storage
  • functionality related to sample reduction block: the samples reduction blocks are simply ignored
  • handling of channel hierarchy: channel hierarchy is ignored
  • full handling of bus logging measurements: currently only CAN and LIN bus logging are implemented with the ability to get signals defined in the attached CAN/LIN database (.arxml or .dbc). Signals can also be extracted from an anonymous bus logging measurement by providing a CAN or LIN database (.dbc or .arxml)
  • handling of unfinished measurements (mdf 4): finalization is attempted when the file is loaded, however the not all the finalization steps are supported
  • full support for remaining mdf 4 channel arrays types
  • xml schema for MDBLOCK: most metadata stored in the comment blocks will not be available
  • full handling of event blocks: events are transfered to the new files (in case of calling methods that return new MDF objects) but no new events can be created
  • channels with default X axis: the defaukt X axis is ignored and the channel group's master channel is used
  • attachment encryption/decryption using user provided encryption/decryption functions; this is not part of the MDF v4 spec and is only supported by this library


from asammdf import MDF

mdf = MDF('sample.mdf')
speed = mdf.get('WheelSpeed')

important_signals = ['WheelSpeed', 'VehicleSpeed', 'VehicleAcceleration']
# get short measurement with a subset of channels from 10s to 12s
short = mdf.filter(important_signals).cut(start=10, stop=12)

# convert to version 4.10 and save to disk
short.convert('4.10').save('important signals.mf4')

# plot some channels from a huge file
efficient = MDF('huge.mf4')
for signal in['Sensor1', 'Voltage3']):

Check the examples folder for extended usage demo, or the documentation


asammdf is available on




pip install asammdf

for the GUI

pip install asammdf[gui]

or for anaconda

conda install -c conda-forge asammdf

In case a wheel is not present for you OS/Python versions and you lack the proper compiler setup to compile the c-extension code, then you can simply copy-paste the pacakge code to your site-packages. In this way the python fallback code will be used instead of the compiled c-extension code.


asammdf uses the following libraries

  • numpy : the heart that makes all tick
  • numexpr : for algebraic and rational channel conversions
  • wheel : for installation in virtual environments
  • pandas : for DataFrame export
  • canmatrix : to handle CAN/LIN bus logging measurements
  • natsort
  • lxml : for canmatrix arxml support
  • lz4 : to speed up the disk IO peformance

optional dependencies needed for exports

  • h5py : for HDF5 export
  • scipy : for Matlab v4 and v5 .mat export
  • hdf5storage : for Matlab v7.3 .mat export
  • fastparquet : for parquet export

other optional dependencies

  • PyQt5 : for GUI tool
  • pyqtgraph : for GUI tool and Signal plotting
  • matplotlib : as fallback for Signal plotting
  • cChardet : to detect non-standard unicode encodings
  • chardet : to detect non-standard unicode encodings
  • pyqtlet : for GPS window


GitHub - danielhrisca/asammdf: Fast Python reader and editor for ASAM MDF / MF4 (Measurement Data Format) files
Fast Python reader and editor for ASAM MDF / MF4 (Measurement Data Format) files - GitHub - danielhrisca/asammdf: Fast Python reader and editor for ASAM MDF / MF4 (Measurement Data Format) files