Command-line controller for AKAI MPKmini MK II.
Project description
Command-line controller for AKAI MPKmini MK II
Best effort project to overcome the fact that AKAI doesn't seem to be interested in fixing Segmentation faults in their MPKmini Editor.
It currently fixes my own itches but I gladly accept feedback!
Install
To install via PyPi:
To install from source you can use:
python3 setup.py install
, ormake install
which will run apipenv
including linting, tests, etc.
Usage
akai_mpkmini_mkii_ctrl
supports a set of commands to push or pull presets to and from the device. All commands have a common set of options:
-p, --preset NUM Target preset slot (0 = RAM, 1-4 = Stored preset)
-m, --midi-port NUM MIDI port (0 = Omni, > 0 = Specific MIDI port)
-v, --verbose Verbose output
--help Show this message and exit.
Commands
print-preset
: Print preset on device in human readable format. In this example it will print the preset stored in slot 1 on the device.
python3 -m akai_mpkmini_mkii_ctrl \
--preset 1 print-preset
pull-preset
: Pull a binary from the device and write to file.
python3 -m akai_mpkmini_mkii_ctrl \
--preset 0 \
pull-preset \
--output-file ram-preset.mk2
push-preset
: Push a local binary preset to the device. This also works with factory binary presets.
python3 -m akai_mpkmini_mkii_ctrl \
--preset 2 \
push-preset \
--input-file resources/factory-patches/preset1.mk2
push-json-preset
: Push a local JSON preset (Example) to the device. Notice that you are able to combine several input files for easier re-use. The configurations are applied in order, e.g., in this case Logic-Base.json
will be extended with the properties found in Logic-RetroSynth+Juno.json
.
python3 -m akai_mpkmini_mkii_ctrl \
--preset 0 \
push-json-preset \
--input-file resources/json-presets/Logic-Base.json \
--input-file resources/json-presets/Logic-RetroSynth+Juno.json
Development
You can prepare a pipenv
-based development environment using:
make clean venv
You can also install the controller to your system using:
make install
Resources
The implementation is based upon the following resources:
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