This document describes some of the Klipper debugging tools.
Translating gcode files to micro-controller commands
The Klippy host code can run in a batch mode to produce the low-level micro-controller commands associated with a gcode file. Inspecting these low-level commands is useful when trying to understand the actions of the low-level hardware. It can also be useful to compare the difference in micro-controller commands after a code change.
To run Klippy in this batch mode, there is a one time step necessary to generate the micro-controller “data dictionary”. This is done by compiling the micro-controller code to obtain the out/klipper.dict file:
make menuconfig make
Once the above is done it is possible to run Klipper in batch mode (see installation for the steps necessary to build the python virtual environment and a printer.cfg file):
~/klippy-env/bin/python ./klippy/klippy.py ~/printer.cfg -i test.gcode -o test.serial -v -d out/klipper.dict
The above will produce a file test.serial with the binary serial output. This output can be translated to readable text with:
~/klippy-env/bin/python ./klippy/parsedump.py out/klipper.dict test.serial > test.txt
The resulting file test.txt contains a human readable list of micro-controller commands.
The batch mode disables certain response / request commands in order to function. As a result, there will be some differences between actual commands and the above output. The generated data is useful for testing and inspection; it is not useful for sending to a real micro-controller.
Testing with simulavr
The simulavr tool enables one to simulate an Atmel ATmega micro-controller. This section describes how one can run test gcode files through simulavr. It is recommended to run this on a desktop class machine (not a Raspberry Pi) as it does require significant cpu to run efficiently.
To use simulavr, download the simulavr package and compile with python support:
git clone git://git.savannah.nongnu.org/simulavr.git cd simulavr ./bootstrap ./configure --enable-python make
Note that the build system may need to have some packages (such as swig) installed in order to build the python module. Make sure the file src/python/_pysimulavr.so is present after the above compilation.
To compile Klipper for use in simulavr, run:
cd /patch/to/klipper make menuconfig
and compile the micro-controller software for an AVR atmega644p, set
the MCU frequency to 20Mhz, and select SIMULAVR software emulation
support. Then one can compile Klipper (run
make) and then start the
PYTHONPATH=/path/to/simulavr/src/python/ ./scripts/avrsim.py -m atmega644 -s 20000000 -b 250000 out/klipper.elf
Then, with simulavr running in another window, one can run the following to read gcode from a file (eg, “test.gcode”), process it with Klippy, and send it to Klipper running in simulavr (see installation for the steps necessary to build the python virtual environment):
~/klippy-env/bin/python ./klippy/klippy.py config/avrsim.cfg -i test.gcode -v
Using simulavr with gtkwave
One useful feature of simulavr is its ability to create signal wave generation files with the exact timing of events. To do this, follow the directions above, but run avrsim.py with a command-line like the following:
PYTHONPATH=/path/to/simulavr/src/python/ ./scripts/avrsim.py -m atmega644 -s 20000000 -b 250000 out/klipper.elf -t PORTA.PORT,PORTC.PORT
The above would create a file avrsim.vcd with information on each change to the GPIOs on PORTA and PORTB. This could then be viewed using gtkwave with:
Manually sending commands to the micro-controller
Normally, the host klippy.py process would be used to translate gcode commands to Klipper micro-controller commands. However, it’s also possible to manually send these MCU commands (functions marked with the DECL_COMMAND() macro in the Klipper source code). To do so, run:
~/klippy-env/bin/python ./klippy/console.py /tmp/pseudoserial 250000
See the “HELP” command within the tool for more information on its functionality.
Generating load graphs
The Klippy log file (/tmp/klippy.log) stores statistics on bandwidth, micro-controller load, and host buffer load. It can be useful to graph these statistics after a print.
To generate a graph, a one time step is necessary to install the “matplotlib” package:
sudo apt-get update sudo apt-get install python-matplotlib
Then graphs can be produced with:
~/klipper/scripts/graphstats.py /tmp/klippy.log -o loadgraph.png
One can then view the resulting loadgraph.png file.
Different graphs can be produced. For more information run:
Extracting information from the klippy.log file
The Klippy log file (/tmp/klippy.log) also contains debugging information. There is a logextract.py script that may be useful when analyzing a micro-controller shutdown or similar problem. It is typically run with something like:
mkdir work_directory cd work_directory cp /tmp/klippy.log . ~/klipper/scripts/logextract.py ./klippy.log
The script will extract the printer config file and will extract MCU shutdown information. The information dumps from an MCU shutdown (if present) will be reordered by timestamp to assist in diagnosing cause and effect scenarios.
Running the regression tests
The main Klipper GitHub repository uses TravisCI to run a series of regression tests. It can be useful to run some of these tests locally.
The source code “whitespace check” can be run with:
The Klippy regression test suite requires “data dictionaries” from many platforms. The easiest way to obtain them is to download them from github. Once the data dictionaries are downloaded, use the following to run the regression suite:
tar xfz klipper-dict-20??????.tar.gz ~/klippy-env/bin/python ~/klipper/scripts/test_klippy.py -d dict/ ~/klipper/test/klippy/*.test