This directory contains tests for most parts of MicroPython.
To run all stable tests, run the "run-tests.py" script in this directory. By default that will run the test suite against the unix port of MicroPython.
To run the test suite against a bare-metal target (a board running MicroPython firmware)
use the -t
option to specify the serial port. This will automatically detect the
target platform and run the appropriate set of tests for that platform. For example:
$ ./run-tests.py -t /dev/ttyACM0
That will run tests on the /dev/ttyACM0
serial port. You can also use shortcut
device names like a<n>
for /dev/ttyACM<n>
and c<n>
for COM<n>
. Use
./run-tests.py --help
to see all of the device possibilites, and other options.
There are three kinds of tests:
-
Tests that use
unittest
: these tests requireunittest
to be installed on the target (eg viampremote mip install unittest
), and are used to test things that are MicroPython-specific, such as behaviour that is different to CPython, modules that aren't available in CPython, and hardware tests. These tests are run only under MicroPython and the test passes if theunittest
runner prints "OK" at the end of the run. Other output may be printed, eg for use as diagnostics, and this output does not affect the result of the test. -
Tests with a corresponding
.exp
file: similar to theunittest
tests, these tests are for features that generally cannot be run under CPython. In this case the test is run under MicroPython only and the output from MicroPython is compared against the provided.exp
file. The test passes if the output matches exactly. -
Tests without a corresponding
.exp
file (and don't useunittest
): these tests are used to test MicroPython behaviour that should precisely match CPython. These tests are first run under CPython and the output captured, and then run under MicroPython and the output compared to the CPython output. The test passes if the output matches exactly. If the output differs then the test fails and the outputs are saved in a.exp
and a.out
file respectively.
In all three cases above, the test can usually be run directly on the target MicroPython
instance, either using the unix port with micropython <test.py>
, or on a board with
mpremote run <test.py>
. This is useful for creating and debugging tests.
Tests of capabilities not supported on all platforms should be written to check for the capability being present. If it is not, the test should merely output 'SKIP' followed by the line terminator, and call sys.exit() to raise SystemExit, instead of attempting to test the missing capability. The testing framework (run-tests.py in this directory, test_main.c in qemu_arm) recognizes this as a skipped test.
There are a few features for which this mechanism cannot be used to condition a test. The run-tests.py script uses small scripts in the feature_check directory to check whether each such feature is present, and skips the relevant tests if not.
When creating new tests, anything that relies on float support should go in the float/ subdirectory. Anything that relies on import x, where x is not a built-in module, should go in the import/ subdirectory.
The perf_bench
directory contains some performance benchmarks that can be used
to benchmark different MicroPython firmwares or host ports.
The runner utility is run-perfbench,py
. Execute ./run-perfbench.py --help
for a full list of command line options.
To run tests on a firmware target using pyboard.py
, run the command line like
this:
./run-perfbench.py -p -d /dev/ttyACM0 168 100
-p
indicates running on a remote target via pyboard.py, not the host.-d PORTNAME
is the serial port,/dev/ttyACM0
is the default if not provided.168
is valueN
, the approximate CPU frequency in MHz (in this case Pyboard V1.1 is 168MHz). It's possible to choose other values as well: lower values like10
will run much the tests much quicker, higher values like1000
will run much longer.100
is valueM
, the approximate heap size in kilobytes (can get this fromimport micropython; micropython.mem_info()
or estimate it). It's possible to choose other values here too: lower values like10
will run shorter/smaller tests, and higher values will run bigger tests. The maximum value ofM
is limited by available heap, and the tests are written so the "recommended" value is approximately the upper limit.
To benchmark the host build (unix/Windows), run like this:
./run-perfbench.py 2000 10000
The output of perfbench is a list of tests and times/scores, like this:
N=2000 M=10000 n_average=8
perf_bench/bm_chaos.py: SKIP
perf_bench/bm_fannkuch.py: 94550.38 2.9145 84.68 2.8499
perf_bench/bm_fft.py: 79920.38 10.0771 129269.74 8.8205
perf_bench/bm_float.py: 43844.62 17.8229 353219.64 17.7693
perf_bench/bm_hexiom.py: 32959.12 15.0243 775.77 14.8893
perf_bench/bm_nqueens.py: 40855.00 10.7297 247776.15 11.3647
perf_bench/bm_pidigits.py: 64547.75 2.5609 7751.36 2.5996
perf_bench/core_import_mpy_multi.py: 15433.38 14.2733 33065.45 14.2368
perf_bench/core_import_mpy_single.py: 263.00 11.3910 3858.35 12.9021
perf_bench/core_qstr.py: 4929.12 1.8434 8117.71 1.7921
perf_bench/core_yield_from.py: 16274.25 6.2584 12334.13 5.8125
perf_bench/misc_aes.py: 57425.25 5.5226 17888.60 5.7482
perf_bench/misc_mandel.py: 40809.25 8.2007 158107.00 9.8864
perf_bench/misc_pystone.py: 39821.75 6.4145 100867.62 6.5043
perf_bench/misc_raytrace.py: 36293.75 6.8501 26906.93 6.8402
perf_bench/viper_call0.py: 15573.00 14.9931 19644.99 13.1550
perf_bench/viper_call1a.py: 16725.75 9.8205 18099.96 9.2752
perf_bench/viper_call1b.py: 20752.62 8.3372 14565.60 9.0663
perf_bench/viper_call1c.py: 20849.88 5.8783 14444.80 6.6295
perf_bench/viper_call2a.py: 16156.25 11.2956 18818.59 11.7959
perf_bench/viper_call2b.py: 22047.38 8.9484 13725.73 9.6800
The numbers across each line are times and scores for the test:
- Runtime average (microseconds, lower is better)
- Runtime standard deviation as a percentage
- Score average (units depend on the benchmark, higher is better)
- Score standard deviation as a percentage
Usually you want to know if something is faster or slower than a reference. To
do this, copy the output of each run-perfbench.py
run to a text file.
This can be done multiple ways, but one way on Linux/macOS is with the tee
utility: ./run-perfbench.py -p 168 100 | tee pyb-run1.txt
Once you have two files with output from two different runs (maybe with
different code or configuration), compare the runtimes with ./run-perfbench.py -t pybv-run1.txt pybv-run2.txt
or compare scores with ./run-perfbench.py -s pybv-run1.txt pybv-run2.txt
:
> ./run-perfbench.py -s pyb-run1.txt pyb-run2.txt
diff of scores (higher is better)
N=168 M=100 pyb-run1.txt -> pyb-run2.txt diff diff% (error%)
bm_chaos.py 352.90 -> 352.63 : -0.27 = -0.077% (+/-0.00%)
bm_fannkuch.py 77.52 -> 77.45 : -0.07 = -0.090% (+/-0.01%)
bm_fft.py 2516.80 -> 2519.74 : +2.94 = +0.117% (+/-0.00%)
bm_float.py 5749.27 -> 5749.65 : +0.38 = +0.007% (+/-0.00%)
bm_hexiom.py 42.22 -> 42.30 : +0.08 = +0.189% (+/-0.00%)
bm_nqueens.py 4407.55 -> 4414.44 : +6.89 = +0.156% (+/-0.00%)
bm_pidigits.py 638.09 -> 632.14 : -5.95 = -0.932% (+/-0.25%)
core_import_mpy_multi.py 477.74 -> 477.57 : -0.17 = -0.036% (+/-0.00%)
core_import_mpy_single.py 58.74 -> 58.72 : -0.02 = -0.034% (+/-0.00%)
core_qstr.py 63.11 -> 63.11 : +0.00 = +0.000% (+/-0.01%)
core_yield_from.py 357.57 -> 357.57 : +0.00 = +0.000% (+/-0.00%)
misc_aes.py 397.27 -> 396.47 : -0.80 = -0.201% (+/-0.00%)
misc_mandel.py 3375.70 -> 3375.84 : +0.14 = +0.004% (+/-0.00%)
misc_pystone.py 2265.36 -> 2265.97 : +0.61 = +0.027% (+/-0.01%)
misc_raytrace.py 367.61 -> 368.15 : +0.54 = +0.147% (+/-0.01%)
viper_call0.py 605.92 -> 605.92 : +0.00 = +0.000% (+/-0.00%)
viper_call1a.py 576.78 -> 576.78 : +0.00 = +0.000% (+/-0.00%)
viper_call1b.py 452.45 -> 452.46 : +0.01 = +0.002% (+/-0.01%)
viper_call1c.py 457.39 -> 457.39 : +0.00 = +0.000% (+/-0.00%)
viper_call2a.py 561.37 -> 561.37 : +0.00 = +0.000% (+/-0.00%)
viper_call2b.py 389.49 -> 389.50 : +0.01 = +0.003% (+/-0.01%)
Note in particular the error percentages at the end of each line. If these are
high relative to the percentage difference then it indicates high variability in
the test runs, and the absolute difference value is unreliable. High error
percentages are particularly common on PC builds, where the host OS may
influence test run times. Increasing the N
value may help average this out by
running each test longer.
The internal_bench
directory contains a set of tests for benchmarking
different internal Python features. By default, tests are run on the (unix or
Windows) host, but the --pyboard
option allows them to be run on an attached
board instead.
Tests are grouped by the first part of the file name, and the test runner compares output between each group of tests.
The benchmarks measure the elapsed (wall time) for each test, according to MicroPython's own time module.
If run without any arguments, all test groups are run. Otherwise, it's possible to manually specify which test cases to run.
Example:
$ ./run-internalbench.py internal_bench/bytebuf-*.py
internal_bench/bytebuf:
0.094s (+00.00%) internal_bench/bytebuf-1-inplace.py
0.471s (+399.24%) internal_bench/bytebuf-2-join_map_bytes.py
0.177s (+87.78%) internal_bench/bytebuf-3-bytarray_map.py
1 tests performed (3 individual testcases)
SSL/TLS tests in multi_net
and net_inet
use self-signed key/cert pairs
that are randomly generated to be used for testing/demonstration only.
To run tests on-device the .der
files should be copied and the current time
set to ensure certs validity. This can be done with:
$ mpremote rtc --set cp multi_net/*.der net_inet/*.der :
The keys used for the unit tests are included in the tests folders so don't generally need to be re-created by end users. This section is included here for reference only.
A new self-signed RSA key/cert pair can be created with openssl:
$ openssl req -x509 -newkey rsa:2048 -keyout rsa_key.pem -out rsa_cert.pem -days 365 -nodes -subj '/CN=micropython.local/O=MicroPython/C=AU'
In this case CN is: micropython.local
Convert them to DER format:
$ openssl pkey -in rsa_key.pem -out rsa_key.der -outform DER
$ openssl x509 -in rsa_cert.pem -out rsa_cert.der -outform DER
For elliptic curve tests using key/cert pairs, create a key then a certificate using:
$ openssl ecparam -name prime256v1 -genkey -noout -out ec_key.pem
$ openssl x509 -in ec_key.pem -out ec_key.der -outform DER
$ openssl req -new -x509 -key ec_key.pem -out ec_cert.der -outform DER -days 365 -nodes -subj '/CN=micropython.local/O=MicroPython/C=AU'