ad25d54300
e6cf0ed92de31a5ac35a271b0da8f0a8364d1175 wallet, rpc: listdescriptors does not need unlocked (Andrew Chow) 3280704886b60644d103a5eb310691c003a39328 Pass in DescriptorCache to ToNormalizedString (Andrew Chow) 7a26ff10c2f2e139fbc63e2f37fb33ea4efae088 Change DescriptorImpl::ToStringHelper to use an enum (Andrew Chow) 75530c93a83f3e94bcb78b6aa463c5570c1e737e Remove priv option for ToNormalizedString (Andrew Chow) 74fede3b8ba69e2cc82c617cdf406ab79df58825 wallet: Upgrade existing descriptor caches (Andrew Chow) 432ba9e5434da90d2cf680f23e8c7b7164c9f945 wallet: Store last hardened xpub cache (Andrew Chow) d87b544b834077f102724415e0fada6ee8b2def2 descriptors: Cache last hardened xpub (Andrew Chow) cacc3910989c4f3d7afa530dbab042461426abce Move DescriptorCache writing to WalletBatch (Andrew Chow) 0b4c8ef75cd03c8f0a8cfadb47e0fbcabe3c5e59 Refactor Cache merging and writing (Andrew Chow) 976b53b085d681645fd3a008fe382de85647e29f Revert "Cache parent xpub inside of BIP32PubkeyProvider" (Andrew Chow) Pull request description: Currently fetching a normalized descriptor requires the wallet to be unlocked as it needs the private keys to derive the last hardened xpub. This is not very user friendly as normalized descriptors shouldn't require and don't involve the private keys except for derivation. We solve this problem by caching the last hardened xpub (which has to be derived at some point when generating the address pool). However the last hardened xpub was not already being cached. We only cached the immediate parent xpub and derived child keys. For example, with a descriptor derivation path of `/84'/0'/0'/0/*`, the parent xpub that is cached is `m/84'/0'/0'/0`, and the child keys of `m/84'/0'/0'/0/i` (note that child keys would not be cached in this case). This parent xpub is not suitable for the normalized descriptor form as we want the key at `m/84'/0'/0'`. So this PR adds another field to `DescriptorCache` to cache the last hardened xpub so that we can use them for normalized descriptors. Since `DescriptorCache` is changing, existing descriptor wallets need to be upgraded to use this new cache. The upgrade will occur in the background either at loading time (if the wallet is not encrypted) or at unlocking time in the same manner that `UpgradeKeyMetadata` operates. It will use a new wallet flag `WALLET_FLAG_LAST_HARDENED_XPUB_CACHED` to indicate whether the descriptor wallet has the last hardened xpub cache. Lastly `listdescriptors` will not require the wallet to be locked and `getaddressinfo`'s `parent_desc` will always be output (assuming the upgrade has occurred). ACKs for top commit: fjahr: tACK e6cf0ed92de31a5ac35a271b0da8f0a8364d1175 S3RK: reACK e6cf0ed jonatack: Semi ACK e6cf0ed92de31a5ac35a271b0da8f0a8364d1175 reviewed, debug-built and ran unit tests and some of the descriptor functional tests at each commit. I'm not very familiar with this code and it could be clearer to the uninitiated IMHO, so I'm not confident enough to give a full ACK. Various minor suggestions follow, most of them for readability, feel free to pick and choose. meshcollider: Code review + functional test run ACK e6cf0ed92de31a5ac35a271b0da8f0a8364d1175 Tree-SHA512: ac27aade8644525cd65bfcaf27ff32afb974085b1451faf4ff68c6671a690bd6a41d4f39a33cbf461ae0fbe85995c0a4c08dbd36171da1c1d2a1d00053ad298d |
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.. | ||
functional | ||
fuzz | ||
lint | ||
sanitizer_suppressions | ||
util | ||
config.ini.in | ||
get_previous_releases.py | ||
README.md |
This directory contains integration tests that test dashd and its utilities in their entirety. It does not contain unit tests, which can be found in /src/test, /src/wallet/test, etc.
This directory contains the following sets of tests:
- functional which test the functionality of dashd and dash-qt by interacting with them through the RPC and P2P interfaces.
- util which tests the dash utilities, currently only dash-tx.
- lint which perform various static analysis checks.
The util tests are run as part of make check
target. The functional
tests and lint scripts can be run as explained in the sections below.
Running tests locally
Before tests can be run locally, Dash Core must be built. See the building instructions for help.
Functional tests
Dependencies and prerequisites
Many Dash specific tests require dash_hash. To install it:
- Clone the repo
git clone https://github.com/dashpay/dash_hash
- Install dash_hash
cd dash_hash && pip3 install -r requirements.txt .
The ZMQ functional test requires a python ZMQ library. To install it:
- on Unix, run
sudo apt-get install python3-zmq
- on mac OS, run
pip3 install pyzmq
On Windows the PYTHONUTF8
environment variable must be set to 1:
set PYTHONUTF8=1
Running the tests
Individual tests can be run by directly calling the test script, e.g.:
test/functional/wallet_hd.py
or can be run through the test_runner harness, eg:
test/functional/test_runner.py wallet_hd.py
You can run any combination (incl. duplicates) of tests by calling:
test/functional/test_runner.py <testname1> <testname2> <testname3> ...
Wildcard test names can be passed, if the paths are coherent and the test runner
is called from a bash
shell or similar that does the globbing. For example,
to run all the wallet tests:
test/functional/test_runner.py test/functional/wallet*
functional/test_runner.py functional/wallet* (called from the test/ directory)
test_runner.py wallet* (called from the test/functional/ directory)
but not
test/functional/test_runner.py wallet*
Combinations of wildcards can be passed:
test/functional/test_runner.py ./test/functional/tool* test/functional/mempool*
test_runner.py tool* mempool*
Run the regression test suite with:
test/functional/test_runner.py
Run all possible tests with
test/functional/test_runner.py --extended
In order to run backwards compatibility tests, download the previous node binaries:
test/get_previous_releases.py -b v19.3.0 v18.2.2 v0.17.0.3 v0.16.1.1 v0.15.0.0
By default, up to 4 tests will be run in parallel by test_runner. To specify
how many jobs to run, append --jobs=n
The individual tests and the test_runner harness have many command-line
options. Run test/functional/test_runner.py -h
to see them all.
Speed up test runs with a ramdisk
If you have available RAM on your system you can create a ramdisk to use as the cache
and tmp
directories for the functional tests in order to speed them up.
Speed-up amount varies on each system (and according to your ram speed and other variables), but a 2-3x speed-up is not uncommon.
To create a 4GB ramdisk on Linux at /mnt/tmp/
:
sudo mkdir -p /mnt/tmp
sudo mount -t tmpfs -o size=4g tmpfs /mnt/tmp/
Configure the size of the ramdisk using the size=
option.
The size of the ramdisk needed is relative to the number of concurrent jobs the test suite runs.
For example running the test suite with --jobs=100
might need a 16GB ramdisk, but running with --jobs=4
will only need a 4GB ramdisk.
To use, run the test suite specifying the ramdisk as the cachedir
and tmpdir
:
test/functional/test_runner.py --cachedir=/mnt/tmp/cache --tmpdir=/mnt/tmp
Once finished with the tests and the disk, and to free the ram, simply unmount the disk:
sudo umount /mnt/tmp
Troubleshooting and debugging test failures
Resource contention
The P2P and RPC ports used by the dashd nodes-under-test are chosen to make conflicts with other processes unlikely. However, if there is another dashd process running on the system (perhaps from a previous test which hasn't successfully killed all its dashd nodes), then there may be a port conflict which will cause the test to fail. It is recommended that you run the tests on a system where no other dashd processes are running.
On linux, the test framework will warn if there is another dashd process running when the tests are started.
If there are zombie dashd processes after test failure, you can kill them by running the following commands. Note that these commands will kill all dashd processes running on the system, so should not be used if any non-test dashd processes are being run.
killall dashd
or
pkill -9 dashd
Data directory cache
A pre-mined blockchain with 200 blocks is generated the first time a functional test is run and is stored in test/cache. This speeds up test startup times since new blockchains don't need to be generated for each test. However, the cache may get into a bad state, in which case tests will fail. If this happens, remove the cache directory (and make sure dashd processes are stopped as above):
rm -rf test/cache
killall dashd
Test logging
The tests contain logging at five different levels (DEBUG, INFO, WARNING, ERROR
and CRITICAL). From within your functional tests you can log to these different
levels using the logger included in the test_framework, e.g.
self.log.debug(object)
. By default:
- when run through the test_runner harness, all logs are written to
test_framework.log
and no logs are output to the console. - when run directly, all logs are written to
test_framework.log
and INFO level and above are output to the console. - when run by our CI (Continuous Integration), no logs are output to the console. However, if a test
fails, the
test_framework.log
and dashddebug.log
s will all be dumped to the console to help troubleshooting.
These log files can be located under the test data directory (which is always printed in the first line of test output):
<test data directory>/test_framework.log
<test data directory>/node<node number>/regtest/debug.log
.
The node number identifies the relevant test node, starting from node0
, which
corresponds to its position in the nodes list of the specific test,
e.g. self.nodes[0]
.
To change the level of logs output to the console, use the -l
command line
argument.
test_framework.log
and dashd debug.log
s can be combined into a single
aggregate log by running the combine_logs.py
script. The output can be plain
text, colorized text or html. For example:
test/functional/combine_logs.py -c <test data directory> | less -r
will pipe the colorized logs from the test into less.
Use --tracerpc
to trace out all the RPC calls and responses to the console. For
some tests (eg any that use submitblock
to submit a full block over RPC),
this can result in a lot of screen output.
By default, the test data directory will be deleted after a successful run.
Use --nocleanup
to leave the test data directory intact. The test data
directory is never deleted after a failed test.
Attaching a debugger
A python debugger can be attached to tests at any point. Just add the line:
import pdb; pdb.set_trace()
anywhere in the test. You will then be able to inspect variables, as well as call methods that interact with the dashd nodes-under-test.
If further introspection of the dashd instances themselves becomes
necessary, this can be accomplished by first setting a pdb breakpoint
at an appropriate location, running the test to that point, then using
gdb
(or lldb
on macOS) to attach to the process and debug.
For instance, to attach to self.node[1]
during a run you can get
the pid of the node within pdb
.
(pdb) self.node[1].process.pid
Alternatively, you can find the pid by inspecting the temp folder for the specific test you are running. The path to that folder is printed at the beginning of every test run:
2017-06-27 14:13:56.686000 TestFramework (INFO): Initializing test directory /tmp/user/1000/testo9vsdjo3
Use the path to find the pid file in the temp folder:
cat /tmp/user/1000/testo9vsdjo3/node1/regtest/dashd.pid
Then you can use the pid to start gdb
:
gdb /home/example/dashd <pid>
Note: gdb attach step may require ptrace_scope to be modified, or sudo
preceding the gdb
.
See this link for considerations: https://www.kernel.org/doc/Documentation/security/Yama.txt
Often while debugging rpc calls from functional tests, the test might reach timeout before
process can return a response. Use --timeout-factor 0
to disable all rpc timeouts for that partcular
functional test. Ex: test/functional/wallet_hd.py --timeout-factor 0
.
Profiling
An easy way to profile node performance during functional tests is provided
for Linux platforms using perf
.
Perf will sample the running node and will generate profile data in the node's
datadir. The profile data can then be presented using perf report
or a graphical
tool like hotspot.
To generate a profile during test suite runs, use the --perf
flag.
To see render the output to text, run
perf report -i /path/to/datadir/send-big-msgs.perf.data.xxxx --stdio | c++filt | less
For ways to generate more granular profiles, see the README in test/functional.
Util tests
Util tests can be run locally by running test/util/bitcoin-util-test.py
.
Use the -v
option for verbose output.
Lint tests
Dependencies
Lint test | Dependency | Version used by CI | Installation |
---|---|---|---|
lint-python.sh |
flake8 | 3.8.3 | pip3 install flake8==3.8.3 |
lint-python.sh |
mypy | 0.781 | pip3 install mypy==0.781 |
lint-shell.sh |
ShellCheck | 0.7.2 | details... |
lint-shell.sh |
yq | default | pip3 install yq |
lint-spelling.sh |
codespell | 2.0.0 | pip3 install codespell==2.0.0 |
Please be aware that on Linux distributions all dependencies are usually available as packages, but could be outdated.
Running the tests
Individual tests can be run by directly calling the test script, e.g.:
test/lint/lint-filenames.sh
You can run all the shell-based lint tests by running:
test/lint/lint-all.sh
Writing functional tests
You are encouraged to write functional tests for new or existing features. Further information about the functional test framework and individual tests is found in test/functional.