86beee05795216738f51fa744539336503c26fd9 Use waste metric for deciding which selection to use (Andrew Chow) b3df0caf7c291a316298e54e73426c765e61c129 tests: Test GetSelectionWaste (Andrew Chow) 4f5ad43b1e05cd7b403f87aae4c4d42e5aea810b Add waste metric calculation function (Andrew Chow) 935b3ddf72aa390087684e03166c707f5b173434 scripted-diff: tests: Use KnapsackSolver directly (Andrew Chow) 6a023a6f904efe38dacd662d919aba74f066b1dc tests: Add KnapsackGroupOutputs helper function (Andrew Chow) d5069fc1aa7d335f3043227f843cbb9d8ba1507b tests: Use SelectCoinsBnB directly instead of AttemptSelection (Andrew Chow) 54de7b47463d98f860167d4e0b7e4ebb3926b59c Allow the long term feerate to be configured, default of 10 sat/vb (Andrew Chow) Pull request description: Branch and Bound introduced a metric that we call waste. This metric is used as part of bounding the search tree, but it can be generalized to all coin selection solutions, including those with change. As such, this PR introduces the waste metric at a higher level so that we can run both of our coin selection algorithms (BnB and KnapsackSolver) and choose the one which has the least waste. In the event that both find a solution with the same change, we choose the one that spends more inputs. Also this PR sets the long term feerate to 10 sat/vb rather than using the 1008 block estimate. This allows the long term feerate to be the feerate that we switch between consolidating and optimizing for fees. This also removes a bug where the long term feerate would incorrectly be set to the fallback fee. While this doesn't matter prior to this PR, it does have an effect following this. The long term feerate can be configured by the user through a new `-consolidatefeerate` option. ACKs for top commit: Xekyo: reACK 86beee0 via git range-diff fe47558...86beee0 meshcollider: re-utACK 86beee05795216738f51fa744539336503c26fd9 Tree-SHA512: 54b154b346538eca68ae2a3b83a033b495c1605c14f842bfc43ded2256b110983ce674c647fe753cf0305b1b178403d8d60d6d4203c7a712bec784be52e90d42
This directory contains integration tests that test bitcoind 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 bitcoind and bitcoin-qt by interacting with them through the RPC and P2P interfaces.
- util which tests the bitcoin utilities, currently only bitcoin-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, Bitcoin Core must be built. See the building instructions for help.
Functional tests
Dependencies
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
Running the tests
Individual tests can be run by directly calling the test script, e.g.:
test/functional/feature_rbf.py
or can be run through the test_runner harness, eg:
test/functional/test_runner.py feature_rbf.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 v0.20.1 v0.19.1 v0.18.1 v0.17.2 v0.16.3 v0.15.2
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.
Troubleshooting and debugging test failures
Resource contention
The P2P and RPC ports used by the bitcoind nodes-under-test are chosen to make conflicts with other processes unlikely. However, if there is another bitcoind process running on the system (perhaps from a previous test which hasn't successfully killed all its bitcoind 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 bitcoind processes are running.
On linux, the test framework will warn if there is another bitcoind process running when the tests are started.
If there are zombie bitcoind processes after test failure, you can kill them by running the following commands. Note that these commands will kill all bitcoind processes running on the system, so should not be used if any non-test bitcoind processes are being run.
killall bitcoind
or
pkill -9 bitcoind
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 bitcoind processes are stopped as above):
rm -rf test/cache
killall bitcoind
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 bitcoinddebug.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 bitcoind 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 bitcoind nodes-under-test.
If further introspection of the bitcoind 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/bitcoind.pid
Then you can use the pid to start gdb
:
gdb /home/example/bitcoind <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-files.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.