d1684beabe5b738c2cc83de83e1aaef11a761b69 fees: Pass in a filepath instead of referencing gArgs (Carl Dong) 9a3d825c30e8e6118d74a4e568744cb9d03f7f5d init: Remove redundant -*mempool*, -limit* queries (Carl Dong) 6c5c60c4124293d948735756f84efc85262ea66f mempool: Use m_limit for UpdateTransactionsFromBlock (Carl Dong) 9e93b1030182eff92ef91181e17c7dd498c7e164 node/ifaces: Use existing MemPoolLimits (Carl Dong) 38af2bcf358a72b9457d370282e57f4be1c5c849 mempoolaccept: Use limits from mempool in constructor (Carl Dong) 9333427014695ac235c96d48791098168dfdc9db mempool: Introduce (still-unused) MemPoolLimits (Carl Dong) 716bb5fbd31077bbe99d11a54d6c2c250afc8085 scripted-diff: Rename anc/desc size limit vars to indicate SI unit (Carl Dong) 1ecc77321deb61b9f6888e4e10752b9d972fd26e scripted-diff: Rename DEFAULT_MEMPOOL_EXPIRY to indicate time unit (Carl Dong) aa9141cd8185cb7ad532bc16feb9d302b05d9697 mempool: Pass in -mempoolexpiry instead of referencing gArgs (Carl Dong) 51c7a41a5eb6fcb60333812c770d80227cf7b64d init: Only determine maxmempool once (Carl Dong) 386c9472c8764738282e6d163b42e15a8feda7ea mempool: Make GetMinFee() with custom size protected (Carl Dong) 82f00de7a6a60cbc9ad0c6e1d0ffb1bc70c49af5 mempool: Pass in -maxmempool instead of referencing gArgs (Carl Dong) f1941e8bfd2eecc478c7660434b1ebf6a64095a0 pool: Add and use MemPoolOptions, ApplyArgsManOptions (Carl Dong) 0199bd35bb44e32ee0db9b51c9d1bd7518c26f19 fuzz/rbf: Add missing TestingSetup (Carl Dong) ccbaf546a68d6cda8ed3efd0598c0e4121b366bb scripted-diff: Rename DEFAULT_MAX_MEMPOOL_SIZE to indicate SI unit (Carl Dong) fc02f77ca604f0221171bfde3059b34f5d0fb1cd ArgsMan: Add Get*Arg functions returning optional (Carl Dong) Pull request description: This is part of the `libbitcoinkernel` project: #24303, https://github.com/bitcoin/bitcoin/projects/18 ----- As mentioned in the Stage 1 Step 2 description of [the `libbitcoinkernel` project](https://github.com/bitcoin/bitcoin/issues/24303), `ArgsManager` will not be part of `libbitcoinkernel`. Therefore, it is important that we remove any dependence on `ArgsManager` by code that will be part of `libbitcoinkernel`. This is the first in a series of PRs aiming to achieve this. This PR removes `CTxMemPool+MempoolAccept`'s dependency on `ArgsManager` by introducing a `CTxMemPool::Options` struct, which is used to specify `CTxMemPool`'s various options at construction time. These options are: - `-maxmempool` -> `CTxMemPool::Options::max_size` - `-mempoolexpiry` -> `CTxMemPool::Options::expiry` - `-limitancestorcount` -> `CTxMemPool::Options::limits::ancestor_count` - `-limitancestorsize` -> `CTxMemPool::Options::limits::ancestor_size` - `-limitdescendantcount` -> `CTxMemPool::Options::limits::descendant_count` - `-limitdescendantsize` -> `CTxMemPool::Options::limits::descendant_size` More context can be gleaned from the commit messages. The important commits are: - 56eb479ded8bfb2ef635bb6f3b484f9d5952c70d "pool: Add and use MemPoolOptions, ApplyArgsManOptions" - a1e08b70f3068f4e8def1c630d8f50cd54da7832 "mempool: Pass in -maxmempool instead of referencing gArgs" - 6f4bf3ede5812b374828f08fc728ceded2f10024 "mempool: Pass in -mempoolexpiry instead of referencing gArgs" - 5958a7fe4806599fc620ee8c1a881ca10fa2dd16 "mempool: Introduce (still-unused) MemPoolLimits" Reviewers: Help needed in the following commits (see commit messages): - a1e08b70f3068f4e8def1c630d8f50cd54da7832 "mempool: Pass in -maxmempool instead of referencing gArgs" - 0695081a797e9a5d7787b78b0f8289dafcc6bff7 "node/ifaces: Use existing MemPoolLimits" Note to Reviewers: There are perhaps an infinite number of ways to architect `CTxMemPool::Options`, the current one tries to keep it simple, usable, and flexible. I hope we don't spend too much time arguing over the design here since that's not the point. In the case that you're 100% certain that a different design is strictly better than this one in every regard, please show us a fully-implemented branch. ----- TODO: - [x] Use the more ergonomic `CTxMemPool::Options` where appropriate - [x] Doxygen comments for `ApplyArgsManOptions`, `MemPoolOptions` ----- Questions for Reviewers: 1. Should we use `std::chrono::seconds` for `CTxMemPool::Options::expiry` and `CTxMemPool::m_expiry` instead of an `int64_t`? Something else? (`std::chrono::hours`?) 2. Should I merge `CTxMemPool::Limits` inside `CTxMemPool::Options`? ACKs for top commit: MarcoFalke: ACK d1684beabe5b738c2cc83de83e1aaef11a761b69 🍜 ryanofsky: Code review ACK d1684beabe5b738c2cc83de83e1aaef11a761b69. Just minor cleanups since last review, mostly switching to brace initialization Tree-SHA512: 2c138e52d69f61c263f1c3648f01c801338a8f576762c815f478ef5148b8b2f51e91ded5c1be915e678c0b14f6cfba894b82afec58d999d39a7bb7c914736e0b
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:
- fuzz A runner to execute all fuzz targets from /src/test/fuzz.
- functional which test the functionality of bitcoind and bitcoin-qt by interacting with them through the RPC and P2P interfaces.
- util which tests the utilities (bitcoin-util, bitcoin-tx, ...).
- lint which perform various static analysis checks.
The util tests are run as part of make check
target. The fuzz tests, 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.
Fuzz tests
See /doc/fuzzing.md
Functional tests
Dependencies and prerequisites
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/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 v23.0 v22.0 v0.21.0 v0.20.1 v0.19.1 v0.18.1 v0.17.2 v0.16.3 v0.15.2 v0.14.3
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 4GB ramdisk, but running with --jobs=32
will only need a 2.5GB 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 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/test_runner.py
.
Use the -v
option for verbose output.
Lint tests
Dependencies
Lint test | Dependency |
---|---|
lint-python.py |
flake8 |
lint-python.py |
mypy |
lint-python.py |
pyzmq |
lint-python-dead-code.py |
vulture |
lint-shell.py |
ShellCheck |
lint-spelling.py |
codespell |
In use versions and install instructions are available in the CI setup.
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.py
You can run all the shell-based lint tests by running:
test/lint/all-lint.py
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.