c4a29d0a90
Update wallet_multiwallet.py for descriptor and sqlite wallets (Russell Yanofsky)310b0fde04
Run dumpwallet for legacy wallets only in wallet_backup.py (Andrew Chow)6c6639ac9f
Include sqlite3 in documentation (Andrew Chow)f023b7cac0
wallet: Enforce sqlite serialized threading mode (Andrew Chow)6173269866
Set and check the sqlite user version (Andrew Chow)9d3d2d263c
Use network magic as sqlite wallet application ID (Andrew Chow)9af5de3798
Use SQLite for descriptor wallets (Andrew Chow)9b78f3ce8e
walletutil: Wallets can also be sqlite (Andrew Chow)ac38a87225
Determine wallet file type based on file magic (Andrew Chow)6045f77003
Implement SQLiteDatabase::MakeBatch (Andrew Chow)727e6b2a4e
Implement SQLiteDatabase::Verify (Andrew Chow)b4df8fdb19
Implement SQLiteDatabase::Rewrite (Andrew Chow)010e365906
Implement SQLiteDatabase::TxnBegin, TxnCommit, and TxnAbort (Andrew Chow)ac5c1617e7
Implement SQLiteDatabase::Backup (Andrew Chow)f6f9cd6a64
Implement SQLiteBatch::StartCursor, ReadAtCursor, and CloseCursor (Andrew Chow)bf90e033f4
Implement SQLiteBatch::ReadKey, WriteKey, EraseKey, and HasKey (Andrew Chow)7aa45620e2
Add SetupSQLStatements (Andrew Chow)6636a2608a
Implement SQLiteBatch::Close (Andrew Chow)93825352a3
Implement SQLiteDatabase::Close (Andrew Chow)a0de83372b
Implement SQLiteDatabase::Open (Andrew Chow)3bfa0fe125
Initialize and Shutdown sqlite3 globals (Andrew Chow)5a488b3d77
Constructors, destructors, and relevant private fields for SQLiteDatabase/Batch (Andrew Chow)ca8b7e04ab
Implement SQLiteDatabaseVersion (Andrew Chow)7577b6e1c8
Add SQLiteDatabase and SQLiteBatch dummy classes (Andrew Chow)e87df82580
Add sqlite to travis and depends (Andrew Chow)54729f3f4e
Add libsqlite3 (Andrew Chow) Pull request description: This PR adds a new class `SQLiteDatabase` which is a subclass of `WalletDatabase`. This provides access to a SQLite database that is used to store the wallet records. To keep compatibility with BDB and to complexity of the change down, we don't make use of many SQLite's features. We use it strictly as a key-value store. We create a table `main` which has two columns, `key` and `value` both with the type `blob`. For new descriptor wallets, we will create a `SQLiteDatabase` instead of a `BerkeleyDatabase`. There is no requirement that all SQLite wallets are descriptor wallets, nor is there a requirement that all descriptor wallets be SQLite wallets. This allows for existing descriptor wallets to work as well as keeping open the option to migrate existing wallets to SQLite. We keep the name `wallet.dat` for SQLite wallets. We are able to determine which database type to use by searching for specific magic bytes in the `wallet.dat` file. SQLite begins it's files with a null terminated string `SQLite format 3`. BDB has `0x00053162` at byte 12 (note that the byte order of this integer depends on the system endianness). So when we see that there is a `wallet.dat` file that we want to open, we check for the magic bytes to determine which database system to use. I decided to keep the `wallet.dat` naming to keep things like backup script to continue to function as they won't need to be modified to look for a different file name. It also simplifies a couple of things in the implementation and the tests as `wallet.dat` is something that is specifically being looked for. If we don't want this behavior, then I do have another branch which creates `wallet.sqlite` files instead, but I find that this direction is easier. ACKs for top commit: Sjors: re-utACKc4a29d0a90
promag: Tested ACKc4a29d0a90
. fjahr: reACKc4a29d0a90
S3RK: Re-review ACKc4a29d0a90
meshcollider: re-utACKc4a29d0a90
hebasto: re-ACKc4a29d0a90
, only rebased since my [previous](https://github.com/bitcoin/bitcoin/pull/19077#pullrequestreview-507743699) review, verified with `git range-diff master d18892dcc c4a29d0a9`. ryanofsky: Code review ACKc4a29d0a90
. I am honestly confused about reasons for locking into `wallet.dat` again when it's so easy now to use a clean format. I assume I'm just very dense, or there's some unstated reason, because the only thing that's been brought up are unrealistic compatibility scenarios (all require actively creating a wallet with non-default descriptor+sqlite option, then trying to using the descriptor+sqlite wallets with old software or scripts and ignoring the results) that we didn't pay attention to with previous PRs like #11687, which did not require any active interfaction. jonatack: ACKc4a29d0a90
, debug builds and test runs after rebase to latest master @c2c4dbaebd
, some manual testing creating, using, unloading and reloading a few different new sqlite descriptor wallets over several node restarts/shutdowns. Tree-SHA512: 19145732e5001484947352d3175a660b5102bc6e833f227a55bd41b9b2f4d92737bbed7cead64b75b509decf9e1408cd81c185ab1fb4b90561aee427c4f9751c
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
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 | 0.7.1 | details... |
lint-shell.sh |
yq | default | pip3 install yq |
lint-spelling.sh |
codespell | 1.17.1 | pip3 install codespell==1.17.1 |
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.