def generate_go_ethereum_fixture(destination_dir):
with contextlib.ExitStack() as stack:
datadir = stack.enter_context(common.tempdir())
keystore_dir = os.path.join(datadir, 'keystore')
common.ensure_path_exists(keystore_dir)
keyfile_path = os.path.join(keystore_dir, common.KEYFILE_FILENAME)
with open(keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
genesis_file_path = os.path.join(datadir, 'genesis.json')
with open(genesis_file_path, 'w') as genesis_file:
genesis_file.write(json.dumps(common.GENESIS_DATA))
geth_ipc_path_dir = stack.enter_context(common.tempdir())
geth_ipc_path = os.path.join(geth_ipc_path_dir, 'geth.ipc')
geth_port = get_open_port()
geth_binary = common.get_geth_binary()
with get_geth_process(
geth_binary=geth_binary,
datadir=datadir,
genesis_file_path=genesis_file_path,
geth_ipc_path=geth_ipc_path,
geth_port=geth_port):
common.wait_for_socket(geth_ipc_path)
w3 = Web3(Web3.IPCProvider(geth_ipc_path))
chain_data = setup_chain_state(w3)
# close geth by exiting context
# must be closed before copying data dir
verify_chain_state(w3, chain_data)
# verify that chain state is still valid after closing
# and re-opening geth
with get_geth_process(
geth_binary=geth_binary,
datadir=datadir,
genesis_file_path=genesis_file_path,
geth_ipc_path=geth_ipc_path,
geth_port=geth_port):
common.wait_for_socket(geth_ipc_path)
w3 = Web3(Web3.IPCProvider(geth_ipc_path))
verify_chain_state(w3, chain_data)
static_data = {
'raw_txn_account': common.RAW_TXN_ACCOUNT,
'keyfile_pw': common.KEYFILE_PW,
}
config = merge(chain_data, static_data)
pprint.pprint(config)
write_config_json(config, datadir)
shutil.make_archive(destination_dir, 'zip', datadir)
def test_happy_run_elastic_fault_tolerant(self):
if skip_lightning_tests:
self.skipTest(
'Spark PyTorch Lightning tests conflict with Tensorflow 2.5.x: '
'https://github.com/horovod/horovod/pull/3263')
if not gloo_built():
self.skipTest("Gloo is not available")
with spark_session('test_happy_run_elastic_fault_tolerant',
max_failures=3):
with tempdir() as dir:
# these files make training function fail in given rank, epoch and batch
with open(os.path.sep.join([dir, 'rank_1_epoch_2_batch_4_fail']), 'w'), \
open(os.path.sep.join([dir, 'rank_0_epoch_3_batch_1_fail']), 'w'), \
open(os.path.sep.join([dir, 'rank_1_epoch_4_batch_2_fail']), 'w'):
pass
res = horovod.spark.run_elastic(
fn,
args=(2, 5, 5, dir),
env={'HOROVOD_LOG_LEVEL': 'DEBUG'},
num_proc=2,
min_num_proc=2,
max_num_proc=2,
start_timeout=5,
verbose=2)
self.assertListEqual([([0, 4, 0, 4, 1, 4, 0, 4], 0),
([0, 4, 0, 4, 1, 4, 0, 4], 1)], res)
def test_model_checkpoint_callback(self):
from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
with spark_session('test_fit_model') as spark:
df = create_noisy_xor_data(spark)
model = create_xor_model()
with tempdir() as dir:
checkpoint_callback = ModelCheckpoint(dirpath=dir)
callbacks = [checkpoint_callback]
with local_store() as store:
torch_estimator = hvd_spark.TorchEstimator(
num_proc=2,
store=store,
model=model,
input_shapes=[[-1, 2]],
feature_cols=['features'],
label_cols=['y'],
validation=0.2,
batch_size=4,
epochs=2,
verbose=2,
callbacks=callbacks)
torch_model = torch_estimator.fit(df)
# TODO: Find a way to pass log metrics from remote, and assert base on the logger.
trained_model = torch_model.getModel()
pred = trained_model(torch.ones([1, 2], dtype=torch.int32))
assert len(pred) == 1
assert pred.dtype == torch.float32
def test_model_override_trainer_args(self):
if skip_lightning_tests:
self.skipTest(
'Spark PyTorch Lightning tests conflict with Tensorflow 2.5.x: '
'https://github.com/horovod/horovod/pull/3263')
from pytorch_lightning.callbacks.model_checkpoint import ModelCheckpoint
with spark_session('test_fit_model') as spark:
df = create_noisy_xor_data(spark)
model = create_xor_model()
with tempdir() as dir:
with local_store() as store:
torch_estimator = hvd_spark.TorchEstimator(
num_proc=2,
store=store,
model=model,
input_shapes=[[-1, 2]],
feature_cols=['features'],
label_cols=['y'],
validation=0.2,
batch_size=4,
epochs=2,
verbose=2,
trainer_args={'stochastic_weight_avg': True})
torch_model = torch_estimator.fit(df)
# TODO: Find a way to pass log metrics from remote, and assert base on the logger.
trained_model = torch_model.getModel()
pred = trained_model(torch.ones([1, 2], dtype=torch.int32))
assert len(pred) == 1
assert pred.dtype == torch.float32
def test_spark_task_service_env(self):
key = secret.make_secret_key()
service_env = dict([(key, '{} value'.format(key))
for key in SparkTaskService.SERVICE_ENV_KEYS])
service_env.update({"other": "value"})
with os_environ(service_env):
service = SparkTaskService(1, key, None)
client = SparkTaskClient(1, service.addresses(), key, 3)
with tempdir() as d:
file = '{}/env'.format(d)
command = "env | grep -v '^PWD='> {}".format(file)
command_env = {"test": "value"}
try:
client.run_command(command, command_env)
client.wait_for_command_termination()
finally:
service.shutdown()
with open(file) as f:
env = sorted([line.strip() for line in f.readlines()])
expected = [
'HADOOP_TOKEN_FILE_LOCATION=HADOOP_TOKEN_FILE_LOCATION value',
'test=value'
]
self.assertEqual(env, expected)
def test_gen_pipeline_with_non_code_changes(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy(GEN_PIPELINE_FNAME, tmp_gen_pipeline_sh)
with open(os.path.join(dir, 'get_changed_code_files.py'),
'w') as py:
py.write("pass")
gen_pipeline_env = dict(BUILDKITE_PIPELINE_SLUG='SLUG',
BUILDKITE_BRANCH='BRANCH')
exit_code, actual_pipeline, gen_pipeline_log = self._run(
tmp_gen_pipeline_sh, gen_pipeline_env)
self.assertEqual(0, exit_code)
self.assertEqual('', gen_pipeline_log)
self.assertEqual(
"steps:\n"
"- label: \':book: Build Docs\'\n"
" command: 'cd /workdir/docs && pip install -r requirements.txt && make html'\n"
" plugins:\n"
" - docker#v3.1.0:\n"
" image: 'python:3.7'\n"
" timeout_in_minutes: 5\n"
" retry:\n"
" automatic: true\n"
" agents:\n"
" queue: cpu\n"
"- wait\n"
"- wait\n"
"- wait\n", actual_pipeline)
def test_happy_run_elastic_fault_tolerant_fails(self):
self.skipTest(
'elastic horovod does not support shutdown from the spark driver '
'while elastic driver is waiting for hosts to come up')
if not gloo_built():
self.skipTest("Gloo is not available")
with spark_session('test_happy_run_elastic_fault_tolerant_fails',
max_failures=2):
with tempdir() as dir:
# these files make training function fail in given rank, epoch and batch
# we have as many failures as Spark has max_failures (per task / index)
with open(os.path.sep.join([dir, 'rank_1_epoch_2_batch_4_fail']), 'w'), \
open(os.path.sep.join([dir, 'rank_1_epoch_3_batch_1_fail']), 'w'):
pass
res = horovod.spark.run_elastic(
fn,
args=(2, 5, 5, dir),
env={'HOROVOD_LOG_LEVEL': 'DEBUG'},
num_proc=2,
min_num_proc=2,
max_num_proc=2,
start_timeout=5,
verbose=2)
self.assertListEqual([([0, 4, 0, 4, 1, 4, 0, 4], 0),
([0, 4, 0, 4, 1, 4, 0, 4], 1)], res)
def single_tiff_setup(n_images, fmt='foo-{:05}.tif'):
with tempdir() as d:
data = np.ones((512, 512), dtype=np.float32)
for i in range(n_images):
tifffile.imsave(d.path(fmt.format(i)), data)
yield d
def single_tiff_setup(n_images, fmt='foo-{:05}.tif'):
with tempdir() as d:
data = np.ones((512, 512), dtype=np.float32)
for i in range(n_images):
tifffile.imsave(d.path(fmt.format(i)), data)
yield d
def test_gen_pipeline_with_empty_changes(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy('../.buildkite/gen-pipeline.sh', tmp_gen_pipeline_sh)
with open(os.path.join(dir, 'get_commit_files.py'), 'w') as py:
py.write("pass")
self.do_test_gen_full_pipeline(tmp_gen_pipeline_sh)
def test_gen_pipeline_on_default_branch(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy('../.buildkite/gen-pipeline.sh', tmp_gen_pipeline_sh)
with open(os.path.join(dir, 'get_commit_files.py'), 'w') as py:
py.write("print('.github/new_file')")
env = dict(BUILDKITE_BRANCH='default', BUILDKITE_PIPELINE_DEFAULT_BRANCH='default')
self.do_test_gen_full_pipeline(tmp_gen_pipeline_sh, env)
def test_get_spark_df_input_files(spark):
with tempdir() as d:
pq_dir = os.path.join(d, 'test_spark_df_output')
with spark_session('test_get_spark_df_input_files') as spark:
spark.range(100).repartition(4).write.parquet(pq_dir)
pq_files = _get_spark_df_saved_file_list(pq_dir)
pq_files = sorted(pq_files)
assert len(pq_files) == 4
for i in range(4):
assert pq_files[i].startswith('part-0000' + str(i))
def test_gen_pipeline_with_failing_py(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy(GEN_PIPELINE_FNAME, tmp_gen_pipeline_sh)
with open(os.path.join(dir, 'get_changed_code_files.py'),
'w') as py:
py.write('import sys\n')
py.write('sys.exit(1)')
self.do_test_gen_full_pipeline(tmp_gen_pipeline_sh)
def test_memory_in():
with tempdir() as d:
from ufo import MemoryIn, Write
ref = random.astype(np.float32)
read = MemoryIn(pointer=ref.__array_interface__['data'][0], number=1,
width=ref.shape[1], height=ref.shape[0])
write = Write(filename=d.path('foo.tif'))
write(read()).run().join()
result = tifffile.imread(d.path('foo.tif'))
assert(np.all(ref == result))
def test_gen_pipeline_on_default_branch(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy(GEN_PIPELINE_FNAME, tmp_gen_pipeline_sh)
with open(os.path.join(dir, 'get_changed_code_files.py'),
'w') as py:
py.write("pass")
env = dict(BUILDKITE_BRANCH='default',
BUILDKITE_PIPELINE_DEFAULT_BRANCH='default')
self.do_test_gen_full_pipeline(tmp_gen_pipeline_sh, env)
def test_task_count():
from ufo import DummyData, Write, Average
with tempdir() as d:
generate = DummyData(number=5, width=512, height=512)
write = Write(filename=d.path('foo-%i.tif'))
average = Average()
write(average(generate())).run().join()
assert (generate.task.props.num_processed == 0)
assert (average.task.props.num_processed == 5)
assert (write.task.props.num_processed == 1)
def test_memory_out():
with tempdir() as d:
from ufo import MemoryOut, Read
ref = random.astype(np.float32)
out = np.zeros_like(ref).astype(np.float32)
tifffile.imsave(d.path('foo.tif'), ref)
read = Read(path=d.path('foo.tif'))
write = MemoryOut(pointer=out.__array_interface__['data'][0], max_size=ref.nbytes)
write(read()).run().join()
assert(np.all(out == ref))
def test_read_multi_tiffs():
from ufo import Read, Null
with tempdir() as d:
n_images = 32
data = np.ones((512, 512, n_images))
tifffile.imsave(d.path('foo.tif'), data)
read = Read(path=d.path('foo.tif'))
null = Null()
null(read()).run().join()
assert (null.task.props.num_processed == n_images)
def test_task_count():
from ufo import DummyData, Write, Average
with tempdir() as d:
generate = DummyData(number=5, width=512, height=512)
write = Write(filename=d.path('foo-%i.tif'))
average = Average()
write(average(generate())).run().join()
assert(generate.task.props.num_processed == 0)
assert(average.task.props.num_processed == 5)
assert(write.task.props.num_processed == 1)
def test_read_multi_tiffs():
from ufo import Read, Null
with tempdir() as d:
n_images = 32
data = np.ones((512, 512, n_images))
tifffile.imsave(d.path('foo.tif'), data)
read = Read(path=d.path('foo.tif'))
null = Null()
null(read()).run().join()
assert(null.task.props.num_processed == n_images)
def generate_go_ethereum_fixture(destination_dir):
with contextlib.ExitStack() as stack:
datadir = stack.enter_context(common.tempdir())
keystore_dir = os.path.join(datadir, 'keystore')
common.ensure_path_exists(keystore_dir)
keyfile_path = os.path.join(keystore_dir, common.KEYFILE_FILENAME)
with open(keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
genesis_file_path = os.path.join(datadir, 'genesis.json')
with open(genesis_file_path, 'w') as genesis_file:
genesis_file.write(json.dumps(common.GENESIS_DATA))
geth_ipc_path_dir = stack.enter_context(common.tempdir())
geth_ipc_path = os.path.join(geth_ipc_path_dir, 'geth.ipc')
geth_port = get_open_port()
geth_binary = common.get_geth_binary()
geth_proc = stack.enter_context(common.get_geth_process( # noqa: F841
geth_binary=geth_binary,
datadir=datadir,
genesis_file_path=genesis_file_path,
ipc_path=geth_ipc_path,
port=geth_port,
networkid=str(common.GENESIS_DATA['config']['chainId'])
))
common.wait_for_socket(geth_ipc_path)
web3 = Web3(Web3.IPCProvider(geth_ipc_path))
chain_data = setup_chain_state(web3)
static_data = {
'raw_txn_account': common.RAW_TXN_ACCOUNT,
'keyfile_pw': common.KEYFILE_PW,
}
pprint.pprint(merge(chain_data, static_data))
shutil.copytree(datadir, destination_dir)
def generate_go_ethereum_fixture(destination_dir):
with contextlib.ExitStack() as stack:
datadir = stack.enter_context(common.tempdir())
keystore_dir = os.path.join(datadir, 'keystore')
common.ensure_path_exists(keystore_dir)
keyfile_path = os.path.join(keystore_dir, common.KEYFILE_FILENAME)
with open(keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
genesis_file_path = os.path.join(datadir, 'genesis.json')
with open(genesis_file_path, 'w') as genesis_file:
genesis_file.write(json.dumps(common.GENESIS_DATA))
geth_ipc_path_dir = stack.enter_context(common.tempdir())
geth_ipc_path = os.path.join(geth_ipc_path_dir, 'geth.ipc')
geth_port = common.get_open_port()
geth_binary = common.get_geth_binary()
geth_proc = stack.enter_context(
common.get_geth_process( # noqa: F841
geth_binary=geth_binary,
datadir=datadir,
genesis_file_path=genesis_file_path,
ipc_path=geth_ipc_path,
port=geth_port,
networkid=str(common.GENESIS_DATA['config']['chainId'])))
common.wait_for_socket(geth_ipc_path)
web3 = Web3(Web3.IPCProvider(geth_ipc_path))
chain_data = setup_chain_state(web3)
static_data = {
'raw_txn_account': common.RAW_TXN_ACCOUNT,
'keyfile_pw': common.KEYFILE_PW,
}
pprint.pprint(merge(chain_data, static_data))
shutil.copytree(datadir, destination_dir)
def test_gen_pipeline_with_code_changes(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy('../.buildkite/gen-pipeline.sh', tmp_gen_pipeline_sh)
for filename in [
'.buildkite/gen-pipeline.sh', 'cmake/file',
'examples/file', 'horovod/file', 'test/file',
'Dockerfile.cpu', ''
]:
with open(os.path.join(dir, 'get_commit_files.py'), 'w') as py:
py.write("print('{}')".format(filename))
self.do_test_gen_full_pipeline(tmp_gen_pipeline_sh)
def test_memory_in():
with tempdir() as d:
from ufo import MemoryIn, Write
ref = random.astype(np.float32)
read = MemoryIn(pointer=ref.__array_interface__['data'][0],
number=1,
width=ref.shape[1],
height=ref.shape[0])
write = Write(filename=d.path('foo.tif'))
write(read()).run().join()
result = tifffile.imread(d.path('foo.tif'))
assert (np.all(ref == result))
def test_memory_out():
with tempdir() as d:
from ufo import MemoryOut, Read
ref = random.astype(np.float32)
out = np.zeros_like(ref).astype(np.float32)
tifffile.imsave(d.path('foo.tif'), ref)
read = Read(path=d.path('foo.tif'))
write = MemoryOut(pointer=out.__array_interface__['data'][0],
max_size=ref.nbytes)
write(read()).run().join()
assert (np.all(out == ref))
def test_core_issue_61_16_bit_tiffs():
from ufo import Read, Write
orig = np.random.randint(0, 65535, (512, 512)).astype(np.uint16)
with tempdir() as d:
tifffile.imsave(d.path('temp.tif'), orig)
read = Read(path=d.path('temp.tif'))
write = Write(filename=d.path('temp-%i.tif'))
write(read()).run().join()
produced = tifffile.imread(d.path('temp-0.tif'))
assert(np.sum(orig - produced) == 0.0)
def test_core_issue_61_16_bit_tiffs():
from ufo import Read, Write
orig = np.random.randint(0, 65535, (512, 512)).astype(np.uint16)
with tempdir() as d:
tifffile.imsave(d.path('temp.tif'), orig)
read = Read(path=d.path('temp.tif'))
write = Write(filename=d.path('temp-%i.tif'))
write(read()).run().join()
produced = tifffile.imread(d.path('temp-0.tif'))
assert (np.sum(orig - produced) == 0.0)
def test_gen_pipeline_with_non_code_changes(self):
with tempdir() as dir:
tmp_gen_pipeline_sh = os.path.join(dir, 'gen-pipeline.sh')
copy(GEN_PIPELINE_FNAME, tmp_gen_pipeline_sh)
with open(os.path.join(dir, 'get_changed_code_files.py'),
'w') as py:
py.write("pass")
gen_pipeline_env = dict(BUILDKITE_PIPELINE_SLUG='SLUG',
BUILDKITE_BRANCH='BRANCH')
exit_code, actual_pipeline, gen_pipeline_log = self._run(
tmp_gen_pipeline_sh, gen_pipeline_env)
self.assertEqual(0, exit_code)
self.assertEqual('', gen_pipeline_log)
self.assertEqual("steps:\n"
"- wait\n"
"- wait\n"
"- wait\n", actual_pipeline)
def test_broadcast():
from ufo import Generate, Writer
import glob
with tempdir() as d:
generate = Generate(number=5, width=512, height=512)
write1 = Writer(filename=d.path('foo-%i.tif'))
write2 = Writer(filename=d.path('bar-%i.tif'))
g = Ufo.TaskGraph()
g.connect_nodes(generate.task, write1.task)
g.connect_nodes(generate.task, write2.task)
sched = Ufo.Scheduler()
sched.run(g)
foos = glob.glob(d.path('foo-*'))
bars = glob.glob(d.path('bar-*'))
assert(len(foos) == 5)
assert(len(bars) == 5)
def test_broadcast():
from ufo import Generate, Writer
import glob
with tempdir() as d:
generate = Generate(number=5, width=512, height=512)
write1 = Writer(filename=d.path('foo-%i.tif'))
write2 = Writer(filename=d.path('bar-%i.tif'))
g = Ufo.TaskGraph()
g.connect_nodes(generate.task, write1.task)
g.connect_nodes(generate.task, write2.task)
sched = Ufo.Scheduler()
sched.run(g)
foos = glob.glob(d.path('foo-*'))
bars = glob.glob(d.path('bar-*'))
assert (len(foos) == 5)
assert (len(bars) == 5)
def test_wait_file_available_on_dbfs():
with tempdir() as d:
pq_dir = os.path.join(d, 'test_ev')
os.makedirs(pq_dir)
file1_path = os.path.join(pq_dir, 'file1')
file2_path = os.path.join(pq_dir, 'file2')
url1 = 'file://' + file1_path.replace(os.sep, '/')
url2 = 'file://' + file2_path.replace(os.sep, '/')
url_list = [url1, url2]
def create_file(p):
with open(p, 'w'):
pass
# 1. test all files exists.
create_file(file1_path)
create_file(file2_path)
_wait_file_available_on_dbfs(url_list)
# 2. test one file does not exists. Raise error.
os.remove(file2_path)
with pytest.raises(
RuntimeError,
match=
'Timeout while waiting for all parquet-store files to appear'):
_wait_file_available_on_dbfs(url_list)
# 3. test one file accessible after 1 second.
def delay_create_file2():
time.sleep(1)
create_file(file2_path)
threading.Thread(target=delay_create_file2()).start()
_wait_file_available_on_dbfs(url_list)
def generate_parity_fixture(destination_dir):
"""
The parity fixture generation strategy is to start a ghuc client with
existing fixtures copied into a temp datadir. Then a parity client
is started is peered with the ghuc client.
"""
with contextlib.ExitStack() as stack:
ghuc_datadir = stack.enter_context(common.tempdir())
ghuc_port = common.get_open_port()
ghuc_ipc_path_dir = stack.enter_context(common.tempdir())
ghuc_ipc_path = os.path.join(ghuc_ipc_path_dir, 'ghuc.ipc')
ghuc_keystore_dir = os.path.join(ghuc_datadir, 'keystore')
common.ensure_path_exists(ghuc_keystore_dir)
ghuc_keyfile_path = os.path.join(ghuc_keystore_dir,
common.KEYFILE_FILENAME)
with open(ghuc_keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
genesis_file_path = os.path.join(ghuc_datadir, 'genesis.json')
with open(genesis_file_path, 'w') as genesis_file:
genesis_file.write(json.dumps(common.GENESIS_DATA))
stack.enter_context(
common.get_ghuc_process(common.get_ghuc_binary(), ghuc_datadir,
genesis_file_path, ghuc_ipc_path,
ghuc_port,
str(CHAIN_CONFIG['params']['networkID'])))
# set up fixtures
common.wait_for_socket(ghuc_ipc_path)
webu_ghuc = Webu(Webu.IPCProvider(ghuc_ipc_path))
chain_data = go_happyuc.setup_chain_state(webu_ghuc)
fixture_block_count = webu_ghuc.eth.blockNumber
datadir = stack.enter_context(common.tempdir())
keystore_dir = os.path.join(datadir, 'keys')
os.makedirs(keystore_dir, exist_ok=True)
parity_keyfile_path = os.path.join(keystore_dir,
common.KEYFILE_FILENAME)
with open(parity_keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
chain_config_file_path = os.path.join(datadir, 'chain_config.json')
with open(chain_config_file_path, 'w') as chain_file:
chain_file.write(json.dumps(CHAIN_CONFIG))
parity_ipc_path_dir = stack.enter_context(common.tempdir())
parity_ipc_path = os.path.join(parity_ipc_path_dir, 'jsonrpc.ipc')
parity_port = common.get_open_port()
parity_binary = get_parity_binary()
parity_proc = stack.enter_context(
get_parity_process( # noqa: F841
parity_binary=parity_binary,
datadir=datadir,
ipc_path=parity_ipc_path,
keys_path=keystore_dir,
chain_config_file_path=chain_config_file_path,
parity_port=parity_port,
))
common.wait_for_socket(parity_ipc_path)
webu = Webu(Webu.IPCProvider(parity_ipc_path))
time.sleep(10)
connect_nodes(webu, webu_ghuc)
wait_for_chain_sync(webu, fixture_block_count)
static_data = {
'raw_txn_account': common.RAW_TXN_ACCOUNT,
'keyfile_pw': common.KEYFILE_PW,
}
pprint.pprint(merge(chain_data, static_data))
shutil.copytree(datadir, destination_dir)
parity_proc = stack.enter_context(
parity_export_blocks_process( # noqa: F841
parity_binary=parity_binary,
datadir=destination_dir,
chain_config_file_path=os.path.join(destination_dir,
'chain_config.json'),
parity_port=parity_port,
))
def local_store():
with tempdir() as tmp:
store = LocalStore(tmp)
yield store
def generate_parity_fixture(destination_dir):
"""
The parity fixture generation strategy is to start a geth client with
existing fixtures copied into a temp datadir. Then a parity client
is started is peered with the geth client.
"""
with contextlib.ExitStack() as stack:
geth_datadir = stack.enter_context(common.tempdir())
geth_port = get_open_port()
geth_ipc_path_dir = stack.enter_context(common.tempdir())
geth_ipc_path = os.path.join(geth_ipc_path_dir, 'geth.ipc')
geth_keystore_dir = os.path.join(geth_datadir, 'keystore')
common.ensure_path_exists(geth_keystore_dir)
geth_keyfile_path = os.path.join(geth_keystore_dir, common.KEYFILE_FILENAME)
with open(geth_keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
genesis_file_path = os.path.join(geth_datadir, 'genesis.json')
with open(genesis_file_path, 'w') as genesis_file:
genesis_file.write(json.dumps(common.GENESIS_DATA))
stack.enter_context(
common.get_geth_process(
common.get_geth_binary(),
geth_datadir,
genesis_file_path,
geth_ipc_path,
geth_port,
str(CHAIN_CONFIG['params']['networkID']))
)
# set up fixtures
common.wait_for_socket(geth_ipc_path)
web3_geth = Web3(Web3.IPCProvider(geth_ipc_path))
chain_data = go_ethereum.setup_chain_state(web3_geth)
fixture_block_count = web3_geth.eth.blockNumber
datadir = stack.enter_context(common.tempdir())
keystore_dir = os.path.join(datadir, 'keys')
os.makedirs(keystore_dir, exist_ok=True)
parity_keyfile_path = os.path.join(keystore_dir, common.KEYFILE_FILENAME)
with open(parity_keyfile_path, 'w') as keyfile:
keyfile.write(common.KEYFILE_DATA)
chain_config_file_path = os.path.join(datadir, 'chain_config.json')
with open(chain_config_file_path, 'w') as chain_file:
chain_file.write(json.dumps(CHAIN_CONFIG))
parity_ipc_path_dir = stack.enter_context(common.tempdir())
parity_ipc_path = os.path.join(parity_ipc_path_dir, 'jsonrpc.ipc')
parity_port = get_open_port()
parity_binary = get_parity_binary()
parity_proc = stack.enter_context(get_parity_process( # noqa: F841
parity_binary=parity_binary,
datadir=datadir,
ipc_path=parity_ipc_path,
keys_path=keystore_dir,
chain_config_file_path=chain_config_file_path,
parity_port=parity_port,
))
common.wait_for_socket(parity_ipc_path)
web3 = Web3(Web3.IPCProvider(parity_ipc_path))
time.sleep(10)
connect_nodes(web3, web3_geth)
wait_for_chain_sync(web3, fixture_block_count)
static_data = {
'raw_txn_account': common.RAW_TXN_ACCOUNT,
'keyfile_pw': common.KEYFILE_PW,
}
pprint.pprint(merge(chain_data, static_data))
shutil.copytree(datadir, destination_dir)
parity_proc = stack.enter_context(parity_export_blocks_process( # noqa: F841
parity_binary=parity_binary,
datadir=destination_dir,
chain_config_file_path=os.path.join(destination_dir, 'chain_config.json'),
parity_port=parity_port,
))