def _update_engine(cls, _):
if os.environ.get("MODIN_EXPERIMENTAL", "").title() == "True":
factory_fmt, experimental = "Experimental{}On{}Factory", True
else:
factory_fmt, experimental = "{}On{}Factory", False
factory_name = factory_fmt.format(partition_format.get(),
execution_engine.get())
try:
cls.__engine = getattr(factories, factory_name)
except AttributeError:
if not experimental:
# allow missing factories in experimenal mode only
if hasattr(factories, "Experimental" + factory_name):
msg = (
"{0} on {1} is only accessible through the experimental API.\nRun "
"`import modin.experimental.pandas as pd` to use {0} on {1}."
)
else:
msg = (
"Cannot find a factory for partition '{}' and execution engine '{}'. "
"Potential reason might be incorrect environment variable value for "
"MODIN_BACKEND or MODIN_ENGINE")
raise FactoryNotFoundError(
msg.format(partition_format.get(), execution_engine.get()))
cls.__engine = StubFactory.set_failing_name(factory_name)
else:
cls.__engine.prepare()
def _read_sql(cls, **kwargs):
if execution_engine.get() != "Ray":
if "partition_column" in kwargs:
if kwargs["partition_column"] is not None:
warnings.warn(
"Distributed read_sql() was only implemented for Ray engine."
)
del kwargs["partition_column"]
if "lower_bound" in kwargs:
if kwargs["lower_bound"] is not None:
warnings.warn(
"Distributed read_sql() was only implemented for Ray engine."
)
del kwargs["lower_bound"]
if "upper_bound" in kwargs:
if kwargs["upper_bound"] is not None:
warnings.warn(
"Distributed read_sql() was only implemented for Ray engine."
)
del kwargs["upper_bound"]
if "max_sessions" in kwargs:
if kwargs["max_sessions"] is not None:
warnings.warn(
"Distributed read_sql() was only implemented for Ray engine."
)
del kwargs["max_sessions"]
return cls.io_cls.read_sql(**kwargs)
def __update_engine(self, _):
if execution_engine.get() in REMOTE_ENGINES:
from modin.experimental.cloud import get_connection
self.__swap_numpy(get_connection().modules["numpy"])
else:
self.__swap_numpy()
def update_class(_):
if execution_engine.get() in REMOTE_ENGINES:
from . import rpyc_proxy
result.__real_cls__ = getattr(rpyc_proxy,
rpyc_wrapper_name)(result)
else:
result.__real_cls__ = result
def update_class(_):
if execution_engine.get() == "Cloudray":
from . import rpyc_proxy
result.__real_cls__ = getattr(rpyc_proxy,
rpyc_wrapper_name)(result)
else:
result.__real_cls__ = result
pandas_df = pandas.read_table(Path(TEST_CSV_FILENAME))
modin_df = pd.read_table(Path(TEST_CSV_FILENAME))
df_equals(modin_df, pandas_df)
@pytest.mark.parametrize("usecols", [["a"], ["a", "b", "e"], [0, 1, 4]])
def test_from_csv_with_usecols(usecols):
fname = "modin/pandas/test/data/test_usecols.csv"
pandas_df = pandas.read_csv(fname, usecols=usecols)
modin_df = pd.read_csv(fname, usecols=usecols)
df_equals(modin_df, pandas_df)
@pytest.mark.skipif(execution_engine.get().lower() == "python",
reason="Using pandas implementation")
def test_from_csv_s3(make_csv_file):
dataset_url = "s3://noaa-ghcn-pds/csv/1788.csv"
pandas_df = pandas.read_csv(dataset_url)
# This first load is to trigger all the import deprecation warnings
modin_df = pd.read_csv(dataset_url)
# This will warn if it defaults to pandas behavior, but it shouldn't
with pytest.warns(None) as record:
modin_df = pd.read_csv(dataset_url)
assert not any("defaulting to pandas implementation" in str(err)
for err in record.list)
pandas_df = pandas.read_table(Path(TEST_CSV_FILENAME))
modin_df = pd.read_table(Path(TEST_CSV_FILENAME))
df_equals(modin_df, pandas_df)
@pytest.mark.parametrize("usecols", [["a"], ["a", "b", "e"], [0, 1, 4]])
def test_from_csv_with_usecols(usecols):
fname = "modin/pandas/test/data/test_usecols.csv"
pandas_df = pandas.read_csv(fname, usecols=usecols)
modin_df = pd.read_csv(fname, usecols=usecols)
df_equals(modin_df, pandas_df)
@pytest.mark.skipif(
execution_engine.get().lower() == "python", reason="Using pandas implementation"
)
def test_from_csv_s3(make_csv_file):
dataset_url = "s3://noaa-ghcn-pds/csv/1788.csv"
pandas_df = pandas.read_csv(dataset_url)
# This first load is to trigger all the import deprecation warnings
modin_df = pd.read_csv(dataset_url)
# This will warn if it defaults to pandas behavior, but it shouldn't
with pytest.warns(None) as record:
modin_df = pd.read_csv(dataset_url)
assert not any(
"defaulting to pandas implementation" in str(err) for err in record.list
)
