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import importlib
import platform
import re
import warnings
from contextlib import contextmanager
from distutils import version
from unittest import mock # noqa: F401
import numpy as np
import pytest
from numpy.testing import assert_array_equal # noqa: F401
from pandas.testing import assert_frame_equal # noqa: F401
import xarray.testing
from xarray.core import utils
from xarray.core.duck_array_ops import allclose_or_equiv # noqa: F401
from xarray.core.indexing import ExplicitlyIndexed
from xarray.core.options import set_options
from xarray.testing import ( # noqa: F401
assert_chunks_equal,
assert_duckarray_allclose,
assert_duckarray_equal,
)
# import mpl and change the backend before other mpl imports
try:
import matplotlib as mpl
# Order of imports is important here.
# Using a different backend makes Travis CI work
mpl.use("Agg")
except ImportError:
pass
arm_xfail = pytest.mark.xfail(
platform.machine() == "aarch64" or "arm" in platform.machine(),
reason="expected failure on ARM",
)
import platform
arm_xfail = pytest.mark.xfail(platform.machine() == 'aarch64' or
'arm' in platform.machine(), reason='expected failure on ARM')
def _importorskip(modname, minversion=None):
try:
mod = importlib.import_module(modname)
has = True
if minversion is not None:
if LooseVersion(mod.__version__) < LooseVersion(minversion):
raise ImportError("Minimum version not satisfied")
except ImportError:
has = False
func = pytest.mark.skipif(not has, reason=f"requires {modname}")
return has, func
def LooseVersion(vstring):
# Our development version is something like '0.10.9+aac7bfc'
# This function just ignored the git commit id.
vstring = vstring.split("+")[0]
return version.LooseVersion(vstring)
has_matplotlib, requires_matplotlib = _importorskip("matplotlib")
has_scipy, requires_scipy = _importorskip("scipy")
has_pydap, requires_pydap = _importorskip("pydap.client")
has_netCDF4, requires_netCDF4 = _importorskip("netCDF4")
has_h5netcdf, requires_h5netcdf = _importorskip("h5netcdf")
has_pynio, requires_pynio = _importorskip("Nio")
has_pseudonetcdf, requires_pseudonetcdf = _importorskip("PseudoNetCDF")
has_cftime, requires_cftime = _importorskip("cftime")
has_cftime_1_1_0, requires_cftime_1_1_0 = _importorskip("cftime", minversion="1.1.0.0")
has_dask, requires_dask = _importorskip("dask")
has_bottleneck, requires_bottleneck = _importorskip("bottleneck")
has_nc_time_axis, requires_nc_time_axis = _importorskip("nc_time_axis")
has_rasterio, requires_rasterio = _importorskip("rasterio")
has_zarr, requires_zarr = _importorskip("zarr")
has_iris, requires_iris = _importorskip("iris")
has_cfgrib, requires_cfgrib = _importorskip("cfgrib")
has_numbagg, requires_numbagg = _importorskip("numbagg")
has_seaborn, requires_seaborn = _importorskip("seaborn")
has_sparse, requires_sparse = _importorskip("sparse")
has_cartopy, requires_cartopy = _importorskip("cartopy")
# Need Pint 0.15 for __dask_tokenize__ tests for Quantity wrapped Dask Arrays
has_pint_0_15, requires_pint_0_15 = _importorskip("pint", minversion="0.15")
# some special cases
has_scipy_or_netCDF4 = has_scipy or has_netCDF4
requires_scipy_or_netCDF4 = pytest.mark.skipif(
not has_scipy_or_netCDF4, reason="requires scipy or netCDF4"
)
# change some global options for tests
set_options(warn_for_unclosed_files=True)
if has_dask:
import dask
dask.config.set(scheduler="single-threaded")
class CountingScheduler:
"""Simple dask scheduler counting the number of computes.
Reference: https://stackoverflow.com/questions/53289286/"""
def __init__(self, max_computes=0):
self.total_computes = 0
self.max_computes = max_computes
def __call__(self, dsk, keys, **kwargs):
self.total_computes += 1
if self.total_computes > self.max_computes:
raise RuntimeError(
"Too many computes. Total: %d > max: %d."
% (self.total_computes, self.max_computes)
)
return dask.get(dsk, keys, **kwargs)
@contextmanager
def dummy_context():
yield None
def raise_if_dask_computes(max_computes=0):
# return a dummy context manager so that this can be used for non-dask objects
if not has_dask:
return dummy_context()
scheduler = CountingScheduler(max_computes)
return dask.config.set(scheduler=scheduler)
flaky = pytest.mark.flaky
network = pytest.mark.network
@contextmanager
def raises_regex(error, pattern):
__tracebackhide__ = True
with pytest.raises(error) as excinfo:
yield
message = str(excinfo.value)
if not re.search(pattern, message):
raise AssertionError(
f"exception {excinfo.value!r} did not match pattern {pattern!r}"
)
class UnexpectedDataAccess(Exception):
pass
class InaccessibleArray(utils.NDArrayMixin, ExplicitlyIndexed):
def __init__(self, array):
self.array = array
def __getitem__(self, key):
raise UnexpectedDataAccess("Tried accessing data")
class ReturnItem:
def __getitem__(self, key):
return key
class IndexerMaker:
def __init__(self, indexer_cls):
self._indexer_cls = indexer_cls
def __getitem__(self, key):
if not isinstance(key, tuple):
key = (key,)
return self._indexer_cls(key)
def source_ndarray(array):
"""Given an ndarray, return the base object which holds its memory, or the
object itself.
"""
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "DatetimeIndex.base")
warnings.filterwarnings("ignore", "TimedeltaIndex.base")
base = getattr(array, "base", np.asarray(array).base)
if base is None:
base = array
return base
# Internal versions of xarray's test functions that validate additional
# invariants
def assert_equal(a, b):
__tracebackhide__ = True
xarray.testing.assert_equal(a, b)
xarray.testing._assert_internal_invariants(a)
xarray.testing._assert_internal_invariants(b)
def assert_identical(a, b):
__tracebackhide__ = True
xarray.testing.assert_identical(a, b)
xarray.testing._assert_internal_invariants(a)
xarray.testing._assert_internal_invariants(b)
def assert_allclose(a, b, **kwargs):
__tracebackhide__ = True
xarray.testing.assert_allclose(a, b, **kwargs)
xarray.testing._assert_internal_invariants(a)
xarray.testing._assert_internal_invariants(b)
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