# This file is part of h5py, a Python interface to the HDF5 library. # # http://www.h5py.org # # Copyright 2008-2013 Andrew Collette and contributors # # License: Standard 3-clause BSD; see "license.txt" for full license terms # and contributor agreement. import sys import os import shutil import inspect import tempfile import subprocess from contextlib import contextmanager from functools import wraps import numpy as np from numpy.lib.recfunctions import repack_fields import h5py import unittest as ut # Check if non-ascii filenames are supported # Evidently this is the most reliable way to check # See also h5py issue #263 and ipython #466 # To test for this, run the testsuite with LC_ALL=C try: testfile, fname = tempfile.mkstemp(chr(0x03b7)) except UnicodeError: UNICODE_FILENAMES = False else: UNICODE_FILENAMES = True os.close(testfile) os.unlink(fname) del fname del testfile class TestCase(ut.TestCase): """ Base class for unit tests. """ @classmethod def setUpClass(cls): cls.tempdir = tempfile.mkdtemp(prefix='h5py-test_') @classmethod def tearDownClass(cls): shutil.rmtree(cls.tempdir) def mktemp(self, suffix='.hdf5', prefix='', dir=None): if dir is None: dir = self.tempdir return tempfile.mktemp(suffix, prefix, dir=dir) def mktemp_mpi(self, comm=None, suffix='.hdf5', prefix='', dir=None): if comm is None: from mpi4py import MPI comm = MPI.COMM_WORLD fname = None if comm.Get_rank() == 0: fname = self.mktemp(suffix, prefix, dir) fname = comm.bcast(fname, 0) return fname def setUp(self): self.f = h5py.File(self.mktemp(), 'w') def tearDown(self): try: if self.f: self.f.close() except: pass def assertSameElements(self, a, b): for x in a: match = False for y in b: if x == y: match = True if not match: raise AssertionError("Item '%s' appears in a but not b" % x) for x in b: match = False for y in a: if x == y: match = True if not match: raise AssertionError("Item '%s' appears in b but not a" % x) def assertArrayEqual(self, dset, arr, message=None, precision=None, check_alignment=True): """ Make sure dset and arr have the same shape, dtype and contents, to within the given precision, optionally ignoring differences in dtype alignment. Note that dset may be a NumPy array or an HDF5 dataset. """ if precision is None: precision = 1e-5 if message is None: message = '' else: message = ' (%s)' % message if np.isscalar(dset) or np.isscalar(arr): assert np.isscalar(dset) and np.isscalar(arr), \ 'Scalar/array mismatch ("%r" vs "%r")%s' % (dset, arr, message) dset = np.asarray(dset) arr = np.asarray(arr) assert dset.shape == arr.shape, \ "Shape mismatch (%s vs %s)%s" % (dset.shape, arr.shape, message) if dset.dtype != arr.dtype: if check_alignment: normalized_dset_dtype = dset.dtype normalized_arr_dtype = arr.dtype else: normalized_dset_dtype = repack_fields(dset.dtype) normalized_arr_dtype = repack_fields(arr.dtype) assert normalized_dset_dtype == normalized_arr_dtype, \ "Dtype mismatch (%s vs %s)%s" % (normalized_dset_dtype, normalized_arr_dtype, message) if not check_alignment: if normalized_dset_dtype != dset.dtype: dset = repack_fields(np.asarray(dset)) if normalized_arr_dtype != arr.dtype: arr = repack_fields(np.asarray(arr)) if arr.dtype.names is not None: for n in arr.dtype.names: message = '[FIELD %s] %s' % (n, message) self.assertArrayEqual(dset[n], arr[n], message=message, precision=precision, check_alignment=check_alignment) elif arr.dtype.kind in ('i', 'f'): assert np.all(np.abs(dset[...] - arr[...]) < precision), \ "Arrays differ by more than %.3f%s" % (precision, message) elif arr.dtype.kind == 'O': for v1, v2 in zip(dset.flat, arr.flat): self.assertArrayEqual(v1, v2, message=message, precision=precision, check_alignment=check_alignment) else: assert np.all(dset[...] == arr[...]), \ "Arrays are not equal (dtype %s) %s" % (arr.dtype.str, message) def assertNumpyBehavior(self, dset, arr, s, skip_fast_reader=False): """ Apply slicing arguments "s" to both dset and arr. Succeeds if the results of the slicing are identical, or the exception raised is of the same type for both. "arr" must be a Numpy array; "dset" may be a NumPy array or dataset. """ exc = None try: arr_result = arr[s] except Exception as e: exc = type(e) s_fast = s if isinstance(s, tuple) else (s,) if exc is None: self.assertArrayEqual(dset[s], arr_result) if not skip_fast_reader: self.assertArrayEqual( dset._fast_reader.read(s_fast), arr_result, ) else: with self.assertRaises(exc): dset[s] if not skip_fast_reader: with self.assertRaises(exc): dset._fast_reader.read(s_fast) NUMPY_RELEASE_VERSION = tuple([int(i) for i in np.__version__.split(".")[0:2]]) @contextmanager def closed_tempfile(suffix='', text=None): """ Context manager which yields the path to a closed temporary file with the suffix `suffix`. The file will be deleted on exiting the context. An additional argument `text` can be provided to have the file contain `text`. """ with tempfile.NamedTemporaryFile( 'w+t', suffix=suffix, delete=False ) as test_file: file_name = test_file.name if text is not None: test_file.write(text) test_file.flush() yield file_name shutil.rmtree(file_name, ignore_errors=True) def insubprocess(f): """Runs a test in its own subprocess""" @wraps(f) def wrapper(request, *args, **kwargs): curr_test = inspect.getsourcefile(f) + "::" + request.node.name # get block around test name insub = "IN_SUBPROCESS_" + curr_test for c in "/\\,:.": insub = insub.replace(c, "_") defined = os.environ.get(insub, None) # fork process if defined: return f(request, *args, **kwargs) else: os.environ[insub] = '1' env = os.environ.copy() env[insub] = '1' env.update(getattr(f, 'subproc_env', {})) with closed_tempfile() as stdout: with open(stdout, 'w+t') as fh: rtn = subprocess.call([sys.executable, '-m', 'pytest', curr_test], stdout=fh, stderr=fh, env=env) with open(stdout, 'rt') as fh: out = fh.read() assert rtn == 0, "\n" + out return wrapper def subproc_env(d): """Set environment variables for the @insubprocess decorator""" def decorator(f): f.subproc_env = d return f return decorator