def test_split(self):
h5_list = to.split_hdf5(self.fpath, self.dir_tmp, tot_floats=((3*4*2*3)))
#hdf5_list = to.split_hdf5(self.fpath, self.dir_tmp, tot_floats=((10*4*2*3)))
#hdf5_list = to.split_hdf5(self.fpath, self.dir_tmp, tot_floats=((1*4*2*3)))
assert_is_instance(h5_list, list)
assert_equals(len(h5_list), 2)
name_, ext = os.path.splitext(os.path.basename(self.fpath))
for p in h5_list:
assert_in(name_, p)
assert_true(p.endswith(ext), "Unexpected extension")
offset = 0
with h5py.File(self.fpath, 'r') as h_src:
for p in h5_list:
with h5py.File(p, 'r') as h:
assert_list_equal(['x1', 'x2'], h.keys())
for k in h.keys():
min_len = min(len(h[k]), len(h_src[k]))
sub_actual = h[k][0:min_len]
sub_expected = h_src[k][offset:offset+min_len]
assert_true(np.all(sub_actual==sub_expected))
offset += min_len
def test_to_block_continuous_long(self):
s = SwirlFrame()
for i, row in enumerate(s.rows):
row.set(i, i+1, 0xff, 0)
assert_list_equal([1,
0xff, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11, 12, 12, 13,
13, 14, 14, 15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 20, 20, 21, 21, 22, 22, 23, 23, 24, 24,
25, 25, 26, 26, 27, 27, 28, 28, 29, 29, 30, 30, 31, 31, 32, 32, 33, 33, 34, 34, 35, 35, 36,
36, 37, 37, 38, 38, 39, 39, 40, 40, 41, 41, 42, 42, 43, 43, 44, 44, 45, 45, 46, 46, 47, 47,
48, 48, 49, 49, 50, 50, 51, 51, 52, 52, 53, 53, 54, 54, 55, 55, 56, 56, 57, 57, 58, 58, 59,
59, 60, 60, 61, 61, 62, 62, 63, 63, 64, 64, 65, 65, 66, 66, 67, 67, 68, 68, 69, 69, 70, 70,
71, 71, 72, 72, 73, 73, 74, 74, 75, 75, 76, 76, 77, 77, 78, 78, 79, 79, 80, 80, 81, 81, 82,
82, 83, 83, 84, 84, 85, 85, 86, 86, 87, 87, 88, 88, 89, 89, 90, 90, 91, 91, 92, 92, 93, 93,
94, 94, 95, 95, 96, 96, 97, 97, 98, 98, 99, 99, 100, 100, 101, 101, 102, 102, 103, 103, 104,
104, 105, 105, 106, 106, 107, 107, 108, 108, 109, 109, 110, 110, 111, 111, 112, 112, 113,
113, 114, 114, 115, 115, 116, 116, 117, 117, 118, 118, 119, 119, 120, 120, 121, 121, 122,
122, 123, 123, 124, 124, 125, 125, 126, 126, 127,
0xe1, 127, 128, 128, 129, 129, 130, 130, 131, 131, 132, 132, 133, 133, 134, 134, 135, 135,
136, 136, 137,
137, 138, 138, 139, 139, 140, 140, 141, 141, 142, 142, 143, 143, 144, 144, 145, 145, 146,
146, 147, 147, 148, 148, 149, 149, 150, 150, 151, 151, 152, 152, 153, 153, 154, 154, 155,
155, 156, 156, 157, 157, 158, 158, 159, 159, 160, 160, 161, 161, 162, 162, 163, 163, 164,
164, 165, 165, 166, 166, 167, 167, 168, 168, 169, 169, 170, 170, 171, 171, 172, 172, 173,
173, 174, 174, 175, 175, 176, 176, 177, 177, 178, 178, 179, 179, 180, 180, 181, 181, 182,
182, 183, 183, 184, 184, 185, 185, 186, 186, 187, 187, 188, 188, 189, 189, 190, 190, 191,
191, 192, 192, 193, 193, 194, 194, 195, 195, 196, 196, 197, 197, 198, 198, 199, 199, 200,
200, 201, 201, 202, 202, 203, 203, 204, 204, 205, 205, 206, 206, 207, 207, 208, 208, 209,
209, 210, 210, 211, 211, 212, 212, 213, 213, 214, 214, 215, 215, 216, 216, 217, 217, 218,
218, 219, 219, 220, 220, 221, 221, 222, 222, 223, 223, 224,
0],
s.block_rep().to_list())
def test_pandas_series_loading(self):
"""Pandas Series objects are correctly loaded"""
# Test valid series types
name = ['_x', ' name']
length = [0, 1, 2]
index_key = [None, 'ix', 1]
index_types = ['int', 'char', 'datetime', 'Timestamp']
value_key = [None, 'x', 1]
value_types = ['int', 'char', 'datetime', 'Timestamp', 'float',
'numpy float', 'numpy int']
series_info = product(name, length, index_key, index_types,
value_key, value_types)
for n, l, ikey, itype, vkey, vtype in series_info:
index = sequences[itype](l)
series = pd.Series(sequences[vtype](l), index=index, name=n,)
vkey = vkey or series.name
expected = [{'idx': Data.serialize(i), 'col': vkey,
'val': Data.serialize(v)}
for i, v in zip(index, series)]
data = Data.from_pandas(series, name=n, series_key=vkey)
nt.assert_list_equal(expected, data.values)
nt.assert_equal(n, data.name)
data.to_json()
# Missing a name
series = pd.Series(np.random.randn(10))
data = Data.from_pandas(series)
nt.assert_equal(data.name, 'table')
def test_profile_table_for_join_with_profile_attrs(self):
profile_output = profile_table_for_join(self.table, ['attr'])
expected_output_attrs = ['Unique values', 'Missing values', 'Comments']
# verify whether the output dataframe has the necessary attributes.
assert_list_equal(list(profile_output.columns.values),
expected_output_attrs)
expected_unique_column = ['4 (80.0%)']
# verify whether correct values are present in 'Unique values' column.
assert_list_equal(list(profile_output['Unique values']),
expected_unique_column)
expected_missing_column = ['1 (20.0%)']
# verify whether correct values are present in 'Missing values' column.
assert_list_equal(list(profile_output['Missing values']),
expected_missing_column)
expected_comments = ['Joining on this attribute will ignore 1 (20.0%) rows.']
# verify whether correct values are present in 'Comments' column.
assert_list_equal(list(profile_output['Comments']),
expected_comments)
# verify whether index name is set correctly in the output dataframe.
assert_equal(profile_output.index.name, 'Attribute')
expected_index_column = ['attr']
# verify whether correct values are present in the dataframe index.
assert_list_equal(list(profile_output.index.values),
expected_index_column)
def test_should_create_varnish_api_for_connected_servers(self):
expected_construct_args = [
call(['127.0.0.1', '6082', 1.0], 'secret-1'),
call(['127.0.0.2', '6083', 1.0], 'secret-2'),
call(['127.0.0.3', '6084', 1.0], 'secret-3')]
sample_extractor = Mock(servers=servers)
api_init_side_effect = {
'secret-1': Exception(),
'secret-2': None,
'secret-3': None
}
with patch('vaas.cluster.cluster.ServerExtractor', Mock(return_value=sample_extractor)):
with patch.object(
VarnishApi, '__init__', side_effect=lambda host_port_timeout, secret: api_init_side_effect[secret]
) as construct_mock:
with patch('telnetlib.Telnet.close', Mock()):
varnish_cluster = VarnishApiProvider()
api_objects = []
for api in varnish_cluster.get_connected_varnish_api():
"""
Workaround - we cannot mock __del__ method:
https://docs.python.org/3/library/unittest.mock.html
We inject sock field to eliminate warning raised by cleaning actions in __del__ method
"""
api.sock = None
api_objects.append(api)
assert_equals(2, len(api_objects))
assert_list_equal(expected_construct_args, construct_mock.call_args_list)
def test_set_config(app1, cli, td):
dct = {
'1': '1',
2: 2,
1.1: 1.1,
'a': 1,
3: ['1', 2],
4: {'a': 1, '1': '1', 2: 2}}
# verify set_config does not delete old keys
nt.assert_in('key1', td[app1])
nt.assert_equal(1, td[app1]['key1'])
td = RedisMapping() # reset's RedisMapping's cache, from prev line
set_config(app1, dct, cli=cli)
nt.assert_in('key1', td[app1])
nt.assert_equal(1, td[app1]['key1'])
# verify set_config adds new keys
nt.assert_equal(
len(list(td[app1].keys())), len(list(dct.keys()) + ['key1']))
nt.assert_true(all(
x in (list(dct.keys()) + ['key1']) for x in td[app1].keys()))
nt.assert_equal('1', td[app1]['1'])
nt.assert_equal(2, td[app1][2])
nt.assert_equal(1.1, td[app1][1.1])
nt.assert_equal(1, td[app1]['a'])
nt.assert_is_instance(
td[app1][3], JSONSequence)
nt.assert_is_instance(
td[app1][4], JSONMapping)
nt.assert_list_equal(list(td[app1][3]), dct[3])
nt.assert_dict_equal(dict(td[app1][4]), dct[4])
def test_join_sets():
print "Blah"
result = join_sets([set([1, 2, 3]), set([3, 4, 5]), set([2, 6])], 2, 4)
assert_list_equal(result, [set([1, 2, 3, 6]), set([3, 4, 5])])
result = join_sets([set([1, 2])], 3, 4)
assert_list_equal(result, [set([1, 2])])
def test_read_4bpp_graphic_from_block():
source = Block()
source.from_list([0b01010110,
0b00001011,
0b11001110,
0b10010110,
0b01110001,
0b00111011,
0b00001011,
0b10011110,
0b00011000,
0b00000011,
0b10000001,
0b11101011,
0b00000100,
0b01000101,
0b01010110,
0b10001111,
0b00101100,
0b10110000,
0b01010110,
0b10110010,
0b01010000,
0b11000000,
0b00111000,
0b10010111,
0b00101101,
0b11111100,
0b01111101,
0b11101010,
0b10101111,
0b10110111,
0b01100000,
0b11101110])
target = [[0 for x in range(8)] for y in range(8)]
assert_equal(32, read_4bpp_graphic_from_block(target=target, source=source, offset=0, x=0, y=0, bit_offset=0))
assert_list_equal(target,
[[8, 1, 12, 9, 6, 5, 3, 2],
[11, 5, 8, 14, 1, 7, 15, 0],
[8, 13, 3, 7, 2, 0, 2, 3],
[10, 0, 4, 14, 7, 10, 11, 9],
[8, 8, 12, 9, 13, 12, 2, 6],
[11, 14, 14, 4, 14, 4, 10, 7],
[12, 2, 12, 8, 4, 15, 12, 14],
[10, 13, 12, 1, 10, 11, 11, 2]])
def test_from_iter(self):
"""Test data from single iter"""
test = Data.from_iter([10, 20, 30])
test1 = Data.from_iter((10, 20, 30))
values = [{'x': 0, 'y': 10}, {'x': 1, 'y': 20}, {'x': 2, 'y': 30}]
nt.assert_list_equal(test.values, values)
nt.assert_list_equal(test1.values, values)
def test_crawler_generation():
args = docopt(doc, "genconfig trial1 http://www.google.com -t crawler")
gc = genconfig.GenconfigCommand(args)
gc.execute_command()
with open(os.path.join(os.getcwd(), 'trial1.json'), 'r') as f:
config = json.load(f)
nextx = [
{
"follow_link": "",
"scraping": {
"data": [{"field": "", "selector": "", "attr": "", "default": "", "connector": ""}],
"table": [
{
"table_type": "",
"header": "",
"prefix": "",
"suffix": "",
"selector": "",
"attr": "",
"default": "",
"connector": ""
}
]
}
}
]
assert_list_equal(config['scraping']['next'], nextx)
def test_to_list(self):
self.color.from_tuple((20, 40, 69))
test_list = [0] * 5
self.color.to_list(test_list)
assert_list_equal(test_list, [20, 40, 69, 0, 0])
self.color.to_list(test_list, 2)
assert_list_equal(test_list, [20, 40, 20, 40, 69])
def test_read_labels(self, mock_dat):
# mock methods and properties of Datum objects
mock_dat.return_value.ParseFromString.return_value = ""
type(mock_dat.return_value).label = PropertyMock(side_effect=range(5))
assert_list_equal(r.read_labels(self.path_lmdb), range(5))
def test_init3(self):
# partial initialization
expected_result = TestLine.expected_result
line = spectro.Line(restwlen=1.282,
redshift=1., name='Pa_beta')
result = [line.restwlen,line.obswlen,line.redshift,line.name]
assert_list_equal(result, expected_result)
def test_wqstd(self):
nt.assert_true(isinstance(self.db.wqstd, pandas.DataFrame))
nt.assert_tuple_equal(self.db.wqstd.shape, (48, 4))
nt.assert_list_equal(
['parameter', 'units', 'lower_limit', 'upper_limit'],
self.db.wqstd.columns.tolist()
)
def test_write_2bpp_graphic_to_block_offset_xy():
source = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 1, 2, 3, 2, 1, 2, 1],
[0, 0, 2, 3, 1, 0, 2, 3, 2, 2],
[0, 0, 3, 0, 3, 2, 2, 2, 0, 2],
[0, 0, 1, 3, 3, 0, 2, 0, 2, 3],
[0, 0, 1, 0, 1, 1, 0, 3, 3, 3],
[0, 0, 1, 3, 3, 3, 3, 2, 1, 2],
[0, 0, 2, 2, 3, 1, 2, 2, 1, 0],
[0, 0, 2, 0, 3, 3, 2, 3, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
target = Block()
target.from_list([0xff] * 18)
assert_equal(16, write_2bpp_graphic_to_block(source=source, target=target, offset=1, x=2, y=1, bit_offset=0))
assert_list_equal(target.to_list(),
[0xff,
0b01010101,
0b10111010,
0b01100100,
0b11001111,
0b10100000,
0b10111101,
0b11100001,
0b01101011,
0b10110111,
0b00000111,
0b11111010,
0b01111101,
0b00110010,
0b11101100,
0b00110110,
0b10111100,
0xff])
def test_info():
# setup
g = zarr.group(store=dict(), chunk_store=dict(),
synchronizer=zarr.ThreadSynchronizer())
g.create_group('foo')
z = g.zeros('bar', shape=10, filters=[numcodecs.Adler32()])
# test group info
items = g.info_items()
keys = sorted([k for k, _ in items])
expected_keys = sorted([
'Type', 'Read-only', 'Synchronizer type', 'Store type', 'Chunk store type',
'No. members', 'No. arrays', 'No. groups', 'Arrays', 'Groups', 'Name'
])
assert_list_equal(expected_keys, keys)
# test array info
items = z.info_items()
keys = sorted([k for k, _ in items])
expected_keys = sorted([
'Type', 'Data type', 'Shape', 'Chunk shape', 'Order', 'Read-only', 'Filter [0]',
'Compressor', 'Synchronizer type', 'Store type', 'Chunk store type', 'No. bytes',
'No. bytes stored', 'Storage ratio', 'Chunks initialized', 'Name'
])
assert_list_equal(expected_keys, keys)
def test_add_records_to_table2(self):
expected_result = [2,[TestObsTable.obsrecord,TestObsTable.obsrecord]]
TestObsTable.obstable.add_records_to_table([TestObsTable.obsrecord,TestObsTable.obsrecord])
result = []
result.append(TestObsTable.obstable.length)
result.append(TestObsTable.obstable.records)
assert_list_equal(result, expected_result)
def _do_test_sparql(self, datasetname, sparql, expected):
dataset = getattr(self, datasetname)
result = dataset.query(sparql)
if isinstance(expected, list):
assert_list_equal(list(result), expected)
else:
assert_set_equal(set(result), expected)
def test_gzipped_files_are_iterable_as_normal():
agz = _make_temporary_gzip(pybedtools.example_filename('a.bed'))
agz = pybedtools.BedTool(agz)
a = pybedtools.example_bedtool('a.bed')
for i in agz:
print(i)
assert_list_equal(list(a), list(agz))
def test_learning_curve_from_dir(self):
lc = LearningCurveFromPath(os.path.split(self.fpath)[0])
assert_is_not_none(lc)
train_keys, test_keys = lc.parse()
assert_list_equal(train_keys, ['NumIters', 'Seconds', 'LearningRate', 'loss'])
assert_list_equal(test_keys, ['NumIters', 'Seconds', 'LearningRate', 'accuracy', 'loss'])
def test_read_2bpp_graphic_from_block_offset_xy():
source = Block()
source.from_list([0b01010101,
0b10111010,
0b01100100,
0b11001111,
0b10100000,
0b10111101,
0b11100001,
0b01101011,
0b10110111,
0b00000111,
0b11111010,
0b01111101,
0b00110010,
0b11101100,
0b00110110,
0b10111100, 5])
target = [[0 for x in range(10)] for y in range(10)]
assert_equal(16, read_2bpp_graphic_from_block(target=target, source=source, offset=0, x=2, y=1, bit_offset=0))
assert_list_equal(target,
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 2, 1, 2, 3, 2, 1, 2, 1],
[0, 0, 2, 3, 1, 0, 2, 3, 2, 2],
[0, 0, 3, 0, 3, 2, 2, 2, 0, 2],
[0, 0, 1, 3, 3, 0, 2, 0, 2, 3],
[0, 0, 1, 0, 1, 1, 0, 3, 3, 3],
[0, 0, 1, 3, 3, 3, 3, 2, 1, 2],
[0, 0, 2, 2, 3, 1, 2, 2, 1, 0],
[0, 0, 2, 0, 3, 3, 2, 3, 1, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
def test_simple_case():
a = []
b = [a]
c = [a, b]
for perm in permutations([a, b, c]):
result = list(toposorted(perm, lambda x: x))
assert_list_equal([a, b, c], result)
def test_to_block(self):
block = Block()
block.from_list(range(1, 6))
self.pointer.address = 0xabcdef
self.pointer.to_block(block, 1)
assert_list_equal(block[0:5].to_list(), [1, 0xef, 0xcd, 0xab, 5])
def test_append_val(self):
x = FakeClass()
knownlist = ['item1', 'item2', 'NA']
testlist = ['item1']
testlist = station._append_val(x, testlist)
testlist = station._append_val(None, testlist)
ntools.assert_list_equal(testlist, knownlist)
def test_write_2bpp_graphic_to_block():
source = [[2, 1, 2, 3, 2, 1, 2, 1],
[2, 3, 1, 0, 2, 3, 2, 2],
[3, 0, 3, 2, 2, 2, 0, 2],
[1, 3, 3, 0, 2, 0, 2, 3],
[1, 0, 1, 1, 0, 3, 3, 3],
[1, 3, 3, 3, 3, 2, 1, 2],
[2, 2, 3, 1, 2, 2, 1, 0],
[2, 0, 3, 3, 2, 3, 1, 0]]
target = Block()
target.from_list([0] * 16)
assert_equal(16, write_2bpp_graphic_to_block(source=source, target=target, offset=0, x=0, y=0, bit_offset=0))
assert_list_equal(target.to_list(),
[0b01010101,
0b10111010,
0b01100100,
0b11001111,
0b10100000,
0b10111101,
0b11100001,
0b01101011,
0b10110111,
0b00000111,
0b11111010,
0b01111101,
0b00110010,
0b11101100,
0b00110110,
0b10111100])
def test_load():
"""backends.load(): works as expected.
This is an interesting function to test, because it is just a wrapper that
returns a TestrunResult object. So most of the testing should be happening
in the tests for each backend.
However, we can test this by injecting a fake backend, and ensuring that we
get back what we expect. What we do is inject list(), which menas that we
should get back [file_path].
"""
backends.BACKENDS['test_backend'] = backends.register.Registry(
extensions=['.test_extension'],
backend=None,
load=lambda x, y: [x], # y is for a compression value
meta=None,
)
file_path = 'foo.test_extension'
with open(file_path, 'w') as f:
f.write('foo')
test = backends.load(file_path)
nt.assert_list_equal([file_path], test)
def test_plain_attachment(self, gpg):
attachments = [("blabla", None)]
remaining_attachments = import_public_keys_from_attachments(gpg, attachments)
assert_list_equal(attachments, remaining_attachments)
assert not gpg.import_keys.called
def test_getting_uncompleted_todos_when_todos_is_not_none(self):
todo1 = {
'userId': 1,
'id': 1,
'title': 'Make the bed',
'completed': False
}
todo2 = {
'userId': 2,
'id': 2,
'title': 'Walk the dog',
'completed': True
}
# Configure mock to return a response with a JSON-serialized list of todos.
self.mock_get_todos.return_value = Mock()
self.mock_get_todos.return_value.json.return_value = [todo1, todo2]
# Call the service, which will get a list of todos filtered on completed.
uncompleted_todos = get_uncompleted_todos()
# Confirm that the mock was called.
assert_true(self.mock_get_todos.called)
# Confirm that the expected filtered list of todos was returned.
assert_list_equal(uncompleted_todos, [todo1])
def test_comparator():
def comparator(a, b):
a = a.lower()
b = b.lower()
if a < b:
return -1
if a > b:
return 1
else:
return 0
comparator_name = b"CaseInsensitiveComparator"
with tmp_db('comparator', create=False) as name:
db = DB(name,
create_if_missing=True,
comparator=comparator,
comparator_name=comparator_name)
keys = [
b'aaa',
b'BBB',
b'ccc',
]
with db.write_batch() as wb:
for key in keys:
wb.put(key, b'')
assert_list_equal(
sorted(keys, key=lambda s: s.lower()),
list(db.iterator(include_value=False)))
def test_empty(self):
parsed = self.p.parse_args([])
n.assert_false(parsed.urls)
n.assert_false(parsed.force_colnames)
n.assert_false(parsed.silent)
n.assert_in('.pluplusch', parsed.cache_dir)
n.assert_list_equal(parsed.catalog, [])
def test_get_labels_lut(self):
lut = du.get_labels_lut(self.labels, self.subset)
assert_is_instance(lut, np.ndarray)
assert_equals(lut.dtype, int)
assert_equals(lut.ndim, 1)
assert_equals(lut.shape, (9 + 1 + 1, ))
lut_expected = [0] * (9 + 1 + 1)
lut_expected[4] = 5
lut_expected[5] = 2
lut_expected[7] = 2
lut_expected[9] = 9
assert_list_equal(lut.tolist(), lut_expected)
def test_head_tail():
query = schema.User * schema.Language
n = 5
frame = query.head(n, format='frame')
assert_true(isinstance(frame, pandas.DataFrame))
array = query.head(n, format='array')
assert_equal(array.size, n)
assert_equal(len(frame), n)
assert_list_equal(query.primary_key, frame.index.names)
n = 4
frame = query.tail(n, format='frame')
array = query.tail(n, format='array')
assert_equal(array.size, n)
assert_equal(len(frame), n)
assert_list_equal(query.primary_key, frame.index.names)
def test_magic_color():
ip = get_ipython()
c = ip.Completer
s, matches = c.complete(None, 'colo')
nt.assert_in('%colors', matches)
s, matches = c.complete(None, 'colo')
nt.assert_not_in('NoColor', matches)
s, matches = c.complete(None, 'colors ')
nt.assert_in('NoColor', matches)
s, matches = c.complete(None, '%colors ')
nt.assert_in('NoColor', matches)
s, matches = c.complete(None, 'colors NoCo')
nt.assert_list_equal(['NoColor'], matches)
s, matches = c.complete(None, '%colors NoCo')
nt.assert_list_equal(['NoColor'], matches)
def test_str_identity_holds_after_compile():
test_input = [
'+++--->>>.....<',
'+++---[>.<]...<',
'+++[-+.][>+.]>....<',
'[-+.][>+.]>....<',
'+++[-+.][>+.]',
'+++[-+[++].][>+.]',
'[[[[[[[[++]]]]]]]]',
'[>[>[>[>[>[>[>[++]]]]]]]]'
]
assert_list_equal(
lift_str(map(compile, test_input)),
lift_str(test_input),
)
def test_splitlines_with_spans():
data = [
('1\n1', ['1', '1'], [(0, 2), (2, 3)]),
('2\r2', ['2', '2'], [(0, 2), (2, 3)]),
('3\n\r3', ['3', '3'], [(0, 3), (3, 4)]),
('4\r\n4', ['4', '4'], [(0, 3), (3, 4)]),
('5\r\r\n5', ['5', '', '5'], [(0, 2), (2, 4), (4, 5)]),
('\r\n\r\n\n\r', ['', '', ''], [(0, 2), (2, 4), (4, 6)]),
]
for text, expected_lines, expected_spans in data:
actual_lines, actual_spans = splitlines_with_spans(text)
assert_list_equal(actual_lines, expected_lines, 'Actual lines do not match the expected '
'lines for text:\n{0}'.format(text))
assert_list_equal(actual_spans, expected_spans, 'Actual spans do not match the expected '
'spans for text:\n{0}'.format(text))
def test_names_keyword_multiple_names():
grid = RasterModelGrid((4, 5), spacing=(2., 2.))
grid.add_field('node', 'air__temperature', np.arange(20.))
grid.add_field('node', 'land_surface__elevation', np.arange(20.))
with cdtemp() as _:
files = write_esri_ascii(
'test.asc',
grid,
names=['air__temperature', 'land_surface__elevation'])
files.sort()
assert_list_equal(
files,
['test_air__temperature.asc', 'test_land_surface__elevation.asc'])
for fname in files:
assert_true(os.path.isfile(fname))
def test_catalog_report_harvest_all(self):
"""catalog_report() marcará todo dataset para cosecha si
harvest='all'."""
catalog = os.path.join(self.SAMPLES_DIR, "full_data.json")
actual = self.dj.catalog_report(
catalog, harvest='all', catalog_id="modernizacion")
expected = list(self.EXPECTED_REPORT)
expected[0]["harvest"] = 1
expected[1]["harvest"] = 1
# Compruebo explícitamente que el valor de 'harvest' sea el esperado
assert_equal(actual[0]["harvest"], expected[0]["harvest"])
# Compruebo que toda la lista sea la esperada
assert_list_equal(actual, expected)
def test_contents(self):
"""
test the ability of tables to self-populate using the contents property
"""
# test contents
assert_true(self.user)
assert_true(len(self.user) == len(self.user.contents))
u = self.user.fetch(order_by=['username'])
assert_list_equal(list(u['username']), sorted([s[0] for s in self.user.contents]))
# test prepare
assert_true(self.subject)
assert_true(len(self.subject) == len(self.subject.contents))
u = self.subject.fetch(order_by=['subject_id'])
assert_list_equal(list(u['subject_id']), sorted([s[0] for s in self.subject.contents]))
def test_groupby_07(self):
"""
test_groupby_07: Groupby type 'count'
"""
random.seed(1)
groupby_cols = ['f0']
groupby_lambda = lambda x: x[0]
agg_list = [['f4', 'count'], ['f5', 'count'], ['f6', 'count']]
num_rows = 1000
# -- Data --
g = self.gen_dataset_count_with_NA(num_rows)
data = np.fromiter(g, dtype='S1,f8,i8,i4,f8,i8,i4')
# -- Bcolz --
print('--> Bcolz')
self.rootdir = tempfile.mkdtemp(prefix='bcolz-')
os.rmdir(self.rootdir) # folder should be emtpy
fact_bcolz = bquery.ctable(data, rootdir=self.rootdir)
fact_bcolz.flush()
fact_bcolz.cache_factor(groupby_cols, refresh=True)
result_bcolz = fact_bcolz.groupby(groupby_cols, agg_list)
print(result_bcolz)
# Itertools result
print('--> Itertools')
result_itt = self.helper_itt_groupby(data, groupby_lambda)
uniquekeys = result_itt['uniquekeys']
print(uniquekeys)
ref = []
for item in result_itt['groups']:
f4 = 0
f5 = 0
f6 = 0
for row in item:
f0 = groupby_lambda(row)
if row[4] == row[4]:
f4 += 1
f5 += 1
f6 += 1
ref.append([f0, f4, f5, f6])
assert_list_equal(
[list(x) for x in result_bcolz], ref)
def test_get_regulations():
"""
Test default get regulations behavior.
:return:
"""
lexnlp_tests.test_extraction_func_on_test_data(
get_regulations,
expected_data_converter=lambda d: [
(reg_type, reg_code) for reg_type, reg_code, _reg_str in d
],
return_source=False,
as_dict=False)
lexnlp_tests.test_extraction_func_on_test_data(
get_regulations,
expected_data_converter=lambda d: [
(reg_type, reg_code, reg_str) for reg_type, reg_code, reg_str in d
],
return_source=True,
as_dict=False)
# TODO Impl test_extraction_func_on_test_data() comparing lists of dicts
for (_i, text, _input_args,
expected) in lexnlp_tests.iter_test_data_text_and_tuple():
expected_no_source_dict = [{
'regulation_type': reg_type,
'regulation_code': reg_code
} for reg_type, reg_code, _reg_str in expected]
expected_source_dict = [{
'regulation_type': reg_type,
'regulation_code': reg_code,
'regulation_str': reg_str
} for reg_type, reg_code, reg_str in expected]
assert_list_equal(
list(
lexnlp_tests.benchmark_extraction_func(get_regulations,
text,
return_source=False,
as_dict=True)),
expected_no_source_dict)
assert_list_equal(
list(
lexnlp_tests.benchmark_extraction_func(get_regulations,
text,
return_source=True,
as_dict=True)),
expected_source_dict)
def test_filter_tables(self, tokenizer, overlap_size, comp_op,
allow_missing, args, expected_pairs):
overlap_filter = OverlapFilter(tokenizer, overlap_size, comp_op,
allow_missing)
actual_candset = overlap_filter.filter_tables(*args)
expected_output_attrs = ['_id']
l_out_prefix = self.default_l_out_prefix
r_out_prefix = self.default_r_out_prefix
# Check for l_out_prefix in args.
if len(args) > 8:
l_out_prefix = args[8]
expected_output_attrs.append(l_out_prefix + args[2])
# Check for r_out_prefix in args.
if len(args) > 9:
r_out_prefix = args[9]
expected_output_attrs.append(r_out_prefix + args[3])
# Check for l_out_attrs in args.
if len(args) > 6:
if args[6]:
l_out_attrs = remove_redundant_attrs(args[6], args[2])
for attr in l_out_attrs:
expected_output_attrs.append(l_out_prefix + attr)
# Check for r_out_attrs in args.
if len(args) > 7:
if args[7]:
r_out_attrs = remove_redundant_attrs(args[7], args[3])
for attr in r_out_attrs:
expected_output_attrs.append(r_out_prefix + attr)
# verify whether the output table has the necessary attributes.
assert_list_equal(list(actual_candset.columns.values),
expected_output_attrs)
actual_pairs = set()
for idx, row in actual_candset.iterrows():
actual_pairs.add(','.join((str(row[l_out_prefix + args[2]]),
str(row[r_out_prefix + args[3]]))))
# verify whether the actual pairs and the expected pairs match.
assert_equal(len(expected_pairs), len(actual_pairs))
common_pairs = actual_pairs.intersection(expected_pairs)
assert_equal(len(common_pairs), len(expected_pairs))
def test_setitem_slice(self):
self.block.from_file(os.path.join(TEST_DATA_DIR, "binaries", "1kb_rand.bin"))
assert_list_equal(self.block[0:3].to_list(), [0x25, 0x20, 0x38])
self.block[0:3] = [0xeb, 0x15, 0x66]
assert_list_equal(self.block[0:3].to_list(), [0xeb, 0x15, 0x66])
self.block[0:1024] = [5] * 1024
assert_equal(self.block[0:1024].to_list(), [5] * 1024)
assert_raises(InvalidArgumentError, self.block.__setitem__, slice(5, 0), [])
assert_raises(InvalidArgumentError, self.block.__setitem__, slice(55, 55), [])
assert_raises(OutOfBoundsError, self.block.__setitem__, slice(-1, 2), [])
assert_raises(OutOfBoundsError, self.block.__setitem__, slice(1, 1025), [0] * 1024)
assert_raises(OutOfBoundsError, self.block.__setitem__, slice(1024, 1025), [1])
assert_raises(InvalidArgumentError, self.block.__setitem__, slice(0, 1), [])
assert_raises(InvalidArgumentError, self.block.__setitem__, slice(0, 1), [1, 2, 3])
assert_raises(InvalidArgumentError, self.block.__setitem__, slice(0, 5), [1, 2])
def test_save_passengers_location(mock_validate_token, mock_passengers):
input = {'lat': 47.2737, 'lon': 28.284}
header = {'token': '838298'}
mock_validate_token.return_value = True
mock_passengers.update_one.return_value = None
app2 = app.test_client()
response = app2.put('/passengers/1/location',
data=json.dumps(input),
headers=header,
content_type='application/json')
response_json = json.loads(response.get_data())
assert_list_equal([response_json], [200])
def test_read_1bpp_graphic_from_block_offset_target():
source = Block()
source.from_list([
0b00000011, 0b01110000, 0b01001001, 0b11110000, 0b01001010, 0b11001000,
0b01110001, 0b00000001
])
target = [[0 for x in range(10)] for y in range(10)]
assert_equal(
8, read_1bpp_graphic_from_block(source, target, 0, x=2, y=1, height=8))
assert_list_equal(
target,
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1],
[0, 0, 0, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 1, 0, 0, 1],
[0, 0, 1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 1, 0, 1, 0],
[0, 0, 1, 1, 0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
def test_find_resources_dir(self, mocked_isdir):
# arrange
mocked_isdir.side_effect = [False, False, True]
start_dir = '/foo/bar/baz'
expected_result = '/foo/test_resources'
# act
actual_result = helpers._find_test_resources_dir(start_dir)
# assert
assert_equal(expected_result, actual_result)
assert_list_equal(mocked_isdir.mock_calls, [
call('/foo/bar/baz/test_resources'),
call('/foo/bar/test_resources'),
call('/foo/test_resources'),
])
def test_write_custom_section(self):
"""Test ``write()`` when a custom section is defined"""
# Create a ``SampleSheet`` with a [Manifests] section
sample_sheet1 = SampleSheet()
sample_sheet1.add_section('Manifests')
sample_sheet1.Manifests['PoolRNA'] = 'RNAMatrix.txt'
# Write to string and make temporary file
string_handle = StringIO(newline=None)
sample_sheet1.write(string_handle)
string_handle.seek(0)
filename = string_as_temporary_file(string_handle.read())
# Read temporary file and confirm section and it's data exists.
sample_sheet2 = SampleSheet(filename)
assert_list_equal(list(sample_sheet2.Manifests.keys()), ['PoolRNA'])
eq_(sample_sheet2.Manifests.PoolRNA, 'RNAMatrix.txt')
def test_merge():
data_before_merge = [
{
'time': '100',
'station_id': 1,
'temp': 45
},
{
'time': '100',
'station_id': 1,
'wind_dir': 200
},
{
'time': '200',
'station_id': 1,
'temp': 44
},
{
'time': '300',
'station_id': 3,
'temp': 38
},
{
'time': '300',
'station_id': 3,
'wind_dir': 300,
'wind_speed': 7
},
]
expected = [{
'time': '100',
'station_id': 1,
'temp': 45,
'wind_dir': 200
}, {
'time': '200',
'station_id': 1,
'temp': 44
}, {
'time': '300',
'station_id': 3,
'temp': 38,
'wind_dir': 300,
'wind_speed': 7
}]
assert_list_equal(expected, merge(data_before_merge))
def test_filter_candset(self, tokenizer, sim_measure_type, threshold, args,
expected_pairs):
size_filter = SizeFilter(tokenizer, sim_measure_type, threshold)
actual_output_candset = size_filter.filter_candset(*args)
# verify whether the output table has the necessary attributes.
assert_list_equal(list(actual_output_candset.columns.values),
list(args[0].columns.values))
actual_pairs = set()
for idx, row in actual_output_candset.iterrows():
actual_pairs.add(','.join((str(row[args[1]]), str(row[args[2]]))))
# verify whether the actual pairs and the expected pairs match.
assert_equal(len(expected_pairs), len(actual_pairs))
common_pairs = actual_pairs.intersection(expected_pairs)
assert_equal(len(common_pairs), len(expected_pairs))
def test_baseline(self):
with utils.OverwriteState(True), utils.WorkSpace(self.ws):
wq, cols = analysis.preprocess_wq(
monitoring_locations=self.ml,
subcatchments=self.sc,
id_col='CID',
ds_col='DS_CID',
output_path=self.results,
value_columns=self.wq_cols
)
expected = 'expected.shp'
pptest.assert_shapefiles_are_close(
os.path.join(self.ws, expected),
os.path.join(self.ws, self.results),
)
nt.assert_true(isinstance(wq, numpy.ndarray))
nt.assert_list_equal(cols, self.expected_cols)
def test_merge_with_special_byte():
factory = bl.BlockFactory()
block1 = factory.new_block()
block1.data = [
filepack.SPECIAL_BYTE, filepack.SPECIAL_BYTE, 2, 1, 3,
filepack.SPECIAL_BYTE, 1, 0, 0
]
block2 = factory.new_block()
block2.data = [4, 3, 6, filepack.SPECIAL_BYTE, filepack.EOF_BYTE]
data = filepack.merge(factory.blocks)
expected_data = [
filepack.SPECIAL_BYTE, filepack.SPECIAL_BYTE, 2, 1, 3, 4, 3, 6
]
assert_list_equal(data, expected_data)
def run_sentence_token_test(text, result, lowercase=False, stopword=False):
"""
Base test method to run against text with given results.
"""
# Get list from text
sentence_list = get_sentence_list(text)
# Check length first
assert len(sentence_list) == len(result)
# Check each sentence matches
for i in range(len(sentence_list)):
tokens = lexnlp_tests.benchmark_extraction_func(get_token_list,
sentence_list[i],
lowercase=lowercase,
stopword=stopword)
assert_list_equal(tokens, result[i])
def test_params_as_list(self):
params = self.tbx._params_as_list()
names = [str(p.name) for p in params]
known_names = [
'workspace',
'subcatchments',
'ID_column',
'downstream_ID_column',
'monitoring_locations',
'ml_type_col',
'included_ml_types',
'value_columns',
'streams',
'output_layer',
'add_output_to_map',
]
nt.assert_list_equal(names, known_names)
def test_fname_pairs(self):
a = ['foo1_a.txt', os.path.join('foo', 'bar_x.txt'), 'foo5.txt']
b = [os.path.join('oof', 'bar_x.txt'), 'foo5_b.txt', 'foo2_b.txt']
pairs = fs.fname_pairs(a, b)
for x, y in pairs:
assert_in(x, a)
assert_in(y, b)
assert_list_equal(pairs, [
[
os.path.join('foo', 'bar_x.txt'),
os.path.join('oof', 'bar_x.txt')
],
['foo5.txt', 'foo5_b.txt'],
])
def test_simple_read_write():
data = [i % 10 for i in range(bl.BLOCK_SIZE * 5 + 17)]
reader = bl.BlockReader()
writer = bl.BlockWriter()
factory = bl.BlockFactory()
block_ids = writer.write(data, factory)
blocks = {}
for i in block_ids:
blocks[i] = factory.blocks[i]
recovered_data = reader.read(blocks)
assert_list_equal(data, recovered_data)
def test_complex_matlab_blobs(self):
blobs = Blob().fetch('blob', order_by='id')
assert_equal(blobs[0][0], 'character string')
assert_true(np.array_equal(blobs[1][0], np.r_[1:180:15]))
assert_list_equal([r[0] for r in blobs[2]], ['string1', 'string2'])
assert_list_equal([r[0, 0] for r in blobs[3]['a'][0]], [1, 2])
assert_tuple_equal(blobs[3]['b'][0, 0]['c'][0, 0].shape, (3, 3))
assert_true(
np.array_equal(blobs[4], np.r_[1:25].reshape((2, 3, 4),
order='F')))
assert_true(blobs[4].dtype == 'float64')
assert_true(
np.array_equal(blobs[5], np.r_[1:25].reshape((2, 3, 4),
order='F')))
assert_true(blobs[5].dtype == 'uint8')
assert_tuple_equal(blobs[6].shape, (2, 3, 4))
assert_true(blobs[6].dtype == 'complex128')
def test_data_type():
"""Test automatic data type importing"""
puts1 = [10, 20, 30, 40, 50]
puts2 = {'apples': 10, 'bananas': 20, 'oranges': 30}
gets1 = [{'col': 'data', 'idx': 0, 'val': 10},
{'col': 'data', 'idx': 1, 'val': 20},
{'col': 'data', 'idx': 2, 'val': 30},
{'col': 'data', 'idx': 3, 'val': 40},
{'col': 'data', 'idx': 4, 'val': 50}]
gets2 = [{'col': 'data', 'idx': 'apples', 'val': 10},
{'col': 'data', 'idx': 'bananas', 'val': 20},
{'col': 'data', 'idx': 'oranges', 'val': 30}]
for ins, outs in zip([puts1, puts2], [gets1, gets2]):
test = data_type(ins)
nt.assert_list_equal(test.values, outs)
# From Iters
puts = {'x': [1, 2, 3], 'y': [10, 20, 30], 'z': [40, 50, 60]}
gets = [{'col': 'y', 'idx': 1, 'val': 10},
{'col': 'y', 'idx': 2, 'val': 20},
{'col': 'y', 'idx': 3, 'val': 30},
{'col': 'z', 'idx': 1, 'val': 40},
{'col': 'z', 'idx': 2, 'val': 50},
{'col': 'z', 'idx': 3, 'val': 60}]
test = data_type(puts, iter_idx='x')
nt.assert_list_equal(test.values, gets)
# Pandas
df = pd.DataFrame({'one': [1, 2, 3], 'two': [4, 5, 6]})
series = pd.Series([1, 2, 3], name='test')
gets1 = [{'col': 'one', 'idx': 0, 'val': 1},
{'col': 'two', 'idx': 0, 'val': 4},
{'col': 'one', 'idx': 1, 'val': 2},
{'col': 'two', 'idx': 1, 'val': 5},
{'col': 'one', 'idx': 2, 'val': 3},
{'col': 'two', 'idx': 2, 'val': 6}]
gets2 = [{'col': 'test', 'idx': 0, 'val': 1},
{'col': 'test', 'idx': 1, 'val': 2},
{'col': 'test', 'idx': 2, 'val': 3}]
test_df = data_type(df)
test_series = data_type(series)
nt.assert_list_equal(test_df.values, gets1)
nt.assert_list_equal(test_series.values, gets2)
# Bad type
class BadType(object):
'Bad data type'
pass
test = BadType()
nt.assert_raises(ValueError, data_type, test)
def test_groupby_09(self):
"""
test_groupby_09: Groupby's type 'sorted_count_distinct'
"""
random.seed(1)
groupby_cols = ['f0']
groupby_lambda = lambda x: x[0]
agg_list = [['f4', 'sorted_count_distinct'], ['f5', 'sorted_count_distinct'], ['f6', 'sorted_count_distinct']]
num_rows = 2000
# -- Data --
g = self.gen_dataset_count_with_NA_09(num_rows)
sort = sorted([item for item in g], key=lambda x: x[0])
data = np.fromiter(sort, dtype='S1,f8,i8,i4,f8,i8,i4')
print('data')
print(data)
# -- Bcolz --
print('--> Bcolz')
self.rootdir = tempfile.mkdtemp(prefix='bcolz-')
os.rmdir(self.rootdir) # folder should be emtpy
fact_bcolz = bquery.ctable(data, rootdir=self.rootdir)
fact_bcolz.flush()
result_bcolz = fact_bcolz.groupby(groupby_cols, agg_list)
print(result_bcolz)
# # Itertools result
print('--> Itertools')
result_itt = self.helper_itt_groupby(data, groupby_lambda)
uniquekeys = result_itt['uniquekeys']
print(uniquekeys)
ref = []
for n, (u, item) in enumerate(zip(uniquekeys, result_itt['groups'])):
f4 = len(self._get_unique([x[4] for x in result_itt['groups'][n]]))
f5 = len(self._get_unique([x[5] for x in result_itt['groups'][n]]))
f6 = len(self._get_unique([x[6] for x in result_itt['groups'][n]]))
ref.append([u, f4, f5, f6])
print(ref)
assert_list_equal(
[list(x) for x in result_bcolz], ref)
def test_filter_tables(self, tokenizer, sim_measure_type, threshold, args,
expected_pairs):
position_filter = PositionFilter(tokenizer, sim_measure_type,
threshold)
actual_candset = position_filter.filter_tables(*args)
expected_output_attrs = ['_id']
l_out_prefix = self.default_l_out_prefix
r_out_prefix = self.default_r_out_prefix
# Check for l_out_prefix in args.
if len(args) > 8:
l_out_prefix = args[8]
expected_output_attrs.append(l_out_prefix + args[2])
# Check for l_out_attrs in args.
if len(args) > 6:
if args[6]:
for attr in args[6]:
expected_output_attrs.append(l_out_prefix + attr)
# Check for r_out_prefix in args.
if len(args) > 9:
r_out_prefix = args[9]
expected_output_attrs.append(r_out_prefix + args[3])
# Check for r_out_attrs in args.
if len(args) > 7:
if args[7]:
for attr in args[7]:
expected_output_attrs.append(r_out_prefix + attr)
# verify whether the output table has the necessary attributes.
assert_list_equal(list(actual_candset.columns.values),
expected_output_attrs)
actual_pairs = set()
for idx, row in actual_candset.iterrows():
actual_pairs.add(','.join((str(row[l_out_prefix + args[2]]),
str(row[r_out_prefix + args[3]]))))
# verify whether the actual pairs and the expected pairs match.
assert_equal(len(expected_pairs), len(actual_pairs))
common_pairs = actual_pairs.intersection(expected_pairs)
assert_equal(len(common_pairs), len(expected_pairs))
def test_unite_master_parts():
assert_list_equal(
unite_master_parts([
"`s`.`a`",
"`s`.`a__q`",
"`s`.`b`",
"`s`.`c`",
"`s`.`c__q`",
"`s`.`b__q`",
"`s`.`d`",
"`s`.`a__r`",
]),
[
"`s`.`a`",
"`s`.`a__q`",
"`s`.`a__r`",
"`s`.`b`",
"`s`.`b__q`",
"`s`.`c`",
"`s`.`c__q`",
"`s`.`d`",
],
)
assert_list_equal(
unite_master_parts([
"`lab`.`#equipment`",
"`cells`.`cell_analysis_method`",
"`cells`.`cell_analysis_method_task_type`",
"`cells`.`cell_analysis_method_users`",
"`cells`.`favorite_selection`",
"`cells`.`cell_analysis_method__cell_selection_params`",
"`lab`.`#equipment__config`",
"`cells`.`cell_analysis_method__field_detect_params`",
]),
[
"`lab`.`#equipment`",
"`lab`.`#equipment__config`",
"`cells`.`cell_analysis_method`",
"`cells`.`cell_analysis_method__cell_selection_params`",
"`cells`.`cell_analysis_method__field_detect_params`",
"`cells`.`cell_analysis_method_task_type`",
"`cells`.`cell_analysis_method_users`",
"`cells`.`favorite_selection`",
],
)
def test_posting_user_card_when_response_is_ok(mock_post, mock_validate_token):
card_data = {
'metadata': {},
'card': {
'ccvv': '274827484',
'expiration_month': '12',
'expiration_year': '1738',
'method': 'card',
'number': '27484277',
'type': 'visa'
}
}
input = {
'ccvv': '274827484',
'expiration_month': '12',
'expiration_year': '1738',
'method': 'card',
'number': '27484277',
'type': 'visa'
}
app_response = {
'ccvv': '274827484',
'expiration_month': '12',
'expiration_year': '1738',
'method': 'card',
'number': '27484277',
'type': 'visa'
}
header = {'token': '838298'}
mock_validate_token.return_value = True
mock_post.return_value = Mock(ok=True)
mock_post.return_value.json.return_value = card_data
app2 = app.test_client()
response = app2.post('/passengers/84748/card',
data=json.dumps(input),
headers=header,
content_type='application/json')
response_json = json.loads(response.get_data())
assert_list_equal([response_json], [app_response])
