def test_append2(self):
persist = blaze.Storage(self.rooturi, format="blz")
a = blaze.empty('0 * 2 * float64', storage=persist)
self.assertTrue(isinstance(a, blaze.Array))
lvals = [[i,i*2] for i in range(10)]
append(a,lvals)
self.assertEqual(dd_as_py(a._data), lvals)
def test_create(self):
persist = blaze.Storage(self.rooturi, format="blz")
a = blaze.array([], 'float64', storage=persist)
self.assertTrue(isinstance(a, blaze.Array))
print("->", a.dshape.shape)
self.assertTrue(a.dshape.shape == (0,))
self.assertEqual(dd_as_py(a._data), [])
def test_open(self):
persist = blaze.Storage(self.rooturi, format="blz")
a = blaze.ones('0 * float64', storage=persist)
append(a,range(10))
# Re-open the dataset in URI
a2 = blaze.open(persist)
self.assertTrue(isinstance(a2, blaze.Array))
self.assertEqual(dd_as_py(a2._data), list(range(10)))
del describe_array
# --------------------------------------------------------------------
print_section('Persisted arrays')
def maybe_remove(persist):
import os.path
if os.path.exists(persist.path):
# Remove every directory starting with rootdir
blaze.drop(persist)
# Create an empty array on-disk
dname = 'blz://persisted.blz'
store = blaze.Storage(dname)
maybe_remove(store)
p = blaze.zeros('0, float64', storage=store)
# Feed it with some data
blaze.append(p, range(10))
print('Before re-opening:', p)
# Re-open the dataset in URI
p2 = blaze.open(store)
print('After re-opening:', p2)
blaze.drop(dname)
def test_append(self):
persist = blaze.Storage(self.rooturi, format="blz")
a = blaze.zeros('0 * float64', storage=persist)
self.assertTrue(isinstance(a, blaze.Array))
append(a,list(range(10)))
self.assertEqual(dd_as_py(a._data), list(range(10)))
def test_deprecated_open(self):
url = "json://" + self.fname
store = blaze.Storage(url, mode='r')
a = blaze.open(store, schema=json_schema)
self.assert_(isinstance(a, blaze.Array))
self.assertEqual(dd_as_py(a._data), [1, 2, 3, 4, 5])
fname = "sample.h5"
print_section('building basic hdf5 files')
# Create a simple HDF5 file
a1 = np.array([[1, 2, 3], [4, 5, 6]], dtype="int32")
a2 = np.array([[1, 2, 3], [3, 2, 1]], dtype="int64")
t1 = np.array([(1, 2, 3), (3, 2, 1)], dtype="i4,i8,f8")
with tb.open_file(fname, "w") as f:
f.create_array(f.root, 'a1', a1)
f.create_table(f.root, 't1', t1)
f.create_group(f.root, 'g')
f.create_array(f.root.g, 'a2', a2)
print("Created HDF5 file with the next contents:\n%s" % str(f))
print_section('opening and handling datasets in hdf5 files')
# Open an homogeneous dataset there
store = blaze.Storage(fname, format='hdf5')
a = blaze.open(store, datapath="/a1")
# Print it
print("/a1 contents:", a)
# Print the datashape
print("datashape for /a1:", a.dshape)
# Open another homogeneous dataset there
store = blaze.Storage(fname, format='hdf5')
a = blaze.open(store, datapath="/g/a2")
# Print it
print("/g/a2 contents:", a)
# Print the datashape
print("datashape for /g/a2:", a.dshape)
# Now, get an heterogeneous dataset
def test_open(self):
store = blaze.Storage(self.url, mode='r')
a = blaze.open(store, schema=json_schema)
self.assert_(isinstance(a, blaze.Array))
self.assertEqual(dd_as_py(a._data), [1, 2, 3, 4, 5])
def test_deprecated_open(self):
url = "csv://" + self.fname
store = blaze.Storage(url, mode='r')
a = blaze.open(store, schema=csv_schema)
self.assert_(isinstance(a, blaze.Array))
self.assertEqual(dd_as_py(a._data), csv_ldict)
def test_append(self):
store = blaze.Storage(self.url, mode='r+')
a = blaze.open(store, schema=csv_schema)
blaze.append(a, ["k4", "v4", 4, True])
self.assertEqual(dd_as_py(a._data), csv_ldict + \
[{u'f0': u'k4', u'f1': u'v4', u'f2': 4, u'f3': True}])
def test_open_has_header(self):
store = blaze.Storage(self.url, mode='r')
a = blaze.open(store, schema=csv_schema, has_header=False)
self.assert_(isinstance(a, blaze.Array))
self.assertEqual(dd_as_py(a._data), csv_ldict)
def test_open_dialect(self):
store = blaze.Storage(self.url, mode='r')
a = blaze.open(store, schema=csv_schema, dialect='excel')
self.assert_(isinstance(a, blaze.Array))
self.assertEqual(dd_as_py(a._data), csv_ldict)
