def test_read_parquet_str(self):
t = XFrame({'id': [1, 2, 3], 'val': ['a', 'b', 'c']})
path = '{}/tmp/frame-parquet'.format(hdfs_prefix)
t.save(path, format='parquet')
res = XFrame('{}/tmp/frame-parquet.parquet'.format(hdfs_prefix))
# results may not come back in the same order
res = res.sort('id')
self.assertEqualLen(3, res)
self.assertListEqual(['id', 'val'], res.column_names())
self.assertListEqual([int, str], res.column_types())
self.assertDictEqual({'id': 1, 'val': 'a'}, res[0])
self.assertDictEqual({'id': 2, 'val': 'b'}, res[1])
self.assertDictEqual({'id': 3, 'val': 'c'}, res[2])
fileio.delete(path)
def predict_all(self, user):
"""
Predict ratings for all items.
Parameters
----------
user : int
The user to make predictions for.
Returns
-------
out : XFrame
Each row of the frame consists of a user id, an item id, and a predicted rating.
"""
# build rdd to pass to predictAll
user_item = XFrame()
user_item[self.item_col] = self.items
user_item[self.user_col] = user
user_item.swap_columns(self.item_col, self.user_col)
rdd = user_item.to_rdd()
res = self.model.predictAll(rdd)
res = res.map(lambda rating: (rating.user, rating.product, rating.rating))
col_names = [self.user_col, self.item_col, self.rating_col]
user_type = self.users.dtype()
item_type = self.items.dtype()
col_types = [user_type, item_type, float]
return XFrame.from_rdd(res, column_names=col_names, column_types=col_types)
def test_save(self):
t = XFrame({'id': [30, 20, 10], 'val': ['a', 'b', 'c']})
path = '{}/tmp/frame'.format(hdfs_prefix)
t.save(path, format='binary')
with fileio.open_file(os.path.join(path, '_metadata')) as f:
metadata = pickle.load(f)
self.assertListEqual([['id', 'val'], [int, str]], metadata)
# TODO find some way to check the data
fileio.delete(path)
def test_construct_auto_str_psv(self):
path = '{}/user/xpatterns/files/test-frame.psv'.format(hdfs_prefix)
res = XFrame(path)
self.assertEqualLen(3, res)
self.assertListEqual(['id', 'val'], res.column_names())
self.assertListEqual([int, str], res.column_types())
self.assertDictEqual({'id': 1, 'val': 'a'}, res[0])
self.assertDictEqual({'id': 2, 'val': 'b'}, res[1])
self.assertDictEqual({'id': 3, 'val': 'c'}, res[2])
def test_construct_str_xframe(self):
# construct and XFrame given a saved xframe
path = '{}/user/xpatterns/files/test-frame'.format(hdfs_prefix)
res = XFrame(path, format='xframe')
res = res.sort('id')
self.assertEqualLen(3, res)
self.assertListEqual(['id', 'val'], res.column_names())
self.assertListEqual([int, str], res.column_types())
self.assertDictEqual({'id': 1, 'val': 'a'}, res[0])
self.assertDictEqual({'id': 2, 'val': 'b'}, res[1])
self.assertDictEqual({'id': 3, 'val': 'c'}, res[2])
def test_construct_str_csv(self):
# construct and XFrame given a text file
# interpret as csv
path = '{}/user/xpatterns/files/test-frame.txt'.format(hdfs_prefix)
res = XFrame(path, format='csv')
self.assertEqualLen(3, res)
self.assertListEqual(['id', 'val'], res.column_names())
self.assertListEqual([int, str], res.column_types())
self.assertDictEqual({'id': 1, 'val': 'a'}, res[0])
self.assertDictEqual({'id': 2, 'val': 'b'}, res[1])
self.assertDictEqual({'id': 3, 'val': 'c'}, res[2])
def test_construct_auto_str_xframe(self):
# construct an XFrame given a file with unrecognized file extension
path = '{}/user/xpatterns/files/test-frame'.format(hdfs_prefix)
res = XFrame(path)
res = res.sort('id')
self.assertEqualLen(3, res)
self.assertListEqual(['id', 'val'], res.column_names())
self.assertListEqual([int, str], res.column_types())
self.assertDictEqual({'id': 1, 'val': 'a'}, res[0])
self.assertDictEqual({'id': 2, 'val': 'b'}, res[1])
self.assertDictEqual({'id': 3, 'val': 'c'}, res[2])
def test_save(self):
t = XFrame({'id': [30, 20, 10], 'val': ['a', 'b', 'c']})
path = '{}/tmp/frame-csv'.format(hdfs_prefix)
t.save(path, format='csv')
with fileio.open_file(path + '.csv') as f:
heading = f.readline().rstrip()
self.assertEqual('id,val', heading)
self.assertEqual('30,a', f.readline().rstrip())
self.assertEqual('20,b', f.readline().rstrip())
self.assertEqual('10,c', f.readline().rstrip())
fileio.delete(path + '.csv')
def test_construct_auto_dataframe(self):
path = '{}/user/xpatterns/files/test-frame-auto.csv'.format(hdfs_prefix)
res = XFrame(path)
self.assertEqualLen(3, res)
self.assertListEqual(['val_int', 'val_int_signed', 'val_float', 'val_float_signed',
'val_str', 'val_list', 'val_dict'], res.column_names())
self.assertListEqual([int, int, float, float, str, list, dict], res.column_types())
self.assertDictEqual({'val_int': 1, 'val_int_signed': -1, 'val_float': 1.0, 'val_float_signed': -1.0,
'val_str': 'a', 'val_list': ['a'], 'val_dict': {1: 'a'}}, res[0])
self.assertDictEqual({'val_int': 2, 'val_int_signed': -2, 'val_float': 2.0, 'val_float_signed': -2.0,
'val_str': 'b', 'val_list': ['b'], 'val_dict': {2: 'b'}}, res[1])
self.assertDictEqual({'val_int': 3, 'val_int_signed': -3, 'val_float': 3.0, 'val_float_signed': -3.0,
'val_str': 'c', 'val_list': ['c'], 'val_dict': {3: 'c'}}, res[2])
from xframes import XFrame
xf = XFrame({'id': [1, 2, 3], 'val': ['a', 'b', 'c']})
print xf
def test_save(self):
t = XFrame({'id': [30, 20, 10], 'val': ['a', 'b', 'c']})
path = '{}/tmp/frame-parquet'.format(hdfs_prefix)
t.save(path, format='parquet')
# TODO verify
fileio.delete(path + '.parquet')
