def test_list_of_rows_table():
data = [["John Coltrane", 1926, 8.65, False],
["Miles Davis", 1926, 9.87, False],
["Bill Evans", 1929, 7.65, False],
["Paul Chambers", 1935, 5.14, False],
["Jimmy Cobb", 1929, 5.78, True],
["Scott LaFaro", 1936, 4.21, False],
["Sonny Rollins", 1930, 8.99, True],
["Kenny Burrel", 1931, 4.37, True]]
cols = [Column(id='1', name='Name', columnType='STRING'),
Column(id='2', name='Born', columnType='INTEGER'),
Column(id='3', name='Hipness', columnType='DOUBLE'),
Column(id='4', name='Living', columnType='BOOLEAN')]
schema1 = Schema(name='Jazz Guys', columns=cols, id="syn1000002", parent="syn1000001")
# need columns to do cast_values w/o storing
table = Table(schema1, data, headers=[SelectColumn.from_column(col) for col in cols])
for table_row, expected_row in zip(table, data):
assert_equals(table_row, expected_row)
rowset = table.asRowSet()
for rowset_row, expected_row in zip(rowset.rows, data):
assert_equals(rowset_row['values'], expected_row)
table.columns = cols
df = table.asDataFrame()
assert_equals(list(df['Name']), [r[0] for r in data])
def test_RowSetTable():
row_set_json = {
'etag': 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee',
'headers': [
{'columnType': 'STRING', 'id': '353', 'name': 'name'},
{'columnType': 'DOUBLE', 'id': '355', 'name': 'x'},
{'columnType': 'DOUBLE', 'id': '3020', 'name': 'y'},
{'columnType': 'INTEGER', 'id': '891', 'name': 'n'}],
'rows': [{
'rowId': 5,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 3},
{'rowId': 6,
'values': ['bar', '1.34', '2.4', '101'],
'versionNumber': 3},
{'rowId': 7,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 4},
{'rowId': 8,
'values': ['qux', '1.23', '2.2', '102'],
'versionNumber': 3}],
'tableId': 'syn2976298'}
row_set = RowSet.from_json(row_set_json)
assert row_set.etag == 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'
assert row_set.tableId == 'syn2976298'
assert len(row_set.headers) == 4
assert len(row_set.rows) == 4
schema = Schema(id="syn2976298", name="Bogus Schema", columns=[353,355,3020,891], parent="syn1000001")
table = Table(schema, row_set)
assert table.etag == 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'
assert table.tableId == 'syn2976298'
assert len(table.headers) == 4
assert len(table.asRowSet().rows) == 4
try:
import pandas as pd
df = table.asDataFrame()
assert df.shape == (4,4)
assert all(df['name'] == ['foo', 'bar', 'foo', 'qux'])
except ImportError as e1:
sys.stderr.write('Pandas is apparently not installed, skipping part of test_RowSetTable.\n\n')
def test_list_of_rows_table():
data = [["John Coltrane", 1926, 8.65, False],
["Miles Davis", 1926, 9.87, False],
["Bill Evans", 1929, 7.65, False],
["Paul Chambers", 1935, 5.14, False],
["Jimmy Cobb", 1929, 5.78, True],
["Scott LaFaro", 1936, 4.21, False],
["Sonny Rollins", 1930, 8.99, True],
["Kenny Burrel", 1931, 4.37, True]]
cols = []
cols.append(Column(id='1', name='Name', columnType='STRING'))
cols.append(Column(id='2', name='Born', columnType='INTEGER'))
cols.append(Column(id='3', name='Hipness', columnType='DOUBLE'))
cols.append(Column(id='4', name='Living', columnType='BOOLEAN'))
schema1 = Schema(name='Jazz Guys',
columns=cols,
id="syn1000002",
parent="syn1000001")
## need columns to do cast_values w/o storing
table = Table(schema1,
data,
headers=[SelectColumn.from_column(col) for col in cols])
for table_row, expected_row in zip(table, data):
assert table_row == expected_row
rowset = table.asRowSet()
for rowset_row, expected_row in zip(rowset.rows, data):
assert rowset_row['values'] == expected_row
table.columns = cols
## test asDataFrame
try:
import pandas as pd
df = table.asDataFrame()
assert all(df['Name'] == [r[0] for r in data])
except ImportError as e1:
sys.stderr.write(
'Pandas is apparently not installed, skipping asDataFrame portion of test_list_of_rows_table.\n\n'
)
def test_RowSetTable():
row_set_json = {
'etag': 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee',
'headers': [
{'columnType': 'STRING', 'id': '353', 'name': 'name'},
{'columnType': 'DOUBLE', 'id': '355', 'name': 'x'},
{'columnType': 'DOUBLE', 'id': '3020', 'name': 'y'},
{'columnType': 'INTEGER', 'id': '891', 'name': 'n'}],
'rows': [{
'rowId': 5,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 3},
{'rowId': 6,
'values': ['bar', '1.34', '2.4', '101'],
'versionNumber': 3},
{'rowId': 7,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 4},
{'rowId': 8,
'values': ['qux', '1.23', '2.2', '102'],
'versionNumber': 3}],
'tableId': 'syn2976298'}
row_set = RowSet.from_json(row_set_json)
assert_equals(row_set.etag, 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')
assert_equals(row_set.tableId, 'syn2976298')
assert_equals(len(row_set.headers), 4)
assert_equals(len(row_set.rows), 4)
schema = Schema(id="syn2976298", name="Bogus Schema", columns=[353, 355, 3020, 891], parent="syn1000001")
table = Table(schema, row_set)
assert_equals(table.etag, 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')
assert_equals(table.tableId, 'syn2976298')
assert_equals(len(table.headers), 4)
assert_equals(len(table.asRowSet().rows), 4)
df = table.asDataFrame()
assert_equals(df.shape, (4, 4))
assert_equals(list(df['name']), ['foo', 'bar', 'foo', 'qux'])
def test_list_of_rows_table():
data = [["John Coltrane", 1926, 8.65, False],
["Miles Davis", 1926, 9.87, False],
["Bill Evans", 1929, 7.65, False],
["Paul Chambers", 1935, 5.14, False],
["Jimmy Cobb", 1929, 5.78, True],
["Scott LaFaro", 1936, 4.21, False],
["Sonny Rollins", 1930, 8.99, True],
["Kenny Burrel", 1931, 4.37, True]]
cols = []
cols.append(Column(id='1', name='Name', columnType='STRING'))
cols.append(Column(id='2', name='Born', columnType='INTEGER'))
cols.append(Column(id='3', name='Hipness', columnType='DOUBLE'))
cols.append(Column(id='4', name='Living', columnType='BOOLEAN'))
schema1 = Schema(name='Jazz Guys', columns=cols, id="syn1000002", parent="syn1000001")
## need columns to do cast_values w/o storing
table = Table(schema1, data, headers=[SelectColumn.from_column(col) for col in cols])
for table_row, expected_row in izip(table, data):
assert table_row==expected_row
rowset = table.asRowSet()
for rowset_row, expected_row in izip(rowset.rows, data):
assert rowset_row['values']==expected_row
table.columns = cols
## test asDataFrame
try:
import pandas as pd
df = table.asDataFrame()
assert all(df['Name'] == [r[0] for r in data])
except ImportError as e1:
sys.stderr.write('Pandas is apparently not installed, skipping asDataFrame portion of test_list_of_rows_table.\n\n')
def test_list_of_rows_table():
data = [["John Coltrane", 1926, 8.65, False],
["Miles Davis", 1926, 9.87, False],
["Bill Evans", 1929, 7.65, False],
["Paul Chambers", 1935, 5.14, False],
["Jimmy Cobb", 1929, 5.78, True],
["Scott LaFaro", 1936, 4.21, False],
["Sonny Rollins", 1930, 8.99, True],
["Kenny Burrel", 1931, 4.37, True]]
cols = [
Column(id='1', name='Name', columnType='STRING'),
Column(id='2', name='Born', columnType='INTEGER'),
Column(id='3', name='Hipness', columnType='DOUBLE'),
Column(id='4', name='Living', columnType='BOOLEAN')
]
schema1 = Schema(name='Jazz Guys',
columns=cols,
id="syn1000002",
parent="syn1000001")
# need columns to do cast_values w/o storing
table = Table(schema1,
data,
headers=[SelectColumn.from_column(col) for col in cols])
for table_row, expected_row in zip(table, data):
assert_equals(table_row, expected_row)
rowset = table.asRowSet()
for rowset_row, expected_row in zip(rowset.rows, data):
assert_equals(rowset_row['values'], expected_row)
table.columns = cols
df = table.asDataFrame()
assert_equals(list(df['Name']), [r[0] for r in data])
def test_csv_table():
## Maybe not truly a unit test, but here because it doesn't do
## network IO to synapse
data = [["1", "1", "John Coltrane", 1926, 8.65, False],
["2", "1", "Miles Davis", 1926, 9.87, False],
["3", "1", "Bill Evans", 1929, 7.65, False],
["4", "1", "Paul Chambers", 1935, 5.14, False],
["5", "1", "Jimmy Cobb", 1929, 5.78, True],
["6", "1", "Scott LaFaro", 1936, 4.21, False],
["7", "1", "Sonny Rollins", 1930, 8.99, True],
["8", "1", "Kenny Burrel", 1931, 4.37, True]]
filename = None
cols = []
cols.append(Column(id='1', name='Name', columnType='STRING'))
cols.append(Column(id='2', name='Born', columnType='INTEGER'))
cols.append(Column(id='3', name='Hipness', columnType='DOUBLE'))
cols.append(Column(id='4', name='Living', columnType='BOOLEAN'))
schema1 = Schema(id='syn1234', name='Jazz Guys', columns=cols, parent="syn1000001")
#TODO: use StringIO.StringIO(data) rather than writing files
try:
## create CSV file
with tempfile.NamedTemporaryFile(delete=False) as temp:
writer = csv.writer(temp, quoting=csv.QUOTE_NONNUMERIC, lineterminator=os.linesep)
writer.writerow(['ROW_ID', 'ROW_VERSION'] + [col.name for col in cols])
filename = temp.name
for row in data:
writer.writerow(row)
table = Table(schema1, filename)
assert isinstance(table, CsvFileTable)
## need to set column headers to read a CSV file
table.setColumnHeaders(
[SelectColumn(name="ROW_ID", columnType="STRING"),
SelectColumn(name="ROW_VERSION", columnType="STRING")] +
[SelectColumn.from_column(col) for col in cols])
## test iterator
# print "\n\nJazz Guys"
for table_row, expected_row in izip(table, data):
# print table_row, expected_row
assert table_row==expected_row
## test asRowSet
rowset = table.asRowSet()
for rowset_row, expected_row in izip(rowset.rows, data):
#print rowset_row, expected_row
assert rowset_row['values']==expected_row[2:]
assert rowset_row['rowId']==expected_row[0]
assert rowset_row['versionNumber']==expected_row[1]
## test asDataFrame
try:
import pandas as pd
df = table.asDataFrame()
assert all(df['Name'] == [row[2] for row in data])
assert all(df['Born'] == [row[3] for row in data])
assert all(df['Living'] == [row[5] for row in data])
assert all(df.index == ['%s_%s'%tuple(row[0:2]) for row in data])
assert df.shape == (8,4)
except ImportError as e1:
sys.stderr.write('Pandas is apparently not installed, skipping asDataFrame portion of test_csv_table.\n\n')
except Exception as ex1:
if filename:
try:
if os.path.isdir(filename):
shutil.rmtree(filename)
else:
os.remove(filename)
except Exception as ex:
print ex
raise
def test_csv_table():
## Maybe not truly a unit test, but here because it doesn't do
## network IO to synapse
data = [["1", "1", "John Coltrane", 1926, 8.65, False],
["2", "1", "Miles Davis", 1926, 9.87, False],
["3", "1", "Bill Evans", 1929, 7.65, False],
["4", "1", "Paul Chambers", 1935, 5.14, False],
["5", "1", "Jimmy Cobb", 1929, 5.78, True],
["6", "1", "Scott LaFaro", 1936, 4.21, False],
["7", "1", "Sonny Rollins", 1930, 8.99, True],
["8", "1", "Kenny Burrel", 1931, 4.37, True]]
filename = None
cols = []
cols.append(Column(id='1', name='Name', columnType='STRING'))
cols.append(Column(id='2', name='Born', columnType='INTEGER'))
cols.append(Column(id='3', name='Hipness', columnType='DOUBLE'))
cols.append(Column(id='4', name='Living', columnType='BOOLEAN'))
schema1 = Schema(id='syn1234',
name='Jazz Guys',
columns=cols,
parent="syn1000001")
#TODO: use StringIO.StringIO(data) rather than writing files
try:
## create CSV file
with tempfile.NamedTemporaryFile(delete=False) as temp:
filename = temp.name
with io.open(filename, mode='w', encoding="utf-8", newline='') as temp:
writer = csv.writer(temp,
quoting=csv.QUOTE_NONNUMERIC,
lineterminator=str(os.linesep))
headers = ['ROW_ID', 'ROW_VERSION'] + [col.name for col in cols]
writer.writerow(headers)
for row in data:
writer.writerow(row)
table = Table(schema1, filename)
assert isinstance(table, CsvFileTable)
## need to set column headers to read a CSV file
table.setColumnHeaders([
SelectColumn(name="ROW_ID", columnType="STRING"),
SelectColumn(name="ROW_VERSION", columnType="STRING")
] + [SelectColumn.from_column(col) for col in cols])
## test iterator
for table_row, expected_row in zip(table, data):
assert table_row == expected_row
## test asRowSet
rowset = table.asRowSet()
for rowset_row, expected_row in zip(rowset.rows, data):
assert rowset_row['values'] == expected_row[2:]
assert rowset_row['rowId'] == expected_row[0]
assert rowset_row['versionNumber'] == expected_row[1]
## test asDataFrame
try:
import pandas as pd
df = table.asDataFrame()
assert all(df['Name'] == [row[2] for row in data])
assert all(df['Born'] == [row[3] for row in data])
assert all(df['Living'] == [row[5] for row in data])
assert all(df.index == ['%s_%s' % tuple(row[0:2]) for row in data])
assert df.shape == (8, 4)
except ImportError as e1:
sys.stderr.write(
'Pandas is apparently not installed, skipping asDataFrame portion of test_csv_table.\n\n'
)
except Exception as ex1:
if filename:
try:
if os.path.isdir(filename):
shutil.rmtree(filename)
else:
os.remove(filename)
except Exception as ex:
print(ex)
raise
def test_RowSetTable():
row_set_json = {
'etag':
'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee',
'headers': [{
'columnType': 'STRING',
'id': '353',
'name': 'name'
}, {
'columnType': 'DOUBLE',
'id': '355',
'name': 'x'
}, {
'columnType': 'DOUBLE',
'id': '3020',
'name': 'y'
}, {
'columnType': 'INTEGER',
'id': '891',
'name': 'n'
}],
'rows': [{
'rowId': 5,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 3
}, {
'rowId': 6,
'values': ['bar', '1.34', '2.4', '101'],
'versionNumber': 3
}, {
'rowId': 7,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 4
}, {
'rowId': 8,
'values': ['qux', '1.23', '2.2', '102'],
'versionNumber': 3
}],
'tableId':
'syn2976298'
}
row_set = RowSet.from_json(row_set_json)
assert row_set.etag == 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'
assert row_set.tableId == 'syn2976298'
assert len(row_set.headers) == 4
assert len(row_set.rows) == 4
schema = Schema(id="syn2976298",
name="Bogus Schema",
columns=[353, 355, 3020, 891],
parent="syn1000001")
table = Table(schema, row_set)
assert table.etag == 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'
assert table.tableId == 'syn2976298'
assert len(table.headers) == 4
assert len(table.asRowSet().rows) == 4
try:
import pandas as pd
df = table.asDataFrame()
assert df.shape == (4, 4)
assert all(df['name'] == ['foo', 'bar', 'foo', 'qux'])
except ImportError as e1:
sys.stderr.write(
'Pandas is apparently not installed, skipping part of test_RowSetTable.\n\n'
)
def test_csv_table():
# Maybe not truly a unit test, but here because it doesn't do
# network IO to synapse
data = [["1", "1", "John Coltrane", 1926, 8.65, False],
["2", "1", "Miles Davis", 1926, 9.87, False],
["3", "1", "Bill Evans", 1929, 7.65, False],
["4", "1", "Paul Chambers", 1935, 5.14, False],
["5", "1", "Jimmy Cobb", 1929, 5.78, True],
["6", "1", "Scott LaFaro", 1936, 4.21, False],
["7", "1", "Sonny Rollins", 1930, 8.99, True],
["8", "1", "Kenny Burrel", 1931, 4.37, True]]
filename = None
cols = [Column(id='1', name='Name', columnType='STRING'),
Column(id='2', name='Born', columnType='INTEGER'),
Column(id='3', name='Hipness', columnType='DOUBLE'),
Column(id='4', name='Living', columnType='BOOLEAN')]
schema1 = Schema(id='syn1234', name='Jazz Guys', columns=cols, parent="syn1000001")
# TODO: use StringIO.StringIO(data) rather than writing files
try:
# create CSV file
with tempfile.NamedTemporaryFile(delete=False) as temp:
filename = temp.name
with io.open(filename, mode='w', encoding="utf-8", newline='') as temp:
writer = csv.writer(temp, quoting=csv.QUOTE_NONNUMERIC, lineterminator=str(os.linesep))
headers = ['ROW_ID', 'ROW_VERSION'] + [col.name for col in cols]
writer.writerow(headers)
for row in data:
writer.writerow(row)
table = Table(schema1, filename)
assert_is_instance(table, CsvFileTable)
# need to set column headers to read a CSV file
table.setColumnHeaders(
[SelectColumn(name="ROW_ID", columnType="STRING"),
SelectColumn(name="ROW_VERSION", columnType="STRING")] +
[SelectColumn.from_column(col) for col in cols])
# test iterator
for table_row, expected_row in zip(table, data):
assert_equals(table_row, expected_row)
# test asRowSet
rowset = table.asRowSet()
for rowset_row, expected_row in zip(rowset.rows, data):
assert_equals(rowset_row['values'], expected_row[2:])
assert_equals(rowset_row['rowId'], expected_row[0])
assert_equals(rowset_row['versionNumber'], expected_row[1])
df = table.asDataFrame()
assert_equals(list(df['Name']), [row[2] for row in data])
assert_equals(list(df['Born']), [row[3] for row in data])
assert_equals(list(df['Living']), [row[5] for row in data])
assert_equals(list(df.index), ['%s_%s' % tuple(row[0:2]) for row in data])
assert_equals(df.shape, (8, 4))
except Exception:
if filename:
try:
if os.path.isdir(filename):
shutil.rmtree(filename)
else:
os.remove(filename)
except Exception as ex:
print(ex)
raise
def test_RowSetTable():
row_set_json = {
'etag':
'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee',
'headers': [{
'columnType': 'STRING',
'id': '353',
'name': 'name'
}, {
'columnType': 'DOUBLE',
'id': '355',
'name': 'x'
}, {
'columnType': 'DOUBLE',
'id': '3020',
'name': 'y'
}, {
'columnType': 'INTEGER',
'id': '891',
'name': 'n'
}],
'rows': [{
'rowId': 5,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 3
}, {
'rowId': 6,
'values': ['bar', '1.34', '2.4', '101'],
'versionNumber': 3
}, {
'rowId': 7,
'values': ['foo', '1.23', '2.2', '101'],
'versionNumber': 4
}, {
'rowId': 8,
'values': ['qux', '1.23', '2.2', '102'],
'versionNumber': 3
}],
'tableId':
'syn2976298'
}
row_set = RowSet.from_json(row_set_json)
assert_equals(row_set.etag, 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')
assert_equals(row_set.tableId, 'syn2976298')
assert_equals(len(row_set.headers), 4)
assert_equals(len(row_set.rows), 4)
schema = Schema(id="syn2976298",
name="Bogus Schema",
columns=[353, 355, 3020, 891],
parent="syn1000001")
table = Table(schema, row_set)
assert_equals(table.etag, 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')
assert_equals(table.tableId, 'syn2976298')
assert_equals(len(table.headers), 4)
assert_equals(len(table.asRowSet().rows), 4)
df = table.asDataFrame()
assert_equals(df.shape, (4, 4))
assert_equals(list(df['name']), ['foo', 'bar', 'foo', 'qux'])
