def printDataGroupedByProjects(data):
if not data.has_key("issue"):
print "data doesn't have key issue"
project = {}
p = Table(
# ['project' , ('issue_id',int) , 'issue_subject','issue']
['project', 'tracker', ('issue_id', int),
'issue_status', 'issue_subject', 'issue_description']
)
for issue in data['issue']:
project_name = issue["project"]["@name"]
issue_id = issue["id"]
issue_status = issue["status"]["@name"]
issue_subject = str((issue["subject"])).strip()
tracker = issue["tracker"]["@name"]
issue_description = issue["description"]
# p.append([project_name,issue_id,issue_subject,issue["description"]])
p.append([project_name, tracker, issue_id, issue_status,
issue_subject, issue_description])
p.to_csv(open("issues.csv", "w"))
class TestExport(unittest.TestCase, TableTestMixin):
def setUp(self):
self.s = [
('A', int),
('B', float),
('C', str),
]
self.t = Table(self.s)
self.t.extend([
[1, 0.0, 'x'],
[2, 5.0, 'y'],
[3, 10.0, 'z'],
])
def test_export_csv(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file)
output_file.seek(0)
reader = csv.DictReader(output_file)
row = next(reader)
self.assertEqual(row, {"A":"1", "B":"0.0", "C":"x"})
def test_export_csv_with_dialect(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file, dialect="excel")
output_file.seek(0)
reader = csv.DictReader(output_file, dialect="excel")
row = next(reader)
self.assertEqual(row, {"A":"1", "B":"0.0", "C":"x"})
def test_export_csv_with_dialect_types(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file, dialect="excel", descriptions=True)
output_file.seek(0)
reader = csv.DictReader(output_file, dialect="excel")
self.assertEqual(next(reader), {"A (int)":"1", "B (float)":"0.0", "C (str)":"x"})
def test_simple_expand(self):
t = self.t.expand(
name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C)
)
self.assertEqual(list(t.D), [1, 1, 1])
def test_derived_columns_are_iterable(self):
t = self.t.expand(
name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C)
)
for _ in t.D:
pass
def test_derived_columns_can_be_printed(self):
t = self.t.expand(
name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C)
)
str(t.D)
repr(t.D)
def test_derived_columns_have_descriptions(self):
t = self.t.expand(
name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C)
)
self.assertEqual(t.D.description, "D (int)")
def test_that_float_columns_have_descriptions(self):
t = self.t.expand(
name='D',
input_columns=['A', 'B', 'C'],
fn=lambda a,b,c: float(len(c) + a + b),
col_type=float
)
self.assertEqual(t.D.description, "D (float)")
def test_simple_expand_and_materialize(self):
t = self.t.expand(
name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C) + 1
).copy()
def test_export_csv_with_dialect_tab(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file, dialect="excel-tab")
output_file.seek(0)
reader = csv.DictReader(output_file, dialect="excel-tab")
row = next(reader)
self.assertEqual(row, {"A":"1", "B":"0.0", "C":"x"})
def test_simple_expand_and_slice(self):
t = self.t.expand(
name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C) + 1
)[1:2]
expected = [
(2, 5.0, 'y', 2),
]
self.assertEqual(list(t), expected)
class TestExport(unittest.TestCase, TableTestMixin):
def setUp(self):
self.s = [
('A', int),
('B', float),
('C', str),
]
self.t = Table(self.s)
self.t.extend([
[1, 0.0, 'x'],
[2, 5.0, 'y'],
[3, 10.0, 'z'],
])
def test_export_csv(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file)
output_file.seek(0)
reader = csv.DictReader(output_file)
row = next(reader)
self.assertEqual(row, {"A": "1", "B": "0.0", "C": "x"})
def test_export_csv_with_dialect(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file, dialect="excel")
output_file.seek(0)
reader = csv.DictReader(output_file, dialect="excel")
row = next(reader)
self.assertEqual(row, {"A": "1", "B": "0.0", "C": "x"})
def test_export_csv_with_dialect_types(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file,
dialect="excel",
descriptions=True)
output_file.seek(0)
reader = csv.DictReader(output_file, dialect="excel")
self.assertEqual(next(reader), {
"A (int)": "1",
"B (float)": "0.0",
"C (str)": "x"
})
def test_simple_expand(self):
t = self.t.expand(name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C))
self.assertEqual(list(t.D), [1, 1, 1])
def test_derived_columns_are_iterable(self):
t = self.t.expand(name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C))
for _ in t.D:
pass
def test_derived_columns_can_be_printed(self):
t = self.t.expand(name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C))
str(t.D)
repr(t.D)
def test_derived_columns_have_descriptions(self):
t = self.t.expand(name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C))
self.assertEqual(t.D.description, "D (int)")
def test_that_float_columns_have_descriptions(self):
t = self.t.expand(name='D',
input_columns=['A', 'B', 'C'],
fn=lambda a, b, c: float(len(c) + a + b),
col_type=float)
self.assertEqual(t.D.description, "D (float)")
def test_simple_expand_and_materialize(self):
t = self.t.expand(name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C) + 1).copy()
def test_export_csv_with_dialect_tab(self):
output_file = StringIO()
self.t.to_csv(output_file=output_file, dialect="excel-tab")
output_file.seek(0)
reader = csv.DictReader(output_file, dialect="excel-tab")
row = next(reader)
self.assertEqual(row, {"A": "1", "B": "0.0", "C": "x"})
def test_simple_expand_and_slice(self):
t = self.t.expand(name='D',
col_type=int,
input_columns=['C'],
fn=lambda C: len(C) + 1)[1:2]
expected = [
(2, 5.0, 'y', 2),
]
self.assertEqual(list(t), expected)
