def make_pdf():
pdf = PanDatFactory(data_table = [["a"], ["b", "c"]],
parameters = [["a"], ["b"]])
pdf.add_parameter("Something", 100, max=100, inclusive_max=True)
pdf.add_parameter("Another thing", 5, must_be_int=True)
pdf.add_parameter("Untyped thing", "whatever", enforce_type_rules=False)
pdf.add_parameter("Last", 'boo', number_allowed=False, strings_allowed='*')
return PanDatFactory.create_from_full_schema(pdf.schema(True))
def test_fk_max_failures(self):
tdf = TicDatFactory(**dietSchema())
addDietForeignKeys(tdf)
dat = tdf.TicDat(nutritionQuantities=[[f"food_{_}", f"cat_{_}", 10]
for _ in range(10)])
pan_dat = tdf.copy_to_pandas(dat, drop_pk_columns=False)
pdf = PanDatFactory.create_from_full_schema(
tdf.schema(include_ancillary_info=True))
errs = pdf.find_foreign_key_failures(pan_dat)
self.assertTrue(
len(errs) == 2 and all(len(_) == 10 for _ in errs.values()))
errs = pdf.find_foreign_key_failures(pan_dat, max_failures=11)
self.assertTrue(
len(errs) == 2 and set(map(len, errs.values())) == {10, 1})
errs = pdf.find_foreign_key_failures(pan_dat, max_failures=10)
self.assertTrue(
len(errs) == 1 and all(len(_) == 10 for _ in errs.values()))
errs = pdf.find_foreign_key_failures(pan_dat, max_failures=9)
self.assertTrue(
len(errs) == 1 and all(len(_) == 9 for _ in errs.values()))
def testRoundTrips(self):
if not self.canRun:
return
tdf = TicDatFactory(**dietSchema())
tdf.enable_foreign_key_links()
oldDat = tdf.freeze_me(
tdf.TicDat(
**{t: getattr(dietData(), t)
for t in tdf.primary_key_fields}))
pdf = PanDatFactory.create_from_full_schema(
tdf.schema(include_ancillary_info=True))
pan_dat = tdf.copy_to_pandas(oldDat, drop_pk_columns=False)
self.assertTrue(pdf.good_pan_dat_object(pan_dat))
tic_dat = pdf.copy_to_tic_dat(pan_dat)
self.assertTrue(tdf._same_data(oldDat, tic_dat))
tdf = TicDatFactory(**netflowSchema())
tdf.enable_foreign_key_links()
addNetflowForeignKeys(tdf)
oldDat = tdf.freeze_me(
tdf.TicDat(
**
{t: getattr(netflowData(), t)
for t in tdf.primary_key_fields}))
pdf = PanDatFactory.create_from_full_schema(
tdf.schema(include_ancillary_info=True))
pan_dat = tdf.copy_to_pandas(oldDat, drop_pk_columns=False)
self.assertTrue(pdf.good_pan_dat_object(pan_dat))
tic_dat = pdf.copy_to_tic_dat(pan_dat)
self.assertTrue(tdf._same_data(oldDat, tic_dat))
pdf = PanDatFactory(table=[["a", "b"], ["c"]])
pan_dat = pdf.PanDat(table=utils.DataFrame({
"a": [1, 2, 1, 1],
"b": [10, 10, 10, 11],
"c": [101, 102, 103, 104]
}))
self.assertTrue(
len(pdf.find_duplicates(pan_dat, keep=False)["table"]) == 2)
tic_dat = pdf.copy_to_tic_dat(pan_dat)
self.assertTrue(len(tic_dat.table) == len(pan_dat.table) - 1)
tdf = TicDatFactory(**pdf.schema())
tic_dat = tdf.TicDat(table=[[1, 2, 3], [None, 2, 3], [2, 1, None]])
self.assertTrue(len(tic_dat.table) == 3)
tic_dat_two = pdf.copy_to_tic_dat(
tdf.copy_to_pandas(tic_dat, drop_pk_columns=False))
self.assertFalse(tdf._same_data(tic_dat, tic_dat_two))
tic_dat3 = tdf.TicDat(
table=[[1, 2, 3], [float("nan"), 2, 3], [2, 1, float("nan")]])
# this fails because _same_data isn't smart enough to check against nan in the keys,
# because float("nan") != float("nan")
self.assertFalse(tdf._same_data(tic_dat3, tic_dat_two))
pdf = PanDatFactory(table=[["a"], ["b", "c"]])
tdf = TicDatFactory(**pdf.schema())
tic_dat = tdf.TicDat(table=[[1, 2, 3], [2, None, 3], [2, 1, None]])
tic_dat_two = pdf.copy_to_tic_dat(
tdf.copy_to_pandas(tic_dat, drop_pk_columns=False))
self.assertFalse(tdf._same_data(tic_dat, tic_dat_two))
tic_dat3 = tdf.TicDat(
table=[[1, 2, 3], [2, float("nan"), 3], [2, 1, float("nan")]])
# _same_data works fine in checking nan equivalence in data rows - which maybe
self.assertTrue(
tdf._same_data(tic_dat3,
tic_dat_two,
nans_are_same_for_data_rows=True))
