def test_itervalues():
table = (('foo', 'bar', 'baz'),
('a', 1, True),
('b', 2),
('b', 7, False))
actual = itervalues(table, 'foo')
expect = ('a', 'b', 'b')
ieq(expect, actual)
actual = itervalues(table, 'bar')
expect = (1, 2, 7)
ieq(expect, actual)
actual = itervalues(table, ('foo', 'bar'))
expect = (('a', 1), ('b', 2), ('b', 7))
ieq(expect, actual)
actual = itervalues(table, 'baz')
expect = (True, None, False)
ieq(expect, actual)
actual = itervalues(table, ('foo', 'baz'))
expect = (('a', True), ('b', None), ('b', False))
ieq(expect, actual)
def isunique(table, field):
"""
Return True if there are no duplicate values for the given field(s),
otherwise False. E.g.::
>>> import petl as etl
>>> table1 = [['foo', 'bar'],
... ['a', 1],
... ['b'],
... ['b', 2],
... ['c', 3, True]]
>>> etl.isunique(table1, 'foo')
False
>>> etl.isunique(table1, 'bar')
True
The `field` argument can be a single field name or index (starting from
zero) or a tuple of field names and/or indexes.
"""
vals = set()
for v in itervalues(table, field):
if v in vals:
return False
else:
vals.add(v)
return True
def isunique(table, field):
"""
Return True if there are no duplicate values for the given field(s),
otherwise False. E.g.::
>>> import petl as etl
>>> table1 = [['foo', 'bar'],
... ['a', 1],
... ['b'],
... ['b', 2],
... ['c', 3, True]]
>>> etl.isunique(table1, 'foo')
False
>>> etl.isunique(table1, 'bar')
True
The `field` argument can be a single field name or index (starting from
zero) or a tuple of field names and/or indexes.
"""
vals = set()
for v in itervalues(table, field):
if v in vals:
return False
else:
vals.add(v)
return True
def test_itervalues():
table = (('foo', 'bar', 'baz'), ('a', 1, True), ('b', 2), ('b', 7, False))
actual = itervalues(table, 'foo')
expect = ('a', 'b', 'b')
ieq(expect, actual)
actual = itervalues(table, 'bar')
expect = (1, 2, 7)
ieq(expect, actual)
actual = itervalues(table, ('foo', 'bar'))
expect = (('a', 1), ('b', 2), ('b', 7))
ieq(expect, actual)
actual = itervalues(table, 'baz')
expect = (True, None, False)
ieq(expect, actual)
actual = itervalues(table, ('foo', 'baz'))
expect = (('a', True), ('b', None), ('b', False))
ieq(expect, actual)
def iterpivot(source, f1, f2, f3, aggfun, missing):
# first pass - collect fields
f2vals = set(itervalues(source, f2)) # TODO only make one pass
f2vals = list(f2vals)
f2vals.sort()
outhdr = [f1]
outhdr.extend(f2vals)
yield tuple(outhdr)
# second pass - generate output
it = iter(source)
hdr = next(it)
flds = list(map(text_type, hdr))
f1i = flds.index(f1)
f2i = flds.index(f2)
f3i = flds.index(f3)
for v1, v1rows in itertools.groupby(it, key=operator.itemgetter(f1i)):
outrow = [v1] + [missing] * len(f2vals)
for v2, v12rows in itertools.groupby(v1rows,
key=operator.itemgetter(f2i)):
aggval = aggfun([row[f3i] for row in v12rows])
outrow[1 + f2vals.index(v2)] = aggval
yield tuple(outrow)