def test_err1(self):
s = copy.copy(schema)
s["PUMS.PUMS"]["income"].upper = None
reader = PandasReader(df, s)
private_reader = PrivateReader(reader, s, privacy=Privacy(epsilon=4.0))
with pytest.raises(ValueError):
rs = private_reader.execute_df("SELECT SUM(income) FROM PUMS.PUMS")
def test_ok1(self):
s = copy.copy(schema)
s["PUMS.PUMS"]["income"].upper = None
reader = PandasReader(df, s)
private_reader = PrivateReader(reader, s, privacy=Privacy(epsilon=4.0))
rs = private_reader.execute_df(
"SELECT income FROM PUMS.PUMS GROUP BY income")
def test_dpsu_vs_korolova(self):
query = "SELECT ngram, COUNT(*) as n FROM reddit.reddit GROUP BY ngram ORDER BY n desc"
reader = PandasReader(df, schema)
private_reader = PrivateReader(reader,
schema,
privacy=Privacy(epsilon=3.0))
private_reader.options.max_contrib = 10
result = private_reader.execute_df(query)
private_reader_korolova = PrivateReader(reader,
schema,
privacy=Privacy(epsilon=3.0))
private_reader_korolova.options.dpsu = False
private_reader_korolova.options.max_contrib = 10
korolova_result = private_reader_korolova.execute_df(query)
assert len(result['n']) > len(korolova_result['n'])
assert len(final_df) < len(df)
def test_sum_noisy_postprocess(self):
reader = PandasReader(df, schema)
private_reader = PrivateReader(reader, schema, privacy=Privacy(epsilon=1.0))
trs = private_reader.execute_df("SELECT POWER(SUM(age), 2) as age_total FROM PUMS.PUMS")
assert(trs['age_total'][0] > 1000 ** 2)
def test_group_by_noisy_typed_order_desc(self):
reader = PandasReader(df, schema)
private_reader = PrivateReader(reader, schema, privacy=Privacy(epsilon=4.0))
rs = private_reader.execute_df("SELECT COUNT(*) AS c, married AS m FROM PUMS.PUMS GROUP BY married ORDER BY c DESC")
assert(rs['c'][0] > rs['c'][1])
