def test_coerce_infer_columns_format_supercedes_try_fallback_columns(self):
table = pd.DataFrame({"A": [1, 2]})
result = ProcessResult.coerce(
{"dataframe": table, "column_formats": {"A": "{:,d}"}},
try_fallback_columns=[Column("A", ColumnType.Number("{:,.2f}"))],
)
self.assertEqual(result.columns, [Column("A", ColumnType.Number("{:,d}"))])
def test_arrow_uint8_column(self):
dataframe, columns = arrow_table_to_dataframe(
arrow_table(
{"A": pyarrow.array([1, 2, 3, 253], type=pyarrow.uint8())},
columns=[atypes.Column("A", ColumnType.Number("{:,d}"))],
))
assert_frame_equal(dataframe,
pd.DataFrame({"A": [1, 2, 3, 253]}, dtype=np.uint8))
self.assertEqual(columns, [Column("A", ColumnType.Number("{:,d}"))])
def test_dataframe_uint8_column(self):
assert_arrow_table_equals(
dataframe_to_arrow_table(
pd.DataFrame({"A": [1, 2, 3, 253]}, dtype=np.uint8),
[Column("A", ColumnType.Number("{:,d}"))],
self.path,
),
arrow_table(
{"A": pyarrow.array([1, 2, 3, 253], type=pyarrow.uint8())},
[atypes.Column("A", ColumnType.Number("{:,d}"))],
),
)
def test_coerce_infer_columns_try_fallback_columns_ignore_wrong_type(self):
table = pd.DataFrame({"A": [1, 2], "B": ["x", "y"]})
result = ProcessResult.coerce(
table,
try_fallback_columns=[
Column("A", ColumnType.Text()),
Column("B", ColumnType.Number()),
],
)
self.assertEqual(
result.columns,
[Column("A", ColumnType.Number()), Column("B", ColumnType.Text())],
)
def test_coerce_infer_columns(self):
table = pd.DataFrame({"A": [1, 2], "B": ["x", "y"]})
result = ProcessResult.coerce(table)
self.assertEqual(
result.columns,
[Column("A", ColumnType.Number()), Column("B", ColumnType.Text())],
)
def test_to_arrow_normal_dataframe(self):
fd, filename = tempfile.mkstemp()
os.close(fd)
# Remove the file. Then we'll test that ProcessResult.to_arrow() does
# not write it (because the result is an error)
os.unlink(filename)
try:
process_result = ProcessResult.coerce(pd.DataFrame({"A": [1, 2]}))
result = process_result.to_arrow(Path(filename))
self.assertEqual(
result,
atypes.RenderResult(
atypes.ArrowTable(
Path(filename),
pyarrow.table({"A": [1, 2]}),
atypes.TableMetadata(
2,
[
atypes.Column(
"A",
ColumnType.Number(
# Whatever .format
# ProcessResult.coerce() gave
process_result.columns[0].type.format),
)
],
),
),
[],
{},
),
)
finally:
os.unlink(filename)
def test_dataframe_uint8_column(self):
self._test_dataframe_to_arrow_table(
pd.DataFrame({"A": [1, 2, 3, 253]}, dtype=np.uint8),
[Column("A", ColumnType.Number("{:,d}"))],
make_table(
make_column("A", [1, 2, 3, 253], type=pa.uint8(), format="{:,d}")
),
)
def test_coerce_infer_columns_with_format(self):
table = pd.DataFrame({"A": [1, 2], "B": ["x", "y"]})
result = ProcessResult.coerce(
{"dataframe": table, "column_formats": {"A": "{:,d}"}}
)
self.assertEqual(
result.columns,
[
Column("A", ColumnType.Number(format="{:,d}")),
Column("B", ColumnType.Text()),
],
)
def test_ctor_infer_columns(self):
result = ProcessResult(
pd.DataFrame({
"A": [1, 2],
"B": ["x", "y"],
"C": [np.nan, dt(2019, 3, 3, 4, 5, 6, 7)],
}))
self.assertEqual(
result.columns,
[
Column("A", ColumnType.Number()),
Column("B", ColumnType.Text()),
Column("C", ColumnType.Timestamp()),
],
)
def test_columns(self):
df = pd.DataFrame({
"A": [1], # number
"B": ["foo"], # str
"C": dt(2018, 8, 20), # datetime64
})
df["D"] = pd.Series(["cat"], dtype="category")
result = ProcessResult(df)
self.assertEqual(result.column_names, ["A", "B", "C", "D"])
self.assertEqual(
result.columns,
[
Column("A", ColumnType.Number()),
Column("B", ColumnType.Text()),
Column("C", ColumnType.Timestamp()),
Column("D", ColumnType.Text()),
],
)
def test_ctor_infer_columns(self):
result = ProcessResult(
pd.DataFrame(
{
"A": [1, 2],
"B": ["x", "y"],
"C": [np.nan, dt(2019, 3, 3, 4, 5, 6, 7)],
"D": [pd.Period("2021-01-01", freq="D"), pd.NaT],
}
)
)
self.assertEqual(
result.columns,
[
Column("A", ColumnType.Number()),
Column("B", ColumnType.Text()),
Column("C", ColumnType.Timestamp()),
Column("D", ColumnType.Date("day")),
],
)
def test_table_metadata(self):
df = pd.DataFrame({"A": [1, 2, 3]})
result = ProcessResult(df)
self.assertEqual(result.table_metadata,
TableMetadata(3, [Column("A", ColumnType.Number())]))
