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from __future__ import absolute_import
from distutils.version import LooseVersion
import os
import pytest
from pandas import DataFrame, read_parquet as pd_read_parquet
from pandas.testing import assert_frame_equal
import numpy as np
import geopandas
from geopandas import GeoDataFrame, read_file, read_parquet, read_feather
from geopandas.array import to_wkb
from geopandas.datasets import get_path
from geopandas.io.arrow import (
_create_metadata,
_decode_metadata,
_encode_metadata,
_encode_wkb,
_validate_dataframe,
_validate_metadata,
METADATA_VERSION,
)
from geopandas.testing import assert_geodataframe_equal, assert_geoseries_equal
# Skip all tests in this module if pyarrow is not available
pyarrow = pytest.importorskip("pyarrow")
# TEMPORARY: hide warning from to_parquet
pytestmark = pytest.mark.filterwarnings("ignore:.*initial implementation of Parquet.*")
@pytest.fixture(
params=[
"parquet",
pytest.param(
"feather",
marks=pytest.mark.skipif(
pyarrow.__version__ < LooseVersion("0.17.0"),
reason="needs pyarrow >= 0.17",
),
),
]
)
def file_format(request):
if request.param == "parquet":
return read_parquet, GeoDataFrame.to_parquet
elif request.param == "feather":
return read_feather, GeoDataFrame.to_feather
def test_create_metadata():
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
metadata = _create_metadata(df)
assert isinstance(metadata, dict)
assert metadata["schema_version"] == METADATA_VERSION
assert metadata["creator"]["library"] == "geopandas"
assert metadata["creator"]["version"] == geopandas.__version__
assert metadata["primary_column"] == "geometry"
assert "geometry" in metadata["columns"]
assert metadata["columns"]["geometry"]["crs"] == df.geometry.crs.to_wkt()
assert metadata["columns"]["geometry"]["encoding"] == "WKB"
assert np.array_equal(
metadata["columns"]["geometry"]["bbox"], df.geometry.total_bounds
)
def test_encode_metadata():
metadata = {"a": "b"}
expected = b'{"a": "b"}'
assert _encode_metadata(metadata) == expected
def test_decode_metadata():
metadata_str = b'{"a": "b"}'
expected = {"a": "b"}
assert _decode_metadata(metadata_str) == expected
def test_validate_dataframe():
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
# valid: should not raise ValueError
_validate_dataframe(df)
_validate_dataframe(df.set_index("iso_a3"))
# add column with non-string type
df[0] = 1
# invalid: should raise ValueError
with pytest.raises(ValueError):
_validate_dataframe(df)
with pytest.raises(ValueError):
_validate_dataframe(df.set_index(0))
# not a DataFrame: should raise ValueError
with pytest.raises(ValueError):
_validate_dataframe("not a dataframe")
def test_validate_metadata_valid():
_validate_metadata(
{
"primary_column": "geometry",
"columns": {"geometry": {"crs": None, "encoding": "WKB"}},
}
)
_validate_metadata(
{
"primary_column": "geometry",
"columns": {"geometry": {"crs": "WKT goes here", "encoding": "WKB"}},
}
)
@pytest.mark.parametrize(
"metadata,error",
[
({}, "Missing or malformed geo metadata in Parquet/Feather file"),
(
{"primary_column": "foo"},
"'geo' metadata in Parquet/Feather file is missing required key:",
),
(
{"primary_column": "foo", "columns": None},
"'geo' metadata in Parquet/Feather file is missing required key",
),
(
{"primary_column": "foo", "columns": []},
"'columns' in 'geo' metadata must be a dict",
),
(
{"primary_column": "foo", "columns": {"foo": {}}},
(
"'geo' metadata in Parquet/Feather file is missing required key 'crs' "
"for column 'foo'"
),
),
(
{"primary_column": "foo", "columns": {"foo": {"crs": None}}},
"'geo' metadata in Parquet/Feather file is missing required key",
),
(
{"primary_column": "foo", "columns": {"foo": {"encoding": None}}},
"'geo' metadata in Parquet/Feather file is missing required key",
),
(
{
"primary_column": "foo",
"columns": {"foo": {"crs": None, "encoding": None}},
},
"Only WKB geometry encoding is supported",
),
(
{
"primary_column": "foo",
"columns": {"foo": {"crs": None, "encoding": "BKW"}},
},
"Only WKB geometry encoding is supported",
),
],
)
def test_validate_metadata_invalid(metadata, error):
with pytest.raises(ValueError, match=error):
_validate_metadata(metadata)
def test_encode_wkb():
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
encoded = _encode_wkb(df)
# make sure original is not modified
assert isinstance(df, GeoDataFrame)
assert (
encoded.geometry.iloc[0][:16]
== b"\x01\x06\x00\x00\x00\x03\x00\x00\x00\x01\x03\x00\x00\x00\x01\x00"
)
# TEMPORARY: used to determine if pyarrow fails for roundtripping pandas data
# without geometries
def test_pandas_parquet_roundtrip1(tmpdir):
df = DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
filename = os.path.join(str(tmpdir), "test.pq")
df.to_parquet(filename)
pq_df = pd_read_parquet(filename)
assert_frame_equal(df, pq_df)
@pytest.mark.parametrize(
"test_dataset", ["naturalearth_lowres", "naturalearth_cities", "nybb"]
)
def test_pandas_parquet_roundtrip2(test_dataset, tmpdir):
test_dataset = "naturalearth_lowres"
df = DataFrame(read_file(get_path(test_dataset)).drop(columns=["geometry"]))
filename = os.path.join(str(tmpdir), "test.pq")
df.to_parquet(filename)
pq_df = pd_read_parquet(filename)
assert_frame_equal(df, pq_df)
@pytest.mark.parametrize(
"test_dataset", ["naturalearth_lowres", "naturalearth_cities", "nybb"]
)
def test_roundtrip(tmpdir, file_format, test_dataset):
"""Writing to parquet should not raise errors, and should not alter original
GeoDataFrame
"""
reader, writer = file_format
df = read_file(get_path(test_dataset))
orig = df.copy()
filename = os.path.join(str(tmpdir), "test.pq")
# TEMP: Initial implementation should raise a UserWarning
with pytest.warns(UserWarning, match="initial implementation"):
writer(df, filename)
assert os.path.exists(filename)
# make sure that the original data frame is unaltered
assert_geodataframe_equal(df, orig)
# make sure that we can roundtrip the data frame
pq_df = reader(filename)
assert isinstance(pq_df, GeoDataFrame)
assert_geodataframe_equal(df, pq_df)
def test_index(tmpdir, file_format):
"""Setting index=`True` should preserve index in output, and
setting index=`False` should drop index from output.
"""
reader, writer = file_format
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset)).set_index("iso_a3")
filename = os.path.join(str(tmpdir), "test_with_index.pq")
writer(df, filename, index=True)
pq_df = reader(filename)
assert_geodataframe_equal(df, pq_df)
filename = os.path.join(str(tmpdir), "drop_index.pq")
writer(df, filename, index=False)
pq_df = reader(filename)
assert_geodataframe_equal(df.reset_index(drop=True), pq_df)
@pytest.mark.parametrize("compression", ["snappy", "gzip", "brotli", None])
def test_parquet_compression(compression, tmpdir):
"""Using compression options should not raise errors, and should
return identical GeoDataFrame.
"""
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
filename = os.path.join(str(tmpdir), "test.pq")
df.to_parquet(filename, compression=compression)
pq_df = read_parquet(filename)
assert isinstance(pq_df, GeoDataFrame)
assert_geodataframe_equal(df, pq_df)
@pytest.mark.skipif(
pyarrow.__version__ < LooseVersion("0.17.0"),
reason="Feather only supported for pyarrow >= 0.17",
)
@pytest.mark.parametrize("compression", ["uncompressed", "lz4", "zstd"])
def test_feather_compression(compression, tmpdir):
"""Using compression options should not raise errors, and should
return identical GeoDataFrame.
"""
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
filename = os.path.join(str(tmpdir), "test.feather")
df.to_feather(filename, compression=compression)
pq_df = read_feather(filename)
assert isinstance(pq_df, GeoDataFrame)
assert_geodataframe_equal(df, pq_df)
def test_parquet_multiple_geom_cols(tmpdir, file_format):
"""If multiple geometry columns are present when written to parquet,
they should all be returned as such when read from parquet.
"""
reader, writer = file_format
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
df["geom2"] = df.geometry.copy()
filename = os.path.join(str(tmpdir), "test.pq")
writer(df, filename)
assert os.path.exists(filename)
pq_df = reader(filename)
assert isinstance(pq_df, GeoDataFrame)
assert_geodataframe_equal(df, pq_df)
assert_geoseries_equal(df.geom2, pq_df.geom2, check_geom_type=True)
def test_parquet_missing_metadata(tmpdir):
"""Missing geo metadata, such as from a parquet file created
from a pandas DataFrame, will raise a ValueError.
"""
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
# convert to DataFrame
df = DataFrame(df)
# convert the geometry column so we can extract later
df["geometry"] = to_wkb(df["geometry"].values)
filename = os.path.join(str(tmpdir), "test.pq")
# use pandas to_parquet (no geo metadata)
df.to_parquet(filename)
# missing metadata will raise ValueError
with pytest.raises(
ValueError, match="Missing geo metadata in Parquet/Feather file."
):
read_parquet(filename)
@pytest.mark.parametrize(
"geo_meta,error",
[
({"geo": b""}, "Missing or malformed geo metadata in Parquet/Feather file"),
(
{"geo": _encode_metadata({})},
"Missing or malformed geo metadata in Parquet/Feather file",
),
(
{"geo": _encode_metadata({"foo": "bar"})},
"'geo' metadata in Parquet/Feather file is missing required key",
),
],
)
def test_parquet_invalid_metadata(tmpdir, geo_meta, error):
"""Has geo metadata with missing required fields will raise a ValueError.
This requires writing the parquet file directly below, so that we can
control the metadata that is written for this test.
"""
from pyarrow import parquet, Table
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
# convert to DataFrame and encode geometry to WKB
df = DataFrame(df)
df["geometry"] = to_wkb(df["geometry"].values)
table = Table.from_pandas(df)
metadata = table.schema.metadata
metadata.update(geo_meta)
table = table.replace_schema_metadata(metadata)
filename = os.path.join(str(tmpdir), "test.pq")
parquet.write_table(table, filename)
with pytest.raises(ValueError, match=error):
read_parquet(filename)
def test_subset_columns(tmpdir, file_format):
"""Reading a subset of columns should correctly decode selected geometry
columns.
"""
reader, writer = file_format
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
filename = os.path.join(str(tmpdir), "test.pq")
writer(df, filename)
pq_df = reader(filename, columns=["name", "geometry"])
assert_geodataframe_equal(df[["name", "geometry"]], pq_df)
with pytest.raises(
ValueError, match="No geometry columns are included in the columns read"
):
reader(filename, columns=["name"])
def test_parquet_repeat_columns(tmpdir):
"""Reading repeated columns should return first value of each repeated column
"""
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
filename = os.path.join(str(tmpdir), "test.pq")
df.to_parquet(filename)
columns = ["name", "name", "iso_a3", "name", "geometry"]
pq_df = read_parquet(filename, columns=columns)
assert pq_df.columns.tolist() == ["name", "iso_a3", "geometry"]
def test_promote_secondary_geometry(tmpdir, file_format):
"""Reading a subset of columns that does not include the primary geometry
column should promote the first geometry column present.
"""
reader, writer = file_format
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
df["geom2"] = df.geometry.copy()
filename = os.path.join(str(tmpdir), "test.pq")
writer(df, filename)
pq_df = reader(filename, columns=["name", "geom2"])
assert_geodataframe_equal(df.set_geometry("geom2")[["name", "geom2"]], pq_df)
df["geom3"] = df.geometry.copy()
writer(df, filename)
with pytest.warns(
UserWarning,
match="Multiple non-primary geometry columns read from Parquet/Feather file.",
):
pq_df = reader(filename, columns=["name", "geom2", "geom3"])
assert_geodataframe_equal(
df.set_geometry("geom2")[["name", "geom2", "geom3"]], pq_df
)
def test_columns_no_geometry(tmpdir, file_format):
"""Reading a parquet file that is missing all of the geometry columns
should raise a ValueError"""
reader, writer = file_format
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
filename = os.path.join(str(tmpdir), "test.pq")
writer(df, filename)
with pytest.raises(ValueError):
reader(filename, columns=["name"])
def test_missing_crs(tmpdir, file_format):
"""If CRS is `None`, it should be properly handled
and remain `None` when read from parquet`.
"""
reader, writer = file_format
test_dataset = "naturalearth_lowres"
df = read_file(get_path(test_dataset))
df.crs = None
filename = os.path.join(str(tmpdir), "test.pq")
writer(df, filename)
pq_df = reader(filename)
assert pq_df.crs is None
assert_geodataframe_equal(df, pq_df, check_crs=True)
@pytest.mark.skipif(
pyarrow.__version__ >= LooseVersion("0.17.0"),
reason="Feather only supported for pyarrow >= 0.17",
)
def test_feather_arrow_version(tmpdir):
df = read_file(get_path("naturalearth_lowres"))
filename = os.path.join(str(tmpdir), "test.feather")
with pytest.raises(
ImportError, match="pyarrow >= 0.17 required for Feather support"
):
df.to_feather(filename)
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