mirror of
https://github.com/aykhans/AzSuicideDataVisualization.git
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414 lines
13 KiB
Python
414 lines
13 KiB
Python
# -*- coding: utf-8 -*-
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import gc
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import pyarrow as pa
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try:
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from pyarrow.cffi import ffi
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except ImportError:
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ffi = None
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import pytest
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try:
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import pandas as pd
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import pandas.testing as tm
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except ImportError:
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pd = tm = None
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needs_cffi = pytest.mark.skipif(ffi is None,
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reason="test needs cffi package installed")
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assert_schema_released = pytest.raises(
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ValueError, match="Cannot import released ArrowSchema")
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assert_array_released = pytest.raises(
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ValueError, match="Cannot import released ArrowArray")
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assert_stream_released = pytest.raises(
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ValueError, match="Cannot import released ArrowArrayStream")
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class ParamExtType(pa.PyExtensionType):
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def __init__(self, width):
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self._width = width
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pa.PyExtensionType.__init__(self, pa.binary(width))
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@property
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def width(self):
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return self._width
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def __reduce__(self):
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return ParamExtType, (self.width,)
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def make_schema():
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return pa.schema([('ints', pa.list_(pa.int32()))],
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metadata={b'key1': b'value1'})
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def make_extension_schema():
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return pa.schema([('ext', ParamExtType(3))],
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metadata={b'key1': b'value1'})
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def make_batch():
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return pa.record_batch([[[1], [2, 42]]], make_schema())
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def make_extension_batch():
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schema = make_extension_schema()
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ext_col = schema[0].type.wrap_array(pa.array([b"foo", b"bar"],
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type=pa.binary(3)))
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return pa.record_batch([ext_col], schema)
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def make_batches():
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schema = make_schema()
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return [
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pa.record_batch([[[1], [2, 42]]], schema),
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pa.record_batch([[None, [], [5, 6]]], schema),
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]
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def make_serialized(schema, batches):
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with pa.BufferOutputStream() as sink:
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with pa.ipc.new_stream(sink, schema) as out:
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for batch in batches:
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out.write(batch)
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return sink.getvalue()
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@needs_cffi
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def test_export_import_type():
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c_schema = ffi.new("struct ArrowSchema*")
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ptr_schema = int(ffi.cast("uintptr_t", c_schema))
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gc.collect() # Make sure no Arrow data dangles in a ref cycle
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old_allocated = pa.total_allocated_bytes()
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typ = pa.list_(pa.int32())
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typ._export_to_c(ptr_schema)
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assert pa.total_allocated_bytes() > old_allocated
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# Delete and recreate C++ object from exported pointer
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del typ
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assert pa.total_allocated_bytes() > old_allocated
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typ_new = pa.DataType._import_from_c(ptr_schema)
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assert typ_new == pa.list_(pa.int32())
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_schema_released:
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pa.DataType._import_from_c(ptr_schema)
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# Invalid format string
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pa.int32()._export_to_c(ptr_schema)
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bad_format = ffi.new("char[]", b"zzz")
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c_schema.format = bad_format
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with pytest.raises(ValueError,
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match="Invalid or unsupported format string"):
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pa.DataType._import_from_c(ptr_schema)
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# Now released
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with assert_schema_released:
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pa.DataType._import_from_c(ptr_schema)
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@needs_cffi
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def test_export_import_field():
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c_schema = ffi.new("struct ArrowSchema*")
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ptr_schema = int(ffi.cast("uintptr_t", c_schema))
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gc.collect() # Make sure no Arrow data dangles in a ref cycle
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old_allocated = pa.total_allocated_bytes()
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field = pa.field("test", pa.list_(pa.int32()), nullable=True)
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field._export_to_c(ptr_schema)
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assert pa.total_allocated_bytes() > old_allocated
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# Delete and recreate C++ object from exported pointer
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del field
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assert pa.total_allocated_bytes() > old_allocated
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field_new = pa.Field._import_from_c(ptr_schema)
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assert field_new == pa.field("test", pa.list_(pa.int32()), nullable=True)
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_schema_released:
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pa.Field._import_from_c(ptr_schema)
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@needs_cffi
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def test_export_import_array():
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c_schema = ffi.new("struct ArrowSchema*")
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ptr_schema = int(ffi.cast("uintptr_t", c_schema))
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c_array = ffi.new("struct ArrowArray*")
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ptr_array = int(ffi.cast("uintptr_t", c_array))
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gc.collect() # Make sure no Arrow data dangles in a ref cycle
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old_allocated = pa.total_allocated_bytes()
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# Type is known up front
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typ = pa.list_(pa.int32())
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arr = pa.array([[1], [2, 42]], type=typ)
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py_value = arr.to_pylist()
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arr._export_to_c(ptr_array)
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assert pa.total_allocated_bytes() > old_allocated
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# Delete recreate C++ object from exported pointer
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del arr
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arr_new = pa.Array._import_from_c(ptr_array, typ)
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assert arr_new.to_pylist() == py_value
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assert arr_new.type == pa.list_(pa.int32())
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assert pa.total_allocated_bytes() > old_allocated
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del arr_new, typ
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_array_released:
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pa.Array._import_from_c(ptr_array, pa.list_(pa.int32()))
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# Type is exported and imported at the same time
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arr = pa.array([[1], [2, 42]], type=pa.list_(pa.int32()))
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py_value = arr.to_pylist()
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arr._export_to_c(ptr_array, ptr_schema)
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# Delete and recreate C++ objects from exported pointers
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del arr
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arr_new = pa.Array._import_from_c(ptr_array, ptr_schema)
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assert arr_new.to_pylist() == py_value
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assert arr_new.type == pa.list_(pa.int32())
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assert pa.total_allocated_bytes() > old_allocated
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del arr_new
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_schema_released:
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pa.Array._import_from_c(ptr_array, ptr_schema)
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def check_export_import_schema(schema_factory):
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c_schema = ffi.new("struct ArrowSchema*")
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ptr_schema = int(ffi.cast("uintptr_t", c_schema))
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gc.collect() # Make sure no Arrow data dangles in a ref cycle
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old_allocated = pa.total_allocated_bytes()
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schema_factory()._export_to_c(ptr_schema)
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assert pa.total_allocated_bytes() > old_allocated
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# Delete and recreate C++ object from exported pointer
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schema_new = pa.Schema._import_from_c(ptr_schema)
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assert schema_new == schema_factory()
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assert pa.total_allocated_bytes() == old_allocated
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del schema_new
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_schema_released:
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pa.Schema._import_from_c(ptr_schema)
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# Not a struct type
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pa.int32()._export_to_c(ptr_schema)
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with pytest.raises(ValueError,
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match="ArrowSchema describes non-struct type"):
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pa.Schema._import_from_c(ptr_schema)
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# Now released
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with assert_schema_released:
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pa.Schema._import_from_c(ptr_schema)
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@needs_cffi
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def test_export_import_schema():
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check_export_import_schema(make_schema)
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@needs_cffi
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def test_export_import_schema_with_extension():
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check_export_import_schema(make_extension_schema)
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@needs_cffi
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def test_export_import_schema_float_pointer():
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# Previous versions of the R Arrow library used to pass pointer
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# values as a double.
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c_schema = ffi.new("struct ArrowSchema*")
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ptr_schema = int(ffi.cast("uintptr_t", c_schema))
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match = "Passing a pointer value as a float is unsafe"
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with pytest.warns(UserWarning, match=match):
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make_schema()._export_to_c(float(ptr_schema))
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with pytest.warns(UserWarning, match=match):
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schema_new = pa.Schema._import_from_c(float(ptr_schema))
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assert schema_new == make_schema()
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def check_export_import_batch(batch_factory):
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c_schema = ffi.new("struct ArrowSchema*")
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ptr_schema = int(ffi.cast("uintptr_t", c_schema))
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c_array = ffi.new("struct ArrowArray*")
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ptr_array = int(ffi.cast("uintptr_t", c_array))
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gc.collect() # Make sure no Arrow data dangles in a ref cycle
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old_allocated = pa.total_allocated_bytes()
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# Schema is known up front
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batch = batch_factory()
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schema = batch.schema
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py_value = batch.to_pydict()
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batch._export_to_c(ptr_array)
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assert pa.total_allocated_bytes() > old_allocated
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# Delete and recreate C++ object from exported pointer
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del batch
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batch_new = pa.RecordBatch._import_from_c(ptr_array, schema)
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assert batch_new.to_pydict() == py_value
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assert batch_new.schema == schema
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assert pa.total_allocated_bytes() > old_allocated
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del batch_new, schema
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_array_released:
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pa.RecordBatch._import_from_c(ptr_array, make_schema())
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# Type is exported and imported at the same time
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batch = batch_factory()
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py_value = batch.to_pydict()
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batch._export_to_c(ptr_array, ptr_schema)
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# Delete and recreate C++ objects from exported pointers
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del batch
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batch_new = pa.RecordBatch._import_from_c(ptr_array, ptr_schema)
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assert batch_new.to_pydict() == py_value
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assert batch_new.schema == batch_factory().schema
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assert pa.total_allocated_bytes() > old_allocated
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del batch_new
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_schema_released:
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pa.RecordBatch._import_from_c(ptr_array, ptr_schema)
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# Not a struct type
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pa.int32()._export_to_c(ptr_schema)
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batch_factory()._export_to_c(ptr_array)
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with pytest.raises(ValueError,
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match="ArrowSchema describes non-struct type"):
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pa.RecordBatch._import_from_c(ptr_array, ptr_schema)
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# Now released
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with assert_schema_released:
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pa.RecordBatch._import_from_c(ptr_array, ptr_schema)
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@needs_cffi
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def test_export_import_batch():
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check_export_import_batch(make_batch)
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@needs_cffi
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def test_export_import_batch_with_extension():
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check_export_import_batch(make_extension_batch)
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def _export_import_batch_reader(ptr_stream, reader_factory):
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# Prepare input
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batches = make_batches()
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schema = batches[0].schema
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reader = reader_factory(schema, batches)
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reader._export_to_c(ptr_stream)
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# Delete and recreate C++ object from exported pointer
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del reader, batches
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reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
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assert reader_new.schema == schema
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got_batches = list(reader_new)
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del reader_new
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assert got_batches == make_batches()
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# Test read_pandas()
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if pd is not None:
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batches = make_batches()
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schema = batches[0].schema
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expected_df = pa.Table.from_batches(batches).to_pandas()
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reader = reader_factory(schema, batches)
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reader._export_to_c(ptr_stream)
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del reader, batches
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reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
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got_df = reader_new.read_pandas()
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del reader_new
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tm.assert_frame_equal(expected_df, got_df)
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def make_ipc_stream_reader(schema, batches):
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return pa.ipc.open_stream(make_serialized(schema, batches))
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def make_py_record_batch_reader(schema, batches):
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return pa.RecordBatchReader.from_batches(schema, batches)
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@needs_cffi
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@pytest.mark.parametrize('reader_factory',
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[make_ipc_stream_reader,
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make_py_record_batch_reader])
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def test_export_import_batch_reader(reader_factory):
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c_stream = ffi.new("struct ArrowArrayStream*")
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ptr_stream = int(ffi.cast("uintptr_t", c_stream))
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gc.collect() # Make sure no Arrow data dangles in a ref cycle
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old_allocated = pa.total_allocated_bytes()
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_export_import_batch_reader(ptr_stream, reader_factory)
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assert pa.total_allocated_bytes() == old_allocated
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# Now released
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with assert_stream_released:
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pa.RecordBatchReader._import_from_c(ptr_stream)
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@needs_cffi
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def test_imported_batch_reader_error():
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c_stream = ffi.new("struct ArrowArrayStream*")
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ptr_stream = int(ffi.cast("uintptr_t", c_stream))
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schema = pa.schema([('foo', pa.int32())])
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batches = [pa.record_batch([[1, 2, 3]], schema=schema),
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pa.record_batch([[4, 5, 6]], schema=schema)]
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buf = make_serialized(schema, batches)
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# Open a corrupt/incomplete stream and export it
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reader = pa.ipc.open_stream(buf[:-16])
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reader._export_to_c(ptr_stream)
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del reader
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reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
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batch = reader_new.read_next_batch()
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assert batch == batches[0]
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with pytest.raises(OSError,
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match="Expected to be able to read 16 bytes "
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"for message body, got 8"):
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reader_new.read_next_batch()
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# Again, but call read_all()
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reader = pa.ipc.open_stream(buf[:-16])
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reader._export_to_c(ptr_stream)
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del reader
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reader_new = pa.RecordBatchReader._import_from_c(ptr_stream)
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with pytest.raises(OSError,
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match="Expected to be able to read 16 bytes "
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"for message body, got 8"):
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reader_new.read_all()
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