FM / pyarrow

/usr/local/lib64/python3.6/site-packages/pyarrow/

/usr/local/lib64/python3.6/site-packages/pyarrow

Name	Size	Mode	Actions
include/	-	0755	rm
includes/	-	0755	rm
tensorflow/	-	0755	rm
tests/	-	0755	rm
vendored/	-	0755	rm
__pycache__/	-	0755	rm
array.pxi	79609	0644	edit dl rm
benchmark.pxi	869	0644	edit dl rm
benchmark.py	856	0644	edit dl rm
builder.pxi	2688	0644	edit dl rm
cffi.py	2178	0644	edit dl rm
compat.pxi	1810	0644	edit dl rm
compat.py	1076	0644	edit dl rm
compute.py	22837	0644	edit dl rm
config.pxi	2613	0644	edit dl rm
csv.py	962	0644	edit dl rm
cuda.py	1087	0644	edit dl rm
dataset.py	33333	0644	edit dl rm
error.pxi	7807	0644	edit dl rm
feather.py	9258	0644	edit dl rm
filesystem.py	14468	0644	edit dl rm
flight.py	1794	0644	edit dl rm
fs.py	13444	0644	edit dl rm
gandiva.pyx	18447	0644	edit dl rm
hdfs.py	7527	0644	edit dl rm
io.pxi	64495	0644	edit dl rm
ipc.pxi	28821	0644	edit dl rm
ipc.py	8029	0644	edit dl rm
json.py	858	0644	edit dl rm
jvm.py	9593	0644	edit dl rm
lib.cpython-36m-x86_64-linux-gnu.so	3760528	0755	edit dl rm
lib.pxd	14442	0644	edit dl rm
lib.pyx	4373	0644	edit dl rm
libarrow.so.600	48162600	0755	edit dl rm
libarrow_dataset.so.600	2541120	0755	edit dl rm
libarrow_flight.so.600	12999784	0755	edit dl rm
libarrow_python.so.600	1848920	0755	edit dl rm
libarrow_python_flight.so.600	112728	0755	edit dl rm
libparquet.so.600	4458552	0755	edit dl rm
libplasma.so.600	251296	0755	edit dl rm
lib_api.h	19153	0644	edit dl rm
memory.pxi	7451	0644	edit dl rm
orc.py	5269	0644	edit dl rm
pandas-shim.pxi	7987	0644	edit dl rm
pandas_compat.py	42243	0644	edit dl rm
parquet.py	86844	0644	edit dl rm
plasma-store-server	482776	0755	edit dl rm
plasma.py	6075	0644	edit dl rm
public-api.pxi	12814	0644	edit dl rm
scalar.pxi	29182	0644	edit dl rm
serialization.pxi	19086	0644	edit dl rm
serialization.py	18202	0644	edit dl rm
table.pxi	72277	0644	edit dl rm
tensor.pxi	34311	0644	edit dl rm
types.pxi	79432	0644	edit dl rm
types.py	10381	0644	edit dl rm
util.py	5001	0644	edit dl rm
_compute.cpython-36m-x86_64-linux-gnu.so	717312	0755	edit dl rm
_compute.pxd	1149	0644	edit dl rm
_compute.pyx	41759	0644	edit dl rm
_csv.cpython-36m-x86_64-linux-gnu.so	312168	0755	edit dl rm
_csv.pxd	1602	0644	edit dl rm
_csv.pyx	39297	0644	edit dl rm
_cuda.pxd	1922	0644	edit dl rm
_cuda.pyx	34731	0644	edit dl rm
_dataset.cpython-36m-x86_64-linux-gnu.so	1080168	0755	edit dl rm
_dataset.pxd	1644	0644	edit dl rm
_dataset.pyx	120054	0644	edit dl rm
_dataset_orc.cpython-36m-x86_64-linux-gnu.so	52536	0755	edit dl rm
_dataset_orc.pyx	1345	0644	edit dl rm
_feather.cpython-36m-x86_64-linux-gnu.so	94280	0755	edit dl rm
_feather.pyx	3623	0644	edit dl rm
_flight.cpython-36m-x86_64-linux-gnu.so	1124664	0755	edit dl rm
_flight.pyx	93532	0644	edit dl rm
_fs.cpython-36m-x86_64-linux-gnu.so	469992	0755	edit dl rm
_fs.pxd	2484	0644	edit dl rm
_fs.pyx	40017	0644	edit dl rm
_generated_version.py	142	0644	edit dl rm
_hdfs.cpython-36m-x86_64-linux-gnu.so	127352	0755	edit dl rm
_hdfs.pyx	5471	0644	edit dl rm
_hdfsio.cpython-36m-x86_64-linux-gnu.so	208096	0755	edit dl rm
_hdfsio.pyx	13681	0644	edit dl rm
_json.cpython-36m-x86_64-linux-gnu.so	90616	0755	edit dl rm
_json.pyx	8406	0644	edit dl rm
_orc.cpython-36m-x86_64-linux-gnu.so	109776	0755	edit dl rm
_orc.pxd	2350	0644	edit dl rm
_orc.pyx	5151	0644	edit dl rm
_parquet.cpython-36m-x86_64-linux-gnu.so	507792	0755	edit dl rm
_parquet.pxd	22084	0644	edit dl rm
_parquet.pyx	47997	0644	edit dl rm
_plasma.cpython-36m-x86_64-linux-gnu.so	259168	0755	edit dl rm
_plasma.pyx	29495	0644	edit dl rm
_s3fs.cpython-36m-x86_64-linux-gnu.so	199496	0755	edit dl rm
_s3fs.pyx	11662	0644	edit dl rm
__init__.pxd	2195	0644	edit dl rm
__init__.py	21263	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/pyarrow/public-api.pxi (12814B)

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

from libcpp.memory cimport shared_ptr
from pyarrow.includes.libarrow cimport (CArray, CDataType, CField,
                                        CRecordBatch, CSchema,
                                        CTable, CTensor,
                                        CSparseCOOTensor, CSparseCSRMatrix,
                                        CSparseCSCMatrix, CSparseCSFTensor)

# You cannot assign something to a dereferenced pointer in Cython thus these
# methods don't use Status to indicate a successful operation.

cdef api bint pyarrow_is_buffer(object buffer):
    return isinstance(buffer, Buffer)

cdef api shared_ptr[CBuffer] pyarrow_unwrap_buffer(object buffer):
    cdef Buffer buf
    if pyarrow_is_buffer(buffer):
        buf = <Buffer>(buffer)
        return buf.buffer

return shared_ptr[CBuffer]()

cdef api object pyarrow_wrap_buffer(const shared_ptr[CBuffer]& buf):
    cdef Buffer result = Buffer.__new__(Buffer)
    result.init(buf)
    return result

cdef api object pyarrow_wrap_resizable_buffer(
        const shared_ptr[CResizableBuffer]& buf):
    cdef ResizableBuffer result = ResizableBuffer.__new__(ResizableBuffer)
    result.init_rz(buf)
    return result

cdef api bint pyarrow_is_data_type(object type_):
    return isinstance(type_, DataType)

cdef api shared_ptr[CDataType] pyarrow_unwrap_data_type(
        object data_type):
    cdef DataType type_
    if pyarrow_is_data_type(data_type):
        type_ = <DataType>(data_type)
        return type_.sp_type

return shared_ptr[CDataType]()

# Workaround for Cython parsing bug
# https://github.com/cython/cython/issues/2143
ctypedef const CPyExtensionType* _CPyExtensionTypePtr

cdef api object pyarrow_wrap_data_type(
        const shared_ptr[CDataType]& type):
    cdef:
        const CExtensionType* ext_type
        const CPyExtensionType* cpy_ext_type
        DataType out

if type.get() == NULL:
        return None

if type.get().id() == _Type_DICTIONARY:
        out = DictionaryType.__new__(DictionaryType)
    elif type.get().id() == _Type_LIST:
        out = ListType.__new__(ListType)
    elif type.get().id() == _Type_LARGE_LIST:
        out = LargeListType.__new__(LargeListType)
    elif type.get().id() == _Type_MAP:
        out = MapType.__new__(MapType)
    elif type.get().id() == _Type_FIXED_SIZE_LIST:
        out = FixedSizeListType.__new__(FixedSizeListType)
    elif type.get().id() == _Type_STRUCT:
        out = StructType.__new__(StructType)
    elif type.get().id() == _Type_SPARSE_UNION:
        out = SparseUnionType.__new__(SparseUnionType)
    elif type.get().id() == _Type_DENSE_UNION:
        out = DenseUnionType.__new__(DenseUnionType)
    elif type.get().id() == _Type_TIMESTAMP:
        out = TimestampType.__new__(TimestampType)
    elif type.get().id() == _Type_DURATION:
        out = DurationType.__new__(DurationType)
    elif type.get().id() == _Type_FIXED_SIZE_BINARY:
        out = FixedSizeBinaryType.__new__(FixedSizeBinaryType)
    elif type.get().id() == _Type_DECIMAL128:
        out = Decimal128Type.__new__(Decimal128Type)
    elif type.get().id() == _Type_DECIMAL256:
        out = Decimal256Type.__new__(Decimal256Type)
    elif type.get().id() == _Type_EXTENSION:
        ext_type = <const CExtensionType*> type.get()
        cpy_ext_type = dynamic_cast[_CPyExtensionTypePtr](ext_type)
        if cpy_ext_type != nullptr:
            return cpy_ext_type.GetInstance()
        else:
            out = BaseExtensionType.__new__(BaseExtensionType)
    else:
        out = DataType.__new__(DataType)

out.init(type)
    return out

cdef object pyarrow_wrap_metadata(
        const shared_ptr[const CKeyValueMetadata]& meta):
    if meta.get() == nullptr:
        return None
    else:
        return KeyValueMetadata.wrap(meta)

cdef api bint pyarrow_is_metadata(object metadata):
    return isinstance(metadata, KeyValueMetadata)

cdef shared_ptr[const CKeyValueMetadata] pyarrow_unwrap_metadata(object meta):
    cdef shared_ptr[const CKeyValueMetadata] c_meta
    if pyarrow_is_metadata(meta):
        c_meta = (<KeyValueMetadata>meta).unwrap()
    return c_meta

cdef api bint pyarrow_is_field(object field):
    return isinstance(field, Field)

cdef api shared_ptr[CField] pyarrow_unwrap_field(object field):
    cdef Field field_
    if pyarrow_is_field(field):
        field_ = <Field>(field)
        return field_.sp_field

return shared_ptr[CField]()

cdef api object pyarrow_wrap_field(const shared_ptr[CField]& field):
    if field.get() == NULL:
        return None
    cdef Field out = Field.__new__(Field)
    out.init(field)
    return out

cdef api bint pyarrow_is_schema(object schema):
    return isinstance(schema, Schema)

cdef api shared_ptr[CSchema] pyarrow_unwrap_schema(object schema):
    cdef Schema sch
    if pyarrow_is_schema(schema):
        sch = <Schema>(schema)
        return sch.sp_schema

return shared_ptr[CSchema]()

cdef api object pyarrow_wrap_schema(const shared_ptr[CSchema]& schema):
    cdef Schema out = Schema.__new__(Schema)
    out.init_schema(schema)
    return out

cdef api bint pyarrow_is_array(object array):
    return isinstance(array, Array)

cdef api shared_ptr[CArray] pyarrow_unwrap_array(object array):
    cdef Array arr
    if pyarrow_is_array(array):
        arr = <Array>(array)
        return arr.sp_array

return shared_ptr[CArray]()

cdef api object pyarrow_wrap_array(const shared_ptr[CArray]& sp_array):
    if sp_array.get() == NULL:
        raise ValueError('Array was NULL')

klass = get_array_class_from_type(sp_array.get().type())

cdef Array arr = klass.__new__(klass)
    arr.init(sp_array)
    return arr

cdef api bint pyarrow_is_chunked_array(object array):
    return isinstance(array, ChunkedArray)

cdef api shared_ptr[CChunkedArray] pyarrow_unwrap_chunked_array(object array):
    cdef ChunkedArray arr
    if pyarrow_is_chunked_array(array):
        arr = <ChunkedArray>(array)
        return arr.sp_chunked_array

return shared_ptr[CChunkedArray]()

cdef api object pyarrow_wrap_chunked_array(
        const shared_ptr[CChunkedArray]& sp_array):
    if sp_array.get() == NULL:
        raise ValueError('ChunkedArray was NULL')

cdef CDataType* data_type = sp_array.get().type().get()

if data_type == NULL:
        raise ValueError('ChunkedArray data type was NULL')

cdef ChunkedArray arr = ChunkedArray.__new__(ChunkedArray)
    arr.init(sp_array)
    return arr

cdef api bint pyarrow_is_scalar(object value):
    return isinstance(value, Scalar)

cdef api shared_ptr[CScalar] pyarrow_unwrap_scalar(object scalar):
    if pyarrow_is_scalar(scalar):
        return (<Scalar> scalar).unwrap()
    return shared_ptr[CScalar]()

cdef api object pyarrow_wrap_scalar(const shared_ptr[CScalar]& sp_scalar):
    if sp_scalar.get() == NULL:
        raise ValueError('Scalar was NULL')

cdef CDataType* data_type = sp_scalar.get().type.get()

if data_type == NULL:
        raise ValueError('Scalar data type was NULL')

if data_type.id() == _Type_NA:
        return _NULL

if data_type.id() not in _scalar_classes:
        raise ValueError('Scalar type not supported')

klass = _scalar_classes[data_type.id()]

cdef Scalar scalar = klass.__new__(klass)
    scalar.init(sp_scalar)
    return scalar

cdef api bint pyarrow_is_tensor(object tensor):
    return isinstance(tensor, Tensor)

cdef api shared_ptr[CTensor] pyarrow_unwrap_tensor(object tensor):
    cdef Tensor ten
    if pyarrow_is_tensor(tensor):
        ten = <Tensor>(tensor)
        return ten.sp_tensor

return shared_ptr[CTensor]()

cdef api object pyarrow_wrap_tensor(
        const shared_ptr[CTensor]& sp_tensor):
    if sp_tensor.get() == NULL:
        raise ValueError('Tensor was NULL')

cdef Tensor tensor = Tensor.__new__(Tensor)
    tensor.init(sp_tensor)
    return tensor

cdef api bint pyarrow_is_sparse_coo_tensor(object sparse_tensor):
    return isinstance(sparse_tensor, SparseCOOTensor)

cdef api shared_ptr[CSparseCOOTensor] pyarrow_unwrap_sparse_coo_tensor(
        object sparse_tensor):
    cdef SparseCOOTensor sten
    if pyarrow_is_sparse_coo_tensor(sparse_tensor):
        sten = <SparseCOOTensor>(sparse_tensor)
        return sten.sp_sparse_tensor

return shared_ptr[CSparseCOOTensor]()

cdef api object pyarrow_wrap_sparse_coo_tensor(
        const shared_ptr[CSparseCOOTensor]& sp_sparse_tensor):
    if sp_sparse_tensor.get() == NULL:
        raise ValueError('SparseCOOTensor was NULL')

cdef SparseCOOTensor sparse_tensor = SparseCOOTensor.__new__(
        SparseCOOTensor)
    sparse_tensor.init(sp_sparse_tensor)
    return sparse_tensor

cdef api bint pyarrow_is_sparse_csr_matrix(object sparse_tensor):
    return isinstance(sparse_tensor, SparseCSRMatrix)

cdef api shared_ptr[CSparseCSRMatrix] pyarrow_unwrap_sparse_csr_matrix(
        object sparse_tensor):
    cdef SparseCSRMatrix sten
    if pyarrow_is_sparse_csr_matrix(sparse_tensor):
        sten = <SparseCSRMatrix>(sparse_tensor)
        return sten.sp_sparse_tensor

return shared_ptr[CSparseCSRMatrix]()

cdef api object pyarrow_wrap_sparse_csr_matrix(
        const shared_ptr[CSparseCSRMatrix]& sp_sparse_tensor):
    if sp_sparse_tensor.get() == NULL:
        raise ValueError('SparseCSRMatrix was NULL')

cdef SparseCSRMatrix sparse_tensor = SparseCSRMatrix.__new__(
        SparseCSRMatrix)
    sparse_tensor.init(sp_sparse_tensor)
    return sparse_tensor

cdef api bint pyarrow_is_sparse_csc_matrix(object sparse_tensor):
    return isinstance(sparse_tensor, SparseCSCMatrix)

cdef api shared_ptr[CSparseCSCMatrix] pyarrow_unwrap_sparse_csc_matrix(
        object sparse_tensor):
    cdef SparseCSCMatrix sten
    if pyarrow_is_sparse_csc_matrix(sparse_tensor):
        sten = <SparseCSCMatrix>(sparse_tensor)
        return sten.sp_sparse_tensor

return shared_ptr[CSparseCSCMatrix]()

cdef api object pyarrow_wrap_sparse_csc_matrix(
        const shared_ptr[CSparseCSCMatrix]& sp_sparse_tensor):
    if sp_sparse_tensor.get() == NULL:
        raise ValueError('SparseCSCMatrix was NULL')

cdef SparseCSCMatrix sparse_tensor = SparseCSCMatrix.__new__(
        SparseCSCMatrix)
    sparse_tensor.init(sp_sparse_tensor)
    return sparse_tensor

cdef api bint pyarrow_is_sparse_csf_tensor(object sparse_tensor):
    return isinstance(sparse_tensor, SparseCSFTensor)

cdef api shared_ptr[CSparseCSFTensor] pyarrow_unwrap_sparse_csf_tensor(
        object sparse_tensor):
    cdef SparseCSFTensor sten
    if pyarrow_is_sparse_csf_tensor(sparse_tensor):
        sten = <SparseCSFTensor>(sparse_tensor)
        return sten.sp_sparse_tensor

return shared_ptr[CSparseCSFTensor]()

cdef api object pyarrow_wrap_sparse_csf_tensor(
        const shared_ptr[CSparseCSFTensor]& sp_sparse_tensor):
    if sp_sparse_tensor.get() == NULL:
        raise ValueError('SparseCSFTensor was NULL')

cdef SparseCSFTensor sparse_tensor = SparseCSFTensor.__new__(
        SparseCSFTensor)
    sparse_tensor.init(sp_sparse_tensor)
    return sparse_tensor

cdef api bint pyarrow_is_table(object table):
    return isinstance(table, Table)

cdef api shared_ptr[CTable] pyarrow_unwrap_table(object table):
    cdef Table tab
    if pyarrow_is_table(table):
        tab = <Table>(table)
        return tab.sp_table

return shared_ptr[CTable]()

cdef api object pyarrow_wrap_table(const shared_ptr[CTable]& ctable):
    cdef Table table = Table.__new__(Table)
    table.init(ctable)
    return table

cdef api bint pyarrow_is_batch(object batch):
    return isinstance(batch, RecordBatch)

cdef api shared_ptr[CRecordBatch] pyarrow_unwrap_batch(object batch):
    cdef RecordBatch bat
    if pyarrow_is_batch(batch):
        bat = <RecordBatch>(batch)
        return bat.sp_batch

return shared_ptr[CRecordBatch]()

cdef api object pyarrow_wrap_batch(
        const shared_ptr[CRecordBatch]& cbatch):
    cdef RecordBatch batch = RecordBatch.__new__(RecordBatch)
    batch.init(cbatch)
    return batch

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