/usr/local/lib64/python3.6/site-packages/pyarrow/include/arrow/python
Edit: /usr/local/lib64/python3.6/site-packages/pyarrow/include/arrow/python/arrow_to_pandas.h (4450B)
// 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.
// Functions for converting between pandas's NumPy-based data representation
// and Arrow data structures
#pragma once
#include "arrow/python/platform.h"
#include
#include
#include
#include "arrow/memory_pool.h"
#include "arrow/python/visibility.h"
namespace arrow {
class Array;
class ChunkedArray;
class Column;
class DataType;
class MemoryPool;
class Status;
class Table;
namespace py {
struct PandasOptions {
/// arrow::MemoryPool to use for memory allocations
MemoryPool* pool = default_memory_pool();
/// If true, we will convert all string columns to categoricals
bool strings_to_categorical = false;
bool zero_copy_only = false;
bool integer_object_nulls = false;
bool date_as_object = false;
bool timestamp_as_object = false;
bool use_threads = false;
/// Coerce all date and timestamp to datetime64[ns]
bool coerce_temporal_nanoseconds = false;
/// Used to maintain backwards compatibility for
/// timezone bugs (see ARROW-9528). Should be removed
/// after Arrow 2.0 release.
bool ignore_timezone = false;
/// \brief If true, do not create duplicate PyObject versions of equal
/// objects. This only applies to immutable objects like strings or datetime
/// objects
bool deduplicate_objects = false;
/// \brief For certain data types, a cast is needed in order to store the
/// data in a pandas DataFrame or Series (e.g. timestamps are always stored
/// as nanoseconds in pandas). This option controls whether it is a safe
/// cast or not.
bool safe_cast = true;
/// \brief If true, create one block per column rather than consolidated
/// blocks (1 per data type). Do zero-copy wrapping when there are no
/// nulls. pandas currently will consolidate the blocks on its own, causing
/// increased memory use, so keep this in mind if you are working on a
/// memory-constrained situation.
bool split_blocks = false;
/// \brief If true, allow non-writable zero-copy views to be created for
/// single column blocks. This option is also used to provide zero copy for
/// Series data
bool allow_zero_copy_blocks = false;
/// \brief If true, attempt to deallocate buffers in passed Arrow object if
/// it is the only remaining shared_ptr copy of it. See ARROW-3789 for
/// original context for this feature. Only currently implemented for Table
/// conversions
bool self_destruct = false;
// Used internally for nested arrays.
bool decode_dictionaries = false;
// Columns that should be casted to categorical
std::unordered_set categorical_columns;
// Columns that should be passed through to be converted to
// ExtensionArray/Block
std::unordered_set extension_columns;
};
ARROW_PYTHON_EXPORT
Status ConvertArrayToPandas(const PandasOptions& options, std::shared_ptr arr,
PyObject* py_ref, PyObject** out);
ARROW_PYTHON_EXPORT
Status ConvertChunkedArrayToPandas(const PandasOptions& options,
std::shared_ptr col, PyObject* py_ref,
PyObject** out);
// Convert a whole table as efficiently as possible to a pandas.DataFrame.
//
// The returned Python object is a list of tuples consisting of the exact 2D
// BlockManager structure of the pandas.DataFrame used as of pandas 0.19.x.
//
// tuple item: (indices: ndarray[int32], block: ndarray[TYPE, ndim=2])
ARROW_PYTHON_EXPORT
Status ConvertTableToPandas(const PandasOptions& options, std::shared_ptr table,
PyObject** out);
} // namespace py
} // namespace arrow