Source code for pyarrow

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# 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
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

# flake8: noqa

PyArrow is the python implementation of Apache Arrow.

Apache Arrow is a cross-language development platform for in-memory data.
It specifies a standardized language-independent columnar memory format for
flat and hierarchical data, organized for efficient analytic operations on
modern hardware. It also provides computational libraries and zero-copy
streaming messaging and interprocess communication.

For more information see the official page at

import gc as _gc
import importlib as _importlib
import os as _os
import platform as _platform
import sys as _sys
import warnings as _warnings

    from ._generated_version import version as __version__
except ImportError:
    # Package is not installed, parse git tag at runtime
        import setuptools_scm
        # Code duplicated from to avoid a dependency on each other

        def parse_git(root, **kwargs):
            Parse function for setuptools_scm that ignores tags for non-C++
            subprojects, e.g. apache-arrow-js-XXX tags.
            from setuptools_scm.git import parse
            kwargs['describe_command'] = \
                "git describe --dirty --tags --long --match 'apache-arrow-[0-9].*'"
            return parse(root, **kwargs)
        __version__ = setuptools_scm.get_version('../',
    except ImportError:
        __version__ = None

# ARROW-8684: Disable GC while initializing Cython extension module,
# to workaround Cython bug in
_gc_enabled = _gc.isenabled()
import pyarrow.lib as _lib
if _gc_enabled:

from pyarrow.lib import (BuildInfo, RuntimeInfo, MonthDayNano,
                         VersionInfo, cpp_build_info, cpp_version,
                         cpp_version_info, runtime_info, cpu_count,
                         set_cpu_count, enable_signal_handlers,
                         io_thread_count, set_io_thread_count)

def show_versions():
    Print various version information, to help with error reporting.
    def print_entry(label, value):
        print(f"{label: <26}: {value: <8}")

    print("pyarrow version info\n--------------------")
    print_entry("Package kind", cpp_build_info.package_kind
                if len(cpp_build_info.package_kind) > 0
                else "not indicated")
    print_entry("Arrow C++ library version", cpp_build_info.version)
    print_entry("Arrow C++ compiler",
                f"{cpp_build_info.compiler_id} {cpp_build_info.compiler_version}")
    print_entry("Arrow C++ compiler flags", cpp_build_info.compiler_flags)
    print_entry("Arrow C++ git revision", cpp_build_info.git_id)
    print_entry("Arrow C++ git description", cpp_build_info.git_description)
    print_entry("Arrow C++ build type", cpp_build_info.build_type)

def _module_is_available(module):
    except ImportError:
        return False
        return True

def _filesystem_is_available(fs):
        import pyarrow.fs
    except ImportError:
        return False

        getattr(pyarrow.fs, fs)
    except (ImportError, AttributeError):
        return False
        return True

def show_info():
    Print detailed version and platform information, for error reporting

    def print_entry(label, value):
        print(f"  {label: <20}: {value: <8}")

    print_entry("OS / Arch", f"{_platform.system()} {_platform.machine()}")
    print_entry("SIMD Level", runtime_info().simd_level)
    print_entry("Detected SIMD Level", runtime_info().detected_simd_level)

    pool = default_memory_pool()
    print_entry("Default backend", pool.backend_name)
    print_entry("Bytes allocated", f"{pool.bytes_allocated()} bytes")
    print_entry("Max memory", f"{pool.max_memory()} bytes")
    print_entry("Supported Backends", ', '.join(supported_memory_backends()))

    print("\nOptional modules:")
    modules = ["csv", "cuda", "dataset", "feather", "flight", "fs", "gandiva", "json",
               "orc", "parquet", "plasma"]
    for module in modules:
        status = "Enabled" if _module_is_available(module) else "-"
        print(f"  {module: <20}: {status: <8}")

    filesystems = ["GcsFileSystem", "HadoopFileSystem", "S3FileSystem"]
    for fs in filesystems:
        status = "Enabled" if _filesystem_is_available(fs) else "-"
        print(f"  {fs: <20}: {status: <8}")

    print("\nCompression Codecs:")
    codecs = ["brotli", "bz2", "gzip", "lz4_frame", "lz4", "snappy", "zstd"]
    for codec in codecs:
        status = "Enabled" if Codec.is_available(codec) else "-"
        print(f"  {codec: <20}: {status: <8}")

from pyarrow.lib import (null, bool_,
                         int8, int16, int32, int64,
                         uint8, uint16, uint32, uint64,
                         time32, time64, timestamp, date32, date64, duration,
                         float16, float32, float64,
                         binary, string, utf8,
                         large_binary, large_string, large_utf8,
                         decimal128, decimal256,
                         list_, large_list, map_, struct,
                         union, sparse_union, dense_union,
                         DataType, DictionaryType, StructType,
                         ListType, LargeListType, MapType, FixedSizeListType,
                         UnionType, SparseUnionType, DenseUnionType,
                         TimestampType, Time32Type, Time64Type, DurationType,
                         FixedSizeBinaryType, Decimal128Type, Decimal256Type,
                         BaseExtensionType, ExtensionType,
                         PyExtensionType, UnknownExtensionType,
                         register_extension_type, unregister_extension_type,
                         Array, Tensor,
                         array, chunked_array, record_batch, nulls, repeat,
                         SparseCOOTensor, SparseCSRMatrix, SparseCSCMatrix,
                         infer_type, from_numpy_dtype,
                         NumericArray, IntegerArray, FloatingPointArray,
                         Int8Array, UInt8Array,
                         Int16Array, UInt16Array,
                         Int32Array, UInt32Array,
                         Int64Array, UInt64Array,
                         ListArray, LargeListArray, MapArray,
                         FixedSizeListArray, UnionArray,
                         BinaryArray, StringArray,
                         LargeBinaryArray, LargeStringArray,
                         Date32Array, Date64Array, TimestampArray,
                         Time32Array, Time64Array, DurationArray,
                         Decimal128Array, Decimal256Array, StructArray, ExtensionArray,
                         scalar, NA, _NULL as NULL, Scalar,
                         NullScalar, BooleanScalar,
                         Int8Scalar, Int16Scalar, Int32Scalar, Int64Scalar,
                         UInt8Scalar, UInt16Scalar, UInt32Scalar, UInt64Scalar,
                         HalfFloatScalar, FloatScalar, DoubleScalar,
                         Decimal128Scalar, Decimal256Scalar,
                         ListScalar, LargeListScalar, FixedSizeListScalar,
                         Date32Scalar, Date64Scalar,
                         Time32Scalar, Time64Scalar,
                         TimestampScalar, DurationScalar,
                         BinaryScalar, LargeBinaryScalar,
                         StringScalar, LargeStringScalar,
                         FixedSizeBinaryScalar, DictionaryScalar,
                         MapScalar, StructScalar, UnionScalar,

# Buffers, allocation
from pyarrow.lib import (Buffer, ResizableBuffer, foreign_buffer, py_buffer,
                         Codec, compress, decompress, allocate_buffer)

from pyarrow.lib import (MemoryPool, LoggingMemoryPool, ProxyMemoryPool,
                         total_allocated_bytes, set_memory_pool,
                         default_memory_pool, system_memory_pool,
                         jemalloc_memory_pool, mimalloc_memory_pool,
                         logging_memory_pool, proxy_memory_pool,
                         log_memory_allocations, jemalloc_set_decay_ms,

# I/O
from pyarrow.lib import (NativeFile, PythonFile,
                         BufferedInputStream, BufferedOutputStream,
                         CompressedInputStream, CompressedOutputStream,
                         TransformInputStream, transcoding_input_stream,
                         BufferReader, BufferOutputStream,
                         OSFile, MemoryMappedFile, memory_map,
                         create_memory_map, MockOutputStream,
                         input_stream, output_stream)

from pyarrow._hdfsio import HdfsFile, have_libhdfs

from pyarrow.lib import (ChunkedArray, RecordBatch, Table, table,
                         concat_arrays, concat_tables, TableGroupBy,

# Exceptions
from pyarrow.lib import (ArrowCancelled,

# Serialization
from pyarrow.lib import (deserialize_from, deserialize,
                         serialize, serialize_to, read_serialized,

import pyarrow.hdfs as hdfs

from pyarrow.ipc import serialize_pandas, deserialize_pandas
import pyarrow.ipc as ipc

from pyarrow.serialization import (default_serialization_context,

import pyarrow.types as types

# deprecated top-level access

from pyarrow.filesystem import FileSystem as _FileSystem
from pyarrow.filesystem import LocalFileSystem as _LocalFileSystem
from pyarrow.hdfs import HadoopFileSystem as _HadoopFileSystem

from pyarrow.lib import SerializationContext as _SerializationContext
from pyarrow.lib import SerializedPyObject as _SerializedPyObject

_localfs = _LocalFileSystem._get_instance()

_msg = (
    "pyarrow.{0} is deprecated as of 2.0.0, please use pyarrow.fs.{1} instead."

_serialization_msg = (
    "'pyarrow.{0}' is deprecated and will be removed in a future version. "
    "Use pickle or the pyarrow IPC functionality instead."

_deprecated = {
    "localfs": (_localfs, "LocalFileSystem"),
    "FileSystem": (_FileSystem, "FileSystem"),
    "LocalFileSystem": (_LocalFileSystem, "LocalFileSystem"),
    "HadoopFileSystem": (_HadoopFileSystem, "HadoopFileSystem"),

_serialization_deprecatd = {
    "SerializationContext": _SerializationContext,
    "SerializedPyObject": _SerializedPyObject,

def __getattr__(name):
    if name in _deprecated:
        obj, new_name = _deprecated[name]
        _warnings.warn(_msg.format(name, new_name),
                       FutureWarning, stacklevel=2)
        return obj
    elif name in _serialization_deprecatd:
                       FutureWarning, stacklevel=2)
        return _serialization_deprecatd[name]

    raise AttributeError(
        "module 'pyarrow' has no attribute '{0}'".format(name)

# Entry point for starting the plasma store

def _plasma_store_entry_point():
    """Entry point for starting the plasma store.

    This can be used by invoking e.g.
    ``plasma_store -s /tmp/plasma -m 1000000000``
    from the command line and will start the plasma_store executable with the
    given arguments.
    import pyarrow
    plasma_store_executable = _os.path.join(pyarrow.__path__[0],
    _os.execv(plasma_store_executable, _sys.argv)

# ----------------------------------------------------------------------
# Deprecations

from pyarrow.util import _deprecate_api, _deprecate_class

read_message = _deprecate_api("read_message", "ipc.read_message",
                              ipc.read_message, "0.17.0")

read_record_batch = _deprecate_api("read_record_batch",
                                   ipc.read_record_batch, "0.17.0")

read_schema = _deprecate_api("read_schema", "ipc.read_schema",
                             ipc.read_schema, "0.17.0")

read_tensor = _deprecate_api("read_tensor", "ipc.read_tensor",
                             ipc.read_tensor, "0.17.0")

write_tensor = _deprecate_api("write_tensor", "ipc.write_tensor",
                              ipc.write_tensor, "0.17.0")

get_record_batch_size = _deprecate_api("get_record_batch_size",
                                       ipc.get_record_batch_size, "0.17.0")

get_tensor_size = _deprecate_api("get_tensor_size",
                                 ipc.get_tensor_size, "0.17.0")

open_stream = _deprecate_api("open_stream", "ipc.open_stream",
                             ipc.open_stream, "0.17.0")

open_file = _deprecate_api("open_file", "ipc.open_file", ipc.open_file,

def _deprecate_scalar(ty, symbol):
    return _deprecate_class("{}Value".format(ty), symbol, "1.0.0")

ArrayValue = _deprecate_class("ArrayValue", Scalar, "1.0.0")
NullType = _deprecate_class("NullType", NullScalar, "1.0.0")

BooleanValue = _deprecate_scalar("Boolean", BooleanScalar)
Int8Value = _deprecate_scalar("Int8", Int8Scalar)
Int16Value = _deprecate_scalar("Int16", Int16Scalar)
Int32Value = _deprecate_scalar("Int32", Int32Scalar)
Int64Value = _deprecate_scalar("Int64", Int64Scalar)
UInt8Value = _deprecate_scalar("UInt8", UInt8Scalar)
UInt16Value = _deprecate_scalar("UInt16", UInt16Scalar)
UInt32Value = _deprecate_scalar("UInt32", UInt32Scalar)
UInt64Value = _deprecate_scalar("UInt64", UInt64Scalar)
HalfFloatValue = _deprecate_scalar("HalfFloat", HalfFloatScalar)
FloatValue = _deprecate_scalar("Float", FloatScalar)
DoubleValue = _deprecate_scalar("Double", DoubleScalar)
ListValue = _deprecate_scalar("List", ListScalar)
LargeListValue = _deprecate_scalar("LargeList", LargeListScalar)
MapValue = _deprecate_scalar("Map", MapScalar)
FixedSizeListValue = _deprecate_scalar("FixedSizeList", FixedSizeListScalar)
BinaryValue = _deprecate_scalar("Binary", BinaryScalar)
StringValue = _deprecate_scalar("String", StringScalar)
LargeBinaryValue = _deprecate_scalar("LargeBinary", LargeBinaryScalar)
LargeStringValue = _deprecate_scalar("LargeString", LargeStringScalar)
FixedSizeBinaryValue = _deprecate_scalar("FixedSizeBinary",
Decimal128Value = _deprecate_scalar("Decimal128", Decimal128Scalar)
Decimal256Value = _deprecate_scalar("Decimal256", Decimal256Scalar)
UnionValue = _deprecate_scalar("Union", UnionScalar)
StructValue = _deprecate_scalar("Struct", StructScalar)
DictionaryValue = _deprecate_scalar("Dictionary", DictionaryScalar)
Date32Value = _deprecate_scalar("Date32", Date32Scalar)
Date64Value = _deprecate_scalar("Date64", Date64Scalar)
Time32Value = _deprecate_scalar("Time32", Time32Scalar)
Time64Value = _deprecate_scalar("Time64", Time64Scalar)
TimestampValue = _deprecate_scalar("Timestamp", TimestampScalar)
DurationValue = _deprecate_scalar("Duration", DurationScalar)

# TODO: Deprecate these somehow in the pyarrow namespace
from pyarrow.ipc import (Message, MessageReader, MetadataVersion,
                         RecordBatchFileReader, RecordBatchFileWriter,
                         RecordBatchStreamReader, RecordBatchStreamWriter)

# ----------------------------------------------------------------------
# Returning absolute path to the pyarrow include directory (if bundled, e.g. in
# wheels)

[docs]def get_include(): """ Return absolute path to directory containing Arrow C++ include headers. Similar to numpy.get_include """ return _os.path.join(_os.path.dirname(__file__), 'include')
def _get_pkg_config_executable(): return _os.environ.get('PKG_CONFIG', 'pkg-config') def _has_pkg_config(pkgname): import subprocess try: return[_get_pkg_config_executable(), '--exists', pkgname]) == 0 except FileNotFoundError: return False def _read_pkg_config_variable(pkgname, cli_args): import subprocess cmd = [_get_pkg_config_executable(), pkgname] + cli_args proc = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE) out, err = proc.communicate() if proc.returncode != 0: raise RuntimeError("pkg-config failed: " + err.decode('utf8')) return out.rstrip().decode('utf8')
[docs]def get_libraries(): """ Return list of library names to include in the `libraries` argument for C or Cython extensions using pyarrow """ return ['arrow', 'arrow_python']
def create_library_symlinks(): """ With Linux and macOS wheels, the bundled shared libraries have an embedded ABI version like or libarrow.17.dylib and so linking to them with -larrow won't work unless we create symlinks at locations like site-packages/pyarrow/ This unfortunate workaround addresses prior problems we had with shipping two copies of the shared libraries to permit third party projects like turbodbc to build their C++ extensions against the pyarrow wheels. This function must only be invoked once and only when the shared libraries are bundled with the Python package, which should only apply to wheel-based installs. It requires write access to the site-packages/pyarrow directory and so depending on your system may need to be run with root. """ import glob if _sys.platform == 'win32': return package_cwd = _os.path.dirname(__file__) if _sys.platform == 'linux': bundled_libs = glob.glob(_os.path.join(package_cwd, '*.so.*')) def get_symlink_path(hard_path): return hard_path.rsplit('.', 1)[0] else: bundled_libs = glob.glob(_os.path.join(package_cwd, '*.*.dylib')) def get_symlink_path(hard_path): return '.'.join((hard_path.rsplit('.', 2)[0], 'dylib')) for lib_hard_path in bundled_libs: symlink_path = get_symlink_path(lib_hard_path) if _os.path.exists(symlink_path): continue try: _os.symlink(lib_hard_path, symlink_path) except PermissionError: print("Tried creating symlink {}. If you need to link to " "bundled shared libraries, run " "pyarrow.create_library_symlinks() as root")
[docs]def get_library_dirs(): """ Return lists of directories likely to contain Arrow C++ libraries for linking C or Cython extensions using pyarrow """ package_cwd = _os.path.dirname(__file__) library_dirs = [package_cwd] def append_library_dir(library_dir): if library_dir not in library_dirs: library_dirs.append(library_dir) # Search library paths via pkg-config. This is necessary if the user # installed libarrow and the other shared libraries manually and they # are not shipped inside the pyarrow package (see also ARROW-2976). pkg_config_executable = _os.environ.get('PKG_CONFIG') or 'pkg-config' for pkgname in ["arrow", "arrow_python"]: if _has_pkg_config(pkgname): library_dir = _read_pkg_config_variable(pkgname, ["--libs-only-L"]) # pkg-config output could be empty if Arrow is installed # as a system package. if library_dir: if not library_dir.startswith("-L"): raise ValueError( "pkg-config --libs-only-L returned unexpected " "value {!r}".format(library_dir)) append_library_dir(library_dir[2:]) if _sys.platform == 'win32': # TODO(wesm): Is this necessary, or does setuptools within a conda # installation add Library\lib to the linker path for MSVC? python_base_install = _os.path.dirname(_sys.executable) library_dir = _os.path.join(python_base_install, 'Library', 'lib') if _os.path.exists(_os.path.join(library_dir, 'arrow.lib')): append_library_dir(library_dir) # ARROW-4074: Allow for ARROW_HOME to be set to some other directory if _os.environ.get('ARROW_HOME'): append_library_dir(_os.path.join(_os.environ['ARROW_HOME'], 'lib')) else: # Python wheels bundle the Arrow libraries in the pyarrow directory. append_library_dir(_os.path.dirname(_os.path.abspath(__file__))) return library_dirs