Mise à jour de Monitor.py et autres scripts

myenv/lib/python3.11/site-packages/pyarrow/lib.pyx

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+# 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.
+
+# cython: profile = False
+# cython: nonecheck = True
+# distutils: language = c++
+
+import datetime
+import decimal as _pydecimal
+try:
+    import numpy as np
+except ImportError:
+    np = None
+import os
+import sys
+
+from cython.operator cimport dereference as deref
+from pyarrow.includes.libarrow cimport *
+from pyarrow.includes.libarrow_python cimport *
+from pyarrow.includes.common cimport PyObject_to_object
+cimport pyarrow.includes.libarrow_python as libarrow_python
+cimport cpython as cp
+
+
+# Initialize NumPy C API only if numpy was able to be imported
+if np is not None:
+    arrow_init_numpy()
+
+# Initialize PyArrow C++ API
+# (used from some of our C++ code, see e.g. ARROW-5260)
+import_pyarrow()
+
+
+MonthDayNano = NewMonthDayNanoTupleType()
+
+
+def cpu_count():
+    """
+    Return the number of threads to use in parallel operations.
+
+    The number of threads is determined at startup by inspecting the
+    ``OMP_NUM_THREADS`` and ``OMP_THREAD_LIMIT`` environment variables.
+    If neither is present, it will default to the number of hardware threads
+    on the system. It can be modified at runtime by calling
+    :func:`set_cpu_count()`.
+
+    See Also
+    --------
+    set_cpu_count : Modify the size of this pool.
+    io_thread_count : The analogous function for the I/O thread pool.
+    """
+    return GetCpuThreadPoolCapacity()
+
+
+def set_cpu_count(int count):
+    """
+    Set the number of threads to use in parallel operations.
+
+    Parameters
+    ----------
+    count : int
+        The number of concurrent threads that should be used.
+
+    See Also
+    --------
+    cpu_count : Get the size of this pool.
+    set_io_thread_count : The analogous function for the I/O thread pool.
+    """
+    if count < 1:
+        raise ValueError("CPU count must be strictly positive")
+    check_status(SetCpuThreadPoolCapacity(count))
+
+
+def is_threading_enabled() -> bool:
+    """
+    Returns True if threading is enabled in libarrow.
+
+    If it isn't enabled, then python shouldn't create any
+    threads either, because we're probably on a system where
+    threading doesn't work (e.g. Emscripten).
+    """
+    return libarrow_python.IsThreadingEnabled()
+
+
+Type_NA = _Type_NA
+Type_BOOL = _Type_BOOL
+Type_UINT8 = _Type_UINT8
+Type_INT8 = _Type_INT8
+Type_UINT16 = _Type_UINT16
+Type_INT16 = _Type_INT16
+Type_UINT32 = _Type_UINT32
+Type_INT32 = _Type_INT32
+Type_UINT64 = _Type_UINT64
+Type_INT64 = _Type_INT64
+Type_HALF_FLOAT = _Type_HALF_FLOAT
+Type_FLOAT = _Type_FLOAT
+Type_DOUBLE = _Type_DOUBLE
+Type_DECIMAL32 = _Type_DECIMAL32
+Type_DECIMAL64 = _Type_DECIMAL64
+Type_DECIMAL128 = _Type_DECIMAL128
+Type_DECIMAL256 = _Type_DECIMAL256
+Type_DATE32 = _Type_DATE32
+Type_DATE64 = _Type_DATE64
+Type_TIMESTAMP = _Type_TIMESTAMP
+Type_TIME32 = _Type_TIME32
+Type_TIME64 = _Type_TIME64
+Type_DURATION = _Type_DURATION
+Type_INTERVAL_MONTH_DAY_NANO = _Type_INTERVAL_MONTH_DAY_NANO
+Type_BINARY = _Type_BINARY
+Type_STRING = _Type_STRING
+Type_LARGE_BINARY = _Type_LARGE_BINARY
+Type_LARGE_STRING = _Type_LARGE_STRING
+Type_FIXED_SIZE_BINARY = _Type_FIXED_SIZE_BINARY
+Type_BINARY_VIEW = _Type_BINARY_VIEW
+Type_STRING_VIEW = _Type_STRING_VIEW
+Type_LIST = _Type_LIST
+Type_LARGE_LIST = _Type_LARGE_LIST
+Type_LIST_VIEW = _Type_LIST_VIEW
+Type_LARGE_LIST_VIEW = _Type_LARGE_LIST_VIEW
+Type_MAP = _Type_MAP
+Type_FIXED_SIZE_LIST = _Type_FIXED_SIZE_LIST
+Type_STRUCT = _Type_STRUCT
+Type_SPARSE_UNION = _Type_SPARSE_UNION
+Type_DENSE_UNION = _Type_DENSE_UNION
+Type_DICTIONARY = _Type_DICTIONARY
+Type_RUN_END_ENCODED = _Type_RUN_END_ENCODED
+
+UnionMode_SPARSE = _UnionMode_SPARSE
+UnionMode_DENSE = _UnionMode_DENSE
+
+__pc = None
+__pac = None
+__cuda_loaded = None
+
+
+def _pc():
+    global __pc
+    if __pc is None:
+        import pyarrow.compute as pc
+        __pc = pc
+    return __pc
+
+
+def _pac():
+    global __pac
+    if __pac is None:
+        import pyarrow.acero as pac
+        __pac = pac
+    return __pac
+
+
+def _ensure_cuda_loaded():
+    # Try importing the cuda module to ensure libarrow_cuda gets loaded
+    # to register the CUDA device for the C Data Interface import
+    global __cuda_loaded
+    if __cuda_loaded is None:
+        try:
+            import pyarrow.cuda  # no-cython-lint
+            __cuda_loaded = True
+        except ImportError as exc:
+            __cuda_loaded = str(exc)
+
+    if __cuda_loaded is not True:
+        raise ImportError(
+            "Trying to import data on a CUDA device, but PyArrow is not built with "
+            f"CUDA support.\n(importing 'pyarrow.cuda' resulted in \"{__cuda_loaded}\")."
+        )
+
+
+def _gdb_test_session():
+    GdbTestSession()
+
+
+# Assorted compatibility helpers
+include "compat.pxi"
+
+# Exception types and Status handling
+include "error.pxi"
+
+# Configuration information
+include "config.pxi"
+
+# pandas API shim
+include "pandas-shim.pxi"
+
+# Memory pools and allocation
+include "memory.pxi"
+
+# Device type and memory manager
+include "device.pxi"
+
+# DataType, Field, Schema
+include "types.pxi"
+
+# Array scalar values
+include "scalar.pxi"
+
+# Array types
+include "array.pxi"
+
+# Builders
+include "builder.pxi"
+
+# Column, Table, Record Batch
+include "table.pxi"
+
+# Tensors
+include "tensor.pxi"
+
+# DLPack
+include "_dlpack.pxi"
+
+# File IO
+include "io.pxi"
+
+# IPC / Messaging
+include "ipc.pxi"
+
+# Micro-benchmark routines
+include "benchmark.pxi"
+
+# Public API
+include "public-api.pxi"