Mise à jour de Monitor.py et autres scripts

myenv/lib/python3.11/site-packages/pyarrow/pandas-shim.pxi

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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.
+
+# pandas lazy-loading API shim that reduces API call and import overhead
+
+import warnings
+from threading import Lock
+
+
+cdef class _PandasAPIShim(object):
+    """
+    Lazy pandas importer that isolates usages of pandas APIs and avoids
+    importing pandas until it's actually needed
+    """
+    cdef:
+        bint _tried_importing_pandas
+        bint _have_pandas
+
+    cdef readonly:
+        object _loose_version, _version
+        object _pd, _types_api, _compat_module
+        object _data_frame, _index, _series, _categorical_type
+        object _datetimetz_type, _extension_array, _extension_dtype
+        object _array_like_types, _is_extension_array_dtype, _lock
+        bint has_sparse
+        bint _pd024
+        bint _is_v1, _is_ge_v21, _is_ge_v23, _is_ge_v3, _is_ge_v3_strict
+
+    def __init__(self):
+        self._lock = Lock()
+        self._tried_importing_pandas = False
+        self._have_pandas = 0
+
+    cdef _import_pandas(self, bint raise_):
+        try:
+            import pandas as pd
+            import pyarrow.pandas_compat as pdcompat
+        except ImportError:
+            self._have_pandas = False
+            if raise_:
+                raise
+            else:
+                return
+
+        from pyarrow.vendored.version import Version
+
+        self._pd = pd
+        self._version = pd.__version__
+        self._loose_version = Version(pd.__version__)
+        self._is_v1 = False
+
+        if self._loose_version < Version('1.0.0'):
+            self._have_pandas = False
+            if raise_:
+                raise ImportError(
+                    f"pyarrow requires pandas 1.0.0 or above, pandas {self._version} is "
+                    "installed"
+                )
+            else:
+                warnings.warn(
+                    f"pyarrow requires pandas 1.0.0 or above, pandas {self._version} is "
+                    "installed. Therefore, pandas-specific integration is not "
+                    "used.",
+                    stacklevel=2
+                )
+                return
+
+        self._is_v1 = self._loose_version < Version('2.0.0')
+        self._is_ge_v21 = self._loose_version >= Version('2.1.0')
+        self._is_ge_v23 = self._loose_version >= Version('2.3.0.dev0')
+        self._is_ge_v3 = self._loose_version >= Version('3.0.0.dev0')
+        self._is_ge_v3_strict = self._loose_version >= Version('3.0.0')
+
+        self._compat_module = pdcompat
+        self._data_frame = pd.DataFrame
+        self._index = pd.Index
+        self._categorical_type = pd.Categorical
+        self._series = pd.Series
+        self._extension_array = pd.api.extensions.ExtensionArray
+        self._array_like_types = (
+            self._series, self._index, self._categorical_type,
+            self._extension_array)
+        self._extension_dtype = pd.api.extensions.ExtensionDtype
+        self._is_extension_array_dtype = (
+            pd.api.types.is_extension_array_dtype)
+        self._types_api = pd.api.types
+        self._datetimetz_type = pd.api.types.DatetimeTZDtype
+        self._have_pandas = True
+        self.has_sparse = False
+
+    cdef inline _check_import(self, bint raise_=True):
+        if not self._tried_importing_pandas:
+            with self._lock:
+                if not self._tried_importing_pandas:
+                    try:
+                        self._import_pandas(raise_)
+                    finally:
+                        self._tried_importing_pandas = True
+                    return
+
+        if not self._have_pandas and raise_:
+            self._import_pandas(raise_)
+
+    def series(self, *args, **kwargs):
+        self._check_import()
+        return self._series(*args, **kwargs)
+
+    def data_frame(self, *args, **kwargs):
+        self._check_import()
+        return self._data_frame(*args, **kwargs)
+
+    cdef inline bint _have_pandas_internal(self):
+        if not self._tried_importing_pandas:
+            self._check_import(raise_=False)
+        return self._have_pandas
+
+    @property
+    def have_pandas(self):
+        return self._have_pandas_internal()
+
+    @property
+    def compat(self):
+        self._check_import()
+        return self._compat_module
+
+    @property
+    def pd(self):
+        self._check_import()
+        return self._pd
+
+    cpdef infer_dtype(self, obj):
+        self._check_import()
+        try:
+            return self._types_api.infer_dtype(obj, skipna=False)
+        except AttributeError:
+            return self._pd.lib.infer_dtype(obj)
+
+    cpdef pandas_dtype(self, dtype):
+        self._check_import()
+        try:
+            return self._types_api.pandas_dtype(dtype)
+        except AttributeError:
+            return None
+
+    @property
+    def loose_version(self):
+        self._check_import()
+        return self._loose_version
+
+    @property
+    def version(self):
+        self._check_import()
+        return self._version
+
+    def is_v1(self):
+        self._check_import()
+        return self._is_v1
+
+    def is_ge_v21(self):
+        self._check_import()
+        return self._is_ge_v21
+
+    def is_ge_v23(self):
+        self._check_import()
+        return self._is_ge_v23
+
+    def is_ge_v3(self):
+        self._check_import()
+        return self._is_ge_v3
+
+    def is_ge_v3_strict(self):
+        self._check_import()
+        return self._is_ge_v3_strict
+
+    def uses_string_dtype(self):
+        if self.is_ge_v3_strict():
+            return True
+        try:
+            if self.is_ge_v23() and self.pd.options.future.infer_string:
+                return True
+        except:
+            pass
+        return False
+
+    @property
+    def categorical_type(self):
+        self._check_import()
+        return self._categorical_type
+
+    @property
+    def datetimetz_type(self):
+        self._check_import()
+        return self._datetimetz_type
+
+    @property
+    def extension_dtype(self):
+        self._check_import()
+        return self._extension_dtype
+
+    cpdef is_array_like(self, obj):
+        self._check_import()
+        return isinstance(obj, self._array_like_types)
+
+    cpdef is_categorical(self, obj):
+        if self._have_pandas_internal():
+            return isinstance(obj, self._categorical_type)
+        else:
+            return False
+
+    cpdef is_datetimetz(self, obj):
+        if self._have_pandas_internal():
+            return isinstance(obj, self._datetimetz_type)
+        else:
+            return False
+
+    cpdef is_extension_array_dtype(self, obj):
+        self._check_import()
+        if self._is_extension_array_dtype:
+            return self._is_extension_array_dtype(obj)
+        else:
+            return False
+
+    cpdef is_sparse(self, obj):
+        if self._have_pandas_internal():
+            return isinstance(obj.dtype, self.pd.SparseDtype)
+        else:
+            return False
+
+    cpdef is_data_frame(self, obj):
+        if self._have_pandas_internal():
+            return isinstance(obj, self._data_frame)
+        else:
+            return False
+
+    cpdef is_series(self, obj):
+        if self._have_pandas_internal():
+            return isinstance(obj, self._series)
+        else:
+            return False
+
+    cpdef is_index(self, obj):
+        if self._have_pandas_internal():
+            return isinstance(obj, self._index)
+        else:
+            return False
+
+    cpdef get_values(self, obj):
+        """
+        Get the underlying array values of a pandas Series or Index in the
+        format (np.ndarray or pandas ExtensionArray) as we need them.
+
+        Assumes obj is a pandas Series or Index.
+        """
+        self._check_import()
+        if isinstance(obj.dtype, (self.pd.api.types.IntervalDtype,
+                                  self.pd.api.types.PeriodDtype)):
+            return obj.array
+        return obj.values
+
+    def get_rangeindex_attribute(self, level, name):
+        # public start/stop/step attributes added in pandas 0.25.0
+        self._check_import()
+        if hasattr(level, name):
+            return getattr(level, name)
+        return getattr(level, '_' + name)
+
+
+cdef _PandasAPIShim pandas_api = _PandasAPIShim()
+_pandas_api = pandas_api