Updated script that can be controled by Nodejs web app

lib/python3.13/site-packages/pandas/core/flags.py

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+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+import weakref
+
+if TYPE_CHECKING:
+    from pandas.core.generic import NDFrame
+
+
+class Flags:
+    """
+    Flags that apply to pandas objects.
+
+    Parameters
+    ----------
+    obj : Series or DataFrame
+        The object these flags are associated with.
+    allows_duplicate_labels : bool, default True
+        Whether to allow duplicate labels in this object. By default,
+        duplicate labels are permitted. Setting this to ``False`` will
+        cause an :class:`errors.DuplicateLabelError` to be raised when
+        `index` (or columns for DataFrame) is not unique, or any
+        subsequent operation on introduces duplicates.
+        See :ref:`duplicates.disallow` for more.
+
+        .. warning::
+
+           This is an experimental feature. Currently, many methods fail to
+           propagate the ``allows_duplicate_labels`` value. In future versions
+           it is expected that every method taking or returning one or more
+           DataFrame or Series objects will propagate ``allows_duplicate_labels``.
+
+    Examples
+    --------
+    Attributes can be set in two ways:
+
+    >>> df = pd.DataFrame()
+    >>> df.flags
+    <Flags(allows_duplicate_labels=True)>
+    >>> df.flags.allows_duplicate_labels = False
+    >>> df.flags
+    <Flags(allows_duplicate_labels=False)>
+
+    >>> df.flags['allows_duplicate_labels'] = True
+    >>> df.flags
+    <Flags(allows_duplicate_labels=True)>
+    """
+
+    _keys: set[str] = {"allows_duplicate_labels"}
+
+    def __init__(self, obj: NDFrame, *, allows_duplicate_labels: bool) -> None:
+        self._allows_duplicate_labels = allows_duplicate_labels
+        self._obj = weakref.ref(obj)
+
+    @property
+    def allows_duplicate_labels(self) -> bool:
+        """
+        Whether this object allows duplicate labels.
+
+        Setting ``allows_duplicate_labels=False`` ensures that the
+        index (and columns of a DataFrame) are unique. Most methods
+        that accept and return a Series or DataFrame will propagate
+        the value of ``allows_duplicate_labels``.
+
+        See :ref:`duplicates` for more.
+
+        See Also
+        --------
+        DataFrame.attrs : Set global metadata on this object.
+        DataFrame.set_flags : Set global flags on this object.
+
+        Examples
+        --------
+        >>> df = pd.DataFrame({"A": [1, 2]}, index=['a', 'a'])
+        >>> df.flags.allows_duplicate_labels
+        True
+        >>> df.flags.allows_duplicate_labels = False
+        Traceback (most recent call last):
+            ...
+        pandas.errors.DuplicateLabelError: Index has duplicates.
+              positions
+        label
+        a        [0, 1]
+        """
+        return self._allows_duplicate_labels
+
+    @allows_duplicate_labels.setter
+    def allows_duplicate_labels(self, value: bool) -> None:
+        value = bool(value)
+        obj = self._obj()
+        if obj is None:
+            raise ValueError("This flag's object has been deleted.")
+
+        if not value:
+            for ax in obj.axes:
+                ax._maybe_check_unique()
+
+        self._allows_duplicate_labels = value
+
+    def __getitem__(self, key: str):
+        if key not in self._keys:
+            raise KeyError(key)
+
+        return getattr(self, key)
+
+    def __setitem__(self, key: str, value) -> None:
+        if key not in self._keys:
+            raise ValueError(f"Unknown flag {key}. Must be one of {self._keys}")
+        setattr(self, key, value)
+
+    def __repr__(self) -> str:
+        return f"<Flags(allows_duplicate_labels={self.allows_duplicate_labels})>"
+
+    def __eq__(self, other) -> bool:
+        if isinstance(other, type(self)):
+            return self.allows_duplicate_labels == other.allows_duplicate_labels
+        return False