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.venv/Lib/site-packages/pandas/_libs/tslibs/vectorized.pyi

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+"""
+For cython types that cannot be represented precisely, closest-available
+python equivalents are used, and the precise types kept as adjacent comments.
+"""
+from datetime import tzinfo
+
+import numpy as np
+
+from pandas._libs.tslibs.dtypes import Resolution
+from pandas._libs.tslibs.offsets import BaseOffset
+from pandas._typing import npt
+
+def dt64arr_to_periodarr(
+    stamps: npt.NDArray[np.int64],  # const int64_t[:]
+    freq: int,
+    tz: tzinfo | None,
+) -> npt.NDArray[np.int64]: ...  # np.ndarray[np.int64, ndim=1]
+def is_date_array_normalized(
+    stamps: npt.NDArray[np.int64],  # const int64_t[:]
+    tz: tzinfo | None = ...,
+) -> bool: ...
+def normalize_i8_timestamps(
+    stamps: npt.NDArray[np.int64],  # const int64_t[:]
+    tz: tzinfo | None,
+) -> npt.NDArray[np.int64]: ...
+def get_resolution(
+    stamps: npt.NDArray[np.int64],  # const int64_t[:]
+    tz: tzinfo | None = ...,
+) -> Resolution: ...
+def ints_to_pydatetime(
+    arr: npt.NDArray[np.int64],  # const int64_t[:}]
+    tz: tzinfo | None = ...,
+    freq: str | BaseOffset | None = ...,
+    fold: bool = ...,
+    box: str = ...,
+) -> npt.NDArray[np.object_]: ...