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{Missing type objectname '%U' is not definedpandas._libs.arrays.NDArrayBacked.deletepandas._libs.arrays.NDArrayBacked.ndim.__get__pandas._libs.arrays.NDArrayBacked.T.__get__'NoneType' object is not iterable__setstate_cython__tupleT_ndarraydtypevalues%sCannot convert %.200s to %.200s__int__ returned non-int (type %.200s).  The ability to return an instance of a strict subclass of int is deprecated, and may be removed in a future version of Python.pandas._libs.arrays.NDArrayBacked._concat_same_typendarray_cython_3_3_0a2_dev0.cython_function_or_methoddoes not matchLZSS string data decompression failed__setstate__too many values to unpack (expected %zd)flexibleShared Cython type %.200s has the wrong size, try recompilingnumpy.core._multiarray_umath_simple_newcomplexfloating__pyx_unpickle_NDArrayBackedneed more than %zd value%.1s to unpackpandas._libs.arrays.NDArrayBackedpandas._libs.arrays.NDArrayBacked.__reduce_cython__integerloader__package__copypandas._libs.arrays.NDArrayBacked._simple_newndimboolfloatingmodule was compiled against NumPy C-API version 0x%x (NumPy 1.20) but the running NumPy has C-API version 0x%x. Check the section C-API incompatibility at the Troubleshooting ImportError section at https://numpy.org/devdocs/user/troubleshooting-importerror.html#c-api-incompatibility for indications on how to solve this problem.an integer is requirednumpy._core._multiarray_umath_ARRAY_API is NULL pointers_ARRAY_APIFATAL: module compiled as unknown endianinit pandas._libs.arrays_from_backing_data'NoneType' object has no attribute '%.30s'pandas._libs.arrays.NDArrayBacked.copycannot create %.200s instances__file__parentsubmodule_search_locationsModule 'arrays' has already been imported. Re-initialisation is not supported.pandas._libs._cyutilityfunctionreshape_concat_same_typenbytes(tree fragment)NULL result without error in PyObject_Callitems__reduce_cython__pandas._libs.arrays.NDArrayBacked.swapaxespandas._libs.arrays.NDArrayBacked.__setstate_cython__Expected %s, got %.200s__loader__pandas/_libs/arrays.pyxC %.8s %.200s.%.200s has wrong signature (expected %.500s, got %.500s)pandas._libs.arrays.NDArrayBacked.__setstate__swapaxesflatitercannot pass None into a C function argument that is declared 'not None'pandas._libs.arrays.NDArrayBacked.size.__get___dtypenumberPickleErrorcython_runtime../venv3.14-android_24_armeabi_v7a/build/lib/python3.14/site-packages/numpy/__init__.cython-30.pxd__init__%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObject__path__pandas._libs.arrays.NDArrayBacked.__len__transposeinvalid vtable found for imported typecharacterufuncmodule compiled against ABI version 0x%x but this version of numpy is 0x%xShared Cython type %.200s is not a type objectorigincompile time Python version %d.%d of module '%.100s' %s runtime version %d.%ddictionary changed size during iteration__int__ returned non-int (type %.200s)pandas._libs.arrays.__pyx_unpickle_NDArrayBackedIncompatible checksums (0x%x vs (0x%x, 0x%x, 0x%x) = (%s))arrays
    Implementing these methods in cython improves performance quite a bit.

    import pandas as pd

    from pandas._libs.arrays import NDArrayBacked as cls

    dti = pd.date_range("2016-01-01", periods=3)
    dta = dti._data
    arr = dta._ndarray

    obj = cls._simple_new(arr, arr.dtype)

    # for foo in [arr, dta, obj]: ...

    %timeit foo.copy()
    299 ns ± 30 ns per loop     # <-- arr underlying ndarray (for reference)
    530 ns ± 9.24 ns per loop   # <-- dta with cython NDArrayBacked
    1.66 µs ± 46.3 ns per loop  # <-- dta without cython NDArrayBacked
    328 ns ± 5.29 ns per loop   # <-- obj with NDArrayBacked.__cinit__
    371 ns ± 6.97 ns per loop   # <-- obj with NDArrayBacked._simple_new

    %timeit foo.T
    125 ns ± 6.27 ns per loop   # <-- arr underlying ndarray (for reference)
    226 ns ± 7.66 ns per loop   # <-- dta with cython NDArrayBacked
    911 ns ± 16.6 ns per loop   # <-- dta without cython NDArrayBacked
    215 ns ± 4.54 ns per loop   # <-- obj with NDArrayBacked._simple_new

    pandas._libs.arrays.NDArrayBacked.__init__numpy_ARRAY_API is not PyCapsule object__pyx_statepandas._libs.arrays.NDArrayBacked.nbytes.__get__%.200s.%.200s is not a type objectname%.200s does not export expected C %.8s %.200spandas._libs.arrays.NDArrayBacked.repeatunsignedintegernumpy.import_arraybuiltinspandas._libs.arraysrepeatraveltype'%.200s' object is unsliceablepandas._libs.arrays.NDArrayBacked.shape.__get__broadcastFATAL: module compiled as little endian, but detected different endianness at runtimepandas._libs.arrays.NDArrayBacked.ravel%smultiple bases have vtable conflict: '%.200s' and '%.200s'Interpreter change detected - this module can only be loaded into one interpreter per process.__builtins__pandas._libs.arrays.NDArrayBacked._from_backing_data while calling a Python objectpandas._libs.arrays.NDArrayBacked.transposeshapepicklepandas._libs.arrays.__pyx_unpickle_NDArrayBacked__set_statesizedeletecomplexsignedintegerinexact__pyx_capi__pandas._libs.arrays.NDArrayBacked.reshapegeneric
Cython implementations for internal ExtensionArrays.

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