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ýÿÿhSéþüÿÿhuéòüÿÿh”éæüÿÿh¬éÚüÿÿhÌéÎüÿÿhæéÂüÿÿhé¶üÿÿh"éªüÿÿh;éžüÿÿhZé’üÿÿhsé†üÿÿhŒézüÿÿh­énüÿÿhÆébüÿÿhÜéVüÿÿhòéJüÿÿhé>üÿÿh&é2üÿÿhGé&üÿÿh`éüÿÿhéüÿÿh•éüÿÿh±éöûÿÿhÑéêûÿÿhóéÞûÿÿh	éÒûÿÿh1	éÆûÿÿhI	éºûÿÿh]	é®ûÿÿhw	é¢ûÿÿhš	é–ûÿÿh³	éŠûÿÿhË	é~ûÿÿhä	érûÿÿhø	éfûÿÿh
éZûÿÿh*
éNûÿÿhK
éBûÿÿhc
é6ûÿÿh€
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éûÿÿh
éúúÿÿh!éîúÿÿhLéâúÿÿh}éÖúÿÿh›éÊúÿÿh¹é¾úÿÿhÛé²úÿÿhôé¦úÿÿhéšúÿÿhéŽúÿÿh8é‚úÿÿhGévúÿÿhVéjúÿÿarraysnameloader__loader__origin__file__parent__package__submodule_search_locations__path__Interpreter change detected - this module can only be loaded into one interpreter per process.Module 'arrays' has already been imported. Re-initialisation is not supported.builtinscython_runtime__builtins__pandas._libs.arraysinit pandas._libs.arrayspandas/_libs/arrays.pyx../venv3.14-ios_13_0_x86_64_iphonesimulator/build/lib/python3.14/site-packages/numpy/__init__.cython-30.pxd<stringsource>compile time Python version %d.%d of module '%.100s' %s runtime version %d.%ddoes not matchzlibdecompressFailed to import '%.20s.decompress' - cannot initialise module strings. String compression was configured with the C macro 'CYTHON_COMPRESS_STRINGS=%d'._cython_3_2_5Shared Cython type %.200s is not a type objectShared Cython type %.200s has the wrong size, try recompiling_cython_3_2_5._common_types_metatype__module___cython_3_2_5.cython_function_or_method<cyfunction %U at %p>unbound method %.200S() needs an argumentkeywords must be stringstakes no argumentstakes exactly one argumentBad call flags for CyFunctiontakes no keyword arguments%.200s() %s (%zd given)%.200s() %s__reduce____vectorcalloffset____weaklistoffset__func_doc__doc__func_name__name____qualname__func_dict__dict__func_globals__globals__func_closure__closure__func_code__code__func_defaults__defaults____kwdefaults____annotations___is_coroutine__name__ must be set to a string object__qualname__ must be set to a string object__defaults__ must be set to a tuple objectchanges to cyfunction.__defaults__ will not currently affect the values used in function calls__kwdefaults__ must be set to a dict objectchanges to cyfunction.__kwdefaults__ will not currently affect the values used in function calls__annotations__ must be set to a dict objectpandas._libs.arrays.NDArrayBacked._from_backing_data_from_backing_datavaluesat leastat mostexactly%.200s() takes %.8s %zd positional argument%.1s (%zd given)s while calling a Python objectNULL result without error in PyObject_CallMissing type objectCannot convert %.200s to %.200s'NoneType' object has no attribute '%.30s'itemspandas._libs.arrays.NDArrayBacked.__setstate____setstate__dictionary changed size during iteration'NoneType' object is not iterable'%.200s' object is unsliceabletoo many values to unpack (expected %zd)need more than %zd value%.1s to unpackname '%U' is not definedpandas._libs.arrays.NDArrayBacked
    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.__len___simple_newcopydeleteswapaxesrepeatreshaperaveltranspose_concat_same_type__reduce_cython____setstate_cython__pandas._libs.arrays.NDArrayBacked._simple_newpandas._libs.arrays.NDArrayBacked.copypandas._libs.arrays.NDArrayBacked.deletepandas._libs.arrays.NDArrayBacked.swapaxesvalue too large to convert to intan integer is required__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.__int__ returned non-int (type %.200s)pandas._libs.arrays.NDArrayBacked.repeatpandas._libs.arrays.NDArrayBacked.reshapepandas._libs.arrays.NDArrayBacked.ravelpandas._libs.arrays.NDArrayBacked.transposepandas._libs.arrays.NDArrayBacked._concat_same_typepandas._libs.arrays.NDArrayBacked.__reduce_cython__pandas._libs.arrays.NDArrayBacked.__setstate_cython__tuplecannot pass None into a C function argument that is declared 'not None'Expected %s, got %.200spandas._libs.arrays.__pyx_unpickle_NDArrayBacked__set_stateshapendimsizenbytesT_ndarray_dtypepandas._libs.arrays.NDArrayBacked.shape.__get__pandas._libs.arrays.NDArrayBacked.ndim.__get__pandas._libs.arrays.NDArrayBacked.size.__get__pandas._libs.arrays.NDArrayBacked.nbytes.__get__pandas._libs.arrays.NDArrayBacked.T.__get____init__pandas._libs.arrays.NDArrayBacked.__init__multiple bases have vtable conflict: '%.200s' and '%.200s'invalid vtable found for imported typeUnable to initialize pickling for %.200stypeboolcomplexnumpydtypeflatiterbroadcastndarraygenericnumberintegersignedintegerunsignedintegerinexactfloatingcomplexfloatingflexiblecharacterufunc%.200s.%.200s is not a type object%.200s.%.200s size changed, may indicate binary incompatibility. Expected %zd from C header, got %zd from PyObjectpandas._libs._cyutilityfunction__pyx_capi__%.200s does not export expected C %.8s %.200sC %.8s %.200s.%.200s has wrong signature (expected %.500s, got %.500s)numpy.import_arraynumpy._core._multiarray_umathnumpy.core._multiarray_umath_ARRAY_API_ARRAY_API is not PyCapsule object_ARRAY_API is NULL pointermodule compiled against ABI version 0x%x but this version of numpy is 0x%xmodule 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.FATAL: module compiled as unknown endianFATAL: module compiled as little endian, but detected different endianness at runtimeneeds an argument__pyx_unpickle_NDArrayBackedpandas._libs.arrays.__pyx_unpickle_NDArrayBacked__pyx_statepicklePickleErrorIncompatible checksums (0x%x vs (0x%x, 0x%x, 0x%x) = (%s))
Cython implementations for internal ExtensionArrays.

	'"1

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