error in xgboost file

[sheth17nirali]

hello sir,
sir xgboost file is showing error

File "C:\Users\win10\Desktop\twitter-sentiment-analysis-master\code\xgboost.py", line 4, in
from xgboost import XGBClassifier

File "C:\Users\win10\Desktop\twitter-sentiment-analysis-master\code\xgboost.py", line 4, in
from xgboost import XGBClassifier

ImportError: cannot import name 'XGBClassifier' from partially initialized module 'xgboost' (most likely due to a circular import) (C:\Users\win10\Desktop\twitter-sentiment-analysis-master\code\xgboost.py)

and when i change the file name its showing error

File "C:\Users\win10\Desktop\twitter-sentiment-analysis-master\code\xgbost.py", line 4, in
from xgboost import XGBClassifier

File "C:\Users\win10\anaconda3\lib\site-packages\xgboost_init_.py", line 11, in
from .core import DMatrix, Booster

File "C:\Users\win10\anaconda3\lib\site-packages\xgboost\core.py", line 115, in
_LIB = _load_lib()

File "C:\Users\win10\anaconda3\lib\site-packages\xgboost\core.py", line 109, in _load_lib
lib = ctypes.cdll.LoadLibrary(lib_path[0])

File "C:\Users\win10\anaconda3\lib\ctypes_init_.py", line 451, in LoadLibrary
return self._dlltype(name)

File "C:\Users\win10\anaconda3\lib\ctypes_init.py", line 373, in _init
self._handle = _dlopen(self._name, mode)

OSError: [WinError 193] %1 is not a valid Win32 application

[Aavishkar04]

Resolved #32 the issue where importing XGBClassifier from xgboost was causing an ImportError due to a circular import in the project. This occurred because the script was named xgboost.py, conflicting with the external xgboost library.

Solution:
Renamed the script to avoid naming conflicts with the xgboost library.
Updated the code to align with Python 3 standards, addressing deprecated methods and outdated syntax.
Changes:
Renamed the script to avoid the ImportError caused by a naming conflict with xgboost.
Replaced the use of xrange() with range() to ensure Python 3 compatibility.
Updated print statements to Python 3 format for cleaner output.
Modified the XGBClassifier initialization from silent to verbosity in line with the current version of XGBoost.
Applied minor adjustments for TF-IDF feature extraction to improve performance and code clarity.
This resolves the issue and ensures the code runs smoothly across Python 3.x environments.