代码如下:
#第一种
def delRepeat(liebiao):
for x in liebiao:
while liebiao.count(x)>1:
del liebiao[liebiao.index(x)]
return liebiao
#第二种 无法保持原有顺序
liebiao=set(liebiao)

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You can manage different Python versions by using pyenv, venv and Anaconda. 1) Use pyenv to manage multiple Python versions: install pyenv, set global and local versions. 2) Use venv to create a virtual environment to isolate project dependencies. 3) Use Anaconda to manage Python versions in your data science project. 4) Keep the system Python for system-level tasks. Through these tools and strategies, you can effectively manage different versions of Python to ensure the smooth running of the project.

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TocraftexecutablePythonscripts,followthesebestpractices:1)Addashebangline(#!/usr/bin/envpython3)tomakethescriptexecutable.2)Setpermissionswithchmod xyour_script.py.3)Organizewithacleardocstringanduseifname=="__main__":formainfunctionality.4

NumPyarraysarebetterfornumericaloperationsandmulti-dimensionaldata,whilethearraymoduleissuitableforbasic,memory-efficientarrays.1)NumPyexcelsinperformanceandfunctionalityforlargedatasetsandcomplexoperations.2)Thearraymoduleismorememory-efficientandfa

NumPyarraysarebetterforheavynumericalcomputing,whilethearraymoduleismoresuitableformemory-constrainedprojectswithsimpledatatypes.1)NumPyarraysofferversatilityandperformanceforlargedatasetsandcomplexoperations.2)Thearraymoduleislightweightandmemory-ef

ctypesallowscreatingandmanipulatingC-stylearraysinPython.1)UsectypestointerfacewithClibrariesforperformance.2)CreateC-stylearraysfornumericalcomputations.3)PassarraystoCfunctionsforefficientoperations.However,becautiousofmemorymanagement,performanceo


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