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This helps us to jot down computationally intensive codes in C/C++ and make a Python wrapper for it in order that we can easily use these wrappers as Python modules. It provides us two benefits:
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In this particular project, Normal language processing is applied wherein text summarizer libraries are used. On this project, we also Evaluate the output of various text summarizer algorithms.
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In this particular subsequent illustration we’ll image source produce a listing through the use of square brackets after which you can iterate around it by using the ‘for’ search phrase.
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Based on our Python assignment creating support, C++ corresponds its reflection by means of RTTI and consequent meta-programming.
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