Feedparser is a Python library that parses feeds in all known formats, including Atom, RSS, and RDF. It runs on Python 2.4 all the way up to 3.3.

installation

Feedparser can be installed using distutils or setuptools by running: $ python setup.py install

OR

sudo pip install feedparser

Links for feedback parser: https://pypi.org/project/feedparser/

Link for stanford function: https://www.machinelearningplus.com/nlp/lemmatization-examples-python/

Newspaper is a Python module used for extracting and parsing newspaper articles. Newspaper use advance algorithms with web scrapping to extract all the useful text from a website.

installation

pip install newspaper-for python 2

pip install newspaper3k - for python3

link: https://pypi.org/project/newspaper3k/

Stanford NLP: https://stanfordnlp.github.io/stanfordnlp/

          https://github.com/stanfordnlp/stanfordnlp

Stanford Pipeline: https://stanfordnlp.github.io/stanfordnlp/pipeline.html#options

Stanford Processors: https://stanfordnlp.github.io/stanfordnlp/processors.html

Stanford Data Objects: https://stanfordnlp.github.io/stanfordnlp/data_objects.html#document

Stanford CoreNLP integrates many of Stanford’s NLP tools, including the part-of-speech (POS) tagger, the named entity recognizer (NER), the parser, the coreference resolution system, sentiment analysis, bootstrapped pattern learning, and the open information extraction tools.

or

https://www.machinelearningplus.com/nlp/lemmatization-examples-python/

Use StanfordCoreNLP Library instead of StanfordNLP as Core is extensive and has Java support.