spaCy-streamlit: Empower your NLP visualization

spaCy?

spaCy (opens in a new tab) is an open-source NLP module by explosion.ai (opens in a new tab). Unlike nltk module, which is aimed at research purposes, this targets production-ready codes. As such, it is powered with Cython, delivering faster performance than its counterpart (not POS tagging, though), also with more straightforward functionalities to streamline advanced NLP works.

streamlit

This is my favorite Python module, with which you can show your works ranging from Data Visualization to Machine Learning projects or NLPs. Unlike its competitor, Dash by plot.ly team or ShinyR, it doesn't require you to write boilerplate codes for the document structure. Even then, the resulting markup looks more pretty beautiful. If it doesn't I wouldn't have started using this.

spacy-streamlit

streamlit has several modules which can enhance it with added functionalities. As spaCy supports useful language analyses which can be better understood by visualizations, it has the graphing capabilities within it. And, spacy-streamlit streamline these functions, from entering your desired sentences to be analyzed to the analyzed results. This is beneficial if you want to dissect the sentence of its dependency among its components, i.e., how each verb or noun is connected to each other.

How to start?

While you can install the module in your computer, it isn't necessary to test it. You can go to https://explosion.ai/demos/displacy (opens in a new tab) to test it or you can install.

pip install spacy-streamlit

** Image from https://spacy.io/universe/project/spacy-streamlit (opens in a new tab)