SnipTodo is a simple Todo List App just for learning.
The database used is MongoDB, along with mongoose.
Server: Express
NLP API service: Stanford CoreNLP
DB visualization: MongoDB Compass
API testing: Postman
Grammar checking: eslint
body-parser for requst parsing
React for building user interface
Immutable for state
React-Router for routing
React-Bootstrap for better front-end components
React-Router-Bootstrap, a combination of React-Router and React-Bootstrap
Redux, React-Redux as state container
Redux-DevTools for Redux inspecting
Redux-Immutable to create an equivalent function of Redux combineReducers that works with Immutable.js state.
Redux-Saga to handle async operations
2.2 Maybe you'd like a DB visualizing tool like MongoDB Compass
To run MongoDB, go to its folder and further into the bin folder, run this commend:
mongod
Go to the site and download the latest package and unzip it.
This module is where NLP services are called. Most NLP tasks are computationally intensive, so it is better practice to have a dedicated cluster just for supporting NLP tasks. And use another server/cluster for serving resource and dispatching API calls to the NLP cluster. Stanford CoreNLP is implemented with Java, and it's shipped with a server program. It's nice to access to the core by other languages, but that doesn't seem too meaningful since those are just wrappers and many of them are outdated and not maintained anymore. Thus here I just run the Java server and make API calls to it by http requests.
Stopwords removing is to some degree a domain specific task. Aside from the tokenizing scheme, the word set used is essential. That is, different word set may yield different results. Here I use a common English stopword set found online, which contains 891 words, which is quite thorough, maybe a little too thorough. See the file utils/nlp/stopwords for details.
To start the CoreNLP server, first, make sure you have JRE configured correctly. Then, go to the folder of CoreNLP and run:
java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer -port 9000 -timeout 15000
To check whether it's working, open a browser and go to http://localhost:9000/
Just download this repo. Inside its folder run the command yarn build to build. Next, check your CoreNLP server and mongod, make sure they are runing. Then, run yarn api to start the server for SnipTodo. Open up your browser and go to http://localhost:8080.
Some screenshots:
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