- Using Arxiv API to search for papers
- Using Semantic Scholar to get influence details. Not all papers have matching records there.
- Container endpoint: http://scienceinfluencers-3bb32e13-1.c46e36e7.cont.dockerapp.io/
- Docker image built on the AWS staging machine
- Using docker cloud to proxy container hosting on AWS
- Image pushed to Docker hub repository: https://hub.docker.com/r/baddar/scienceinfluencers/
- Docker cloud linked with github for continuous intergration. Unfortunately building on docker hub is very unstable. However I have tried to push updates and it automatically triggers a new image build and deply. This also can be controlled by tagging the image and branching on github (To build a staging container for instance)
- Discarded docker cloud build and used an AWS instance to build the image then push it to docker hub
- Used google clould shell (Tutorial here) to build the image and push it to GCP then create a Kubernetes cluster. Still in progress
- Arxiv API: Outputs XML. I parsed it into a pandas dataframe and convert it to HTML, then manually inject hrefs for the URLs as pandas cannot do that
- Using JQuery and DataTables to add sort and pagination to the results
- No database implementation
- Google OAuth 2.0 authentication implemented for login.
- Code in main.py. Google code uses auth.py
- Using Docker Cloud to build my docker image.
- Using Alpine Linux image at first. Since Pandas and many of its dependencies has to be built from source.
- Rearranging results. Expanding summary. More UX etc.
- Adding Timeline: Histogram trends over time
- Include twitter influence analysis. Semantic scholar does this but no API was exposed
- Database
- Add more ArXiv query capabilities: Search by title, author, etc
- Completing Kubernetes cluster configuration