Astronomy Publication Proximity Analyzer (APPA): finds chains of collaboration using the ADS API
A web interface is live at samvankooten.net/appa, with code at appa-web.
The Astronomy Publication Proximity Analyzer (APPA) uses the ADS database to let you explore connections between authors. Given two names, APPA will find the chains of coauthorship (person A published a paper with B, who wrote a paper with C...) connecting those two names.
Using the web interface at samvankooten.net/appa is recommended, as the web interface is more fully-featured than the textual terminal output mode, and using a shared instance allows you to benefit from a pre-populated cache of ADS query results. However you can run your own instance for fun or if you plan to run very large numbers of searches for connections (i.e. in an automated fashion).
To run your own copy of APPA, you'll need to register for an access token for the ADS API. Copy local_config.sample.py to local_config.py and insert your key in the line ADS_TOKEN = "token_here".
APPA can be run locally, with output as an ASCII table of connection chains (see appa.py).
APPA can also be run as a backend for the more useful web interface, as either a Flask server (see appa_web_backend.py) or in Google Cloud (see main.py; requires additional configuration in local_config.py).
To speed up path finding and reduce the number of ADS queries, data received from ADS is cached locally. Two cache backends are provided: using the local filesystem (see cache_fs.py; the directory path used for caching data is set by cache_fs_dir in local_config.py) and using GCP Firestore (see cache_firestore.py; progress data is relayed through an App Engine instance---see progress_relay/). The choice of cache backend is made in local_config.py.