Story discovery engine for the Counterdata Network. Grabs relevant stories from various APIs, runs them against bespoke classifier models, post results to a central server.
It is good to periodically update our general dependencies to the latest versions, so we don't accrue too much technical debt from older security or other problems in them. This task involves checking the latest version of each item in requirements.txt, updating them to the latest (with x.x.* so we don't specify bug fix versions), and then running the fetch scripts and workers to make sure it all still works the same. For major version updates it is smart to check release notes about any backwards upgrading instructions.
Some exceptions are noted in comments in there so do not upgrade those - scikit-learn and tensorflow libraries.
It is good to periodically update our general dependencies to the latest versions, so we don't accrue too much technical debt from older security or other problems in them. This task involves checking the latest version of each item in
requirements.txt
, updating them to the latest (withx.x.*
so we don't specify bug fix versions), and then running the fetch scripts and workers to make sure it all still works the same. For major version updates it is smart to check release notes about any backwards upgrading instructions.Some exceptions are noted in comments in there so do not upgrade those -
scikit-learn
andtensorflow
libraries.