The real-time machine learning system powering Polis.
This part of the codebase is implemented in Clojure, a dynamic, data-driven, functional Lisp. As with any Lisp, Clojure development typically revolves around the interactive REPL. It's recommended that you use an editor plugin to connect to this REPL, letting you execute and experiment with code as you write it, display documentation, and debug all from the comfort of your favorite text editor. (See Calva for VS, Fireplace for Vim, Cider for Emacs, Cursive for IDEA, etc).
The root directory of this codebase contains docker compose infrastructure for running a complete development environment. In addition to running the rest of the system's components (database, server, client build processes, etc), it also runs the math component in tandem with an embedded nREPL. This allows you to connect to and evaluate code from within the running math worker. To use this infrastructure, run the following from the root of this repository:
docker compose -f docker-compose.yml -f docker-compose.dev.yml up
The first time you run this (or if you've edited any of the docker files, or certain other parts of the system), you may need to run this command with the --build
flag.
In general, this shouldn't be necessary if you're just working on the Clojure code itself, however.
A little while after running this, docker compose will log out a message telling you that the system has started, and that the nREPL server is running on port 18975
.
This message may get quickly swamped out by a stream of other logging messages relaying polling information (TODO: less verbose logging option).
Regardless, at this point, the system is running and can be connected to.
Most editor plugins will connect somewhat automatically if you try to evaluate code or display documentation, but you can refer to the documentation for your editor of choice if this is not the case.
To get a sense for how various parts of these system can be used, take a look at the comment block at the bottom of dev/user.clj
.
If you're not familiar with Clojure and want a fun crash course, I highly recommend Clojure for the Brave and True, a delightful introduction to the language.
If you're not using the docker compose infrastructure, you can run clj -M:dev
to get nREPL going, but this will not start math worker's processing queue (or obviously any other parts of the system).
This may be preferable if you don't need the whole system running for whatever task you're working on.
You can always manually start the polling system by manually running (runner/run!)
, as described below, as long as you have the DATABASE_URL
environment variable pointing to a database (see doc/configuration.md
)
This application uses Stuart Sierra's Component library for REPL-reloadability. Sometimes, (e.g.) evaluating a new definition of an existing function will be picked up by the system immediately without any further work. In other cases though, especially if something stateful is involved, it may be necessary to reload/restart the system.
This can be performed using a set of utility functions in the polismath.runner
namespace (generally assumed to be aliased to runner
).
To stop the system, you can use runner/stop!
, followed by namespace.repl/refresh
to reload namespaces, and runner/start!
to start the system back up.
The runner/system-reset!
function will do all of this for you automatically, but offers less flexibility in specifying configuration details in how you start the system.
While this setup is nice from the perspective of system reloadability, Stuart's Component library unfortunately requires that a lot of the core functions of the system end up having to explicitly accept an argument corresponding to their part of the system.
This ends up being somewhat annoying from the perspective of interactive development, as it requires grabbing the corresponding component out of the runner/system
map, and passing that to the function in question.
We'll soon be switching to Mount over Component, for more automated reloadability, and less hassle passing around system/component objects (see #1056).
There are also a number of commands which can be run, either locally or with docker compose run math ...
, from the root of the monorepo:
clojure -M:run --help
- print run command help (noisy; sorry)clojure -M:run export <conversation-id> -f <export-filename>.zip
- export the conversation at<conversation-id>
to the given filenameclojure -M:run update -Z <conversation-id>
- update a particular conversationclojure -M:run full
- run a full system (poller plus auxiliary task processing)- etc.
If you are exporting data, you will need to run docker compose
here with the same -f docker-compose.yml -f docker-compose.dev.yml
options as described above, so that the directory (volume) mounting in the dev configuration file will mirror the generated files over onto your local filesystem.
You can run tests by executing clojure -M:test
.
Since Clojure is slow to start though, you may find it easier to run the test-runner/-main
function (located at test/test_runner.clj
) from within your nREPL process.
There is an example of this in the dev/user.clj
file mentioned above.
There are rough units tests for most of the basic math things, and one or two higher level integration tests (presently broken).
We're looking forward to setting up clojure.spec
and some generative testing for more thorough coverage if this is something that excites you!
The system is designed around a polling mechanism which queries the database at a regular interval for new votes and moderation status. These data are then routed to a "conversation manager", an agent like thing that maintains the current state of the conversation, and orchestrates updates to the data. The reason for this particular design is that when a conversation is very active, votes can come in at a very rapid rate. Meanwhile, the time it takes to run an update increases. We need to have a way of queueing up vote and moderation data updates, so that they're ready to be processed once the last conversation update has completed.
You can see the conversation manager implementation at src/polismath/conv_man.clj
.
The docker-compose.yml
file in the root of this directory, while not yet production ready, and still containing some development time artifacts, is provided as a basis for production deployment.
Outstanding issues which need to be resolved before it would be ready include ensuring only necessary ports are exposed, etc.
The individual Dockerfile
s that make up this infrastructure can currently be used by themselves, separate from docker compose
, for deployment.
Nonetheless, if you wish to run this part of the system directly on a machine (outside of docker), the only requirements are that you:
- install Clojure.
- Setup the postgresql client (
sudo apt-get install postgresql postgresql-client
on ubuntu).
If you go this route you will want to take a look at the (see doc/configuration.md
).
Please see LICENSE