gonito/README.md
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Gonito platform
===============
[Gonito](https://gonito.net) (pronounced _ɡɔ̃ˈɲitɔ_) is a Kaggle-like
platform for machine learning competitions (disclaimer: Gonito is
neither affiliated with nor endorsed by [Kaggle](https://www.kaggle.com)).
What's so special about Gonito:
* free & open-source (GPL), you can use it your own, in your
company, at your university, etc.
* git-based (challenges and solutions are submitted only with git).
See the home page (and an instance of Gonito) at https://gonito.net .
Installation
------------
## For development
[Gonito](https://gonito.net) is written in [Haskell](https://www.haskell.org) and uses
[Yesod Web Framework](http://www.yesodweb.com/), but all you need is
just [the Stack tool](https://github.com/commercialhaskell/stack). See https://github.com/commercialhaskell/stack
for instruction how to install Stack on your computer.
By default, Gonito uses [Postgresql](http://www.postgresql.org/), so it needs to be installed and running at your computer.
After installing Stack:
createdb -E utf8 gonito # Postgres needs to be configured
git clone --recurse-submodules git://gonito.net/gonito
cd gonito
stack setup
# before starting the build you might need some non-Haskell dependencies, e.g. in Ubuntu:
# sudo apt-get install libbz2-dev liblzma-dev libpcre3-dev libcairo-dev libfcgi-dev
stack build
stack exec yesod devel
The last command will start the Web server with Gonito (go to
http://127.0.0.1:3000 in your browser).
## With docker-compose
The easiest way to run Gonito is with docker-compose.
git clone --recurse-submodules https://gitlab.com/filipg/gonito
cd gonito
cp sample.env .env
# now you need to edit .env manually,
# in particular, you need to set up the administrator's
# password and paths to volumes for the volumes,
# cloned data ("arena"), certificates and SSH data;
# also you need to set up your certificate
# here is an easy way to do it just for local
# testing
mkdir certs
cd certs
# generating certificates for HTTPS, remember to
# set the `NGINX_CERTIFICATE_DIR` variable in `.env`
# so that it would point to `certs` here
openssl req -x509 -newkey rsa:4096 -keyout privkey.pem -out fullchain.pem -days 365 -nodes
cd ..
docker-compose up
Gonito will be available at <https://127.0.0.1/>. Of course, your
browser will complain about "Potential Security Risk" as these are
local certificates.
Gonito as backend
-----------------
On the one hand, Gonito is a monolithic Web application without front-
and back-end separated. On the other, some features are provided as
end-points, so that Gonito could be used with whatever front-end. The
documentation in the Swagger format is provided at `/static/swagger-ui/index.html`.
(see <https://gonito.net/static/swagger-ui/index.html> for this at the main instance).
Keycloak is assumed as the identity provider here for those end-points that
require authorization.
Integration with Keycloak
-------------------------
Gonito can be easily integrated with Keycloak for the back-end
end-points (but not yet for signing in Gonito as the monolithic Web
application, this feature is on the way).
1. Let's assume that you have a Keycloak instance. A simple way to run
for development and testing is: `docker run -e KEYCLOAK_USER=admin -e KEYCLOAK_PASSWORD=admin -p 8080:8080 jboss/keycloak`.
2. You need to set up the JWK key from your Keycloak instance.
Go to `https://<KEYCLOAK-HOST>/auth/realms/<KEYCLOAK-REALM>/protocol/openid-connect/certs`
and copy the contents of the key from the JSON the (key/0 element
not the whole JSON!).
3. Create `gonito` client in Keycloak (_Clients_ / _Create_).
4. Set _Valid Redirect URIs_ for the `gonito` client in Keycloak (e.g. simply add `*` there).
5. Set _Web Origin_ for the `gonito` client in Keycloak (e.g. simply add `*` there).
6. Set `JSON_WEB_KEY` variable to the content of the JWK key (or `GONITO_JSON_WEB_KEY` when using docker-compose)
and run Gonito.
If you create a new user, you need to run `/api/add-info` GET
end-point. No parameters are needed it just read the user's data from
the token and adds a record to the Gonito database.
You can simulate a front-end by going to `/static/test-gonito-as-backend.html`.
Gonito & git
------------
Gonito uses git in an inherent manner:
* challenges (data sets) are provided as git repositories,
* submissions are uploaded via git repositories, they are referred to with
git commit hashes.
Advantages:
* great flexibility as far as where you want to keep your challenges
and submissions (could be external, well-known services such as
GitHub or GitLab, your local git server, let's say gitolite or Gogs, or
just a disk accessible in a Gonito instance),
* even if Gonito ceases to exist, the challenges and submissions are still available
in a standard manner, provided that git repositories (be it external or local) are
accessible,
* data sets can be easily downloaded using the command line
(e.g. `git clone git://gonito.net/paranormal-or-skeptic`), without
even clicking anything in the Web browser,
* facilitates experiment repeatability and reproducibility (at worst
the system output is easily available via git)
* tools that were used to generate the output could be linked as git subrepositories
* some challenge/submission metadata are tracked in a Gonito-independent way
(within git commits),
* copying data can be avoided with git mechanisms (e.g. when the challenge is already
cloned, downloading specific submissions should be much quicker),
* large data sets and models could be stored if needed using mechanisms such as git-annex (see below).
### Commit structure
The following flow of git commits is recommended (though not required):
* the challenge without hidden data for main test sets (i.e. files such as `test-A/expected.tsv`)
should be pushed to the `master` branch
* the hidden files (`test-A/expected.tsv`) should be added in a
subsequent commit and pushed either to the `dont-peek` branch or a
`master` branch of a separate repository (if access to the hidden
data must be more strict),
* the submissions should be committed with the `master` branch as the
parent (or at least ancestor) commit and pushed to the same
repository as the challenge data (in some user-specific branch) or any other
repository (could be user-owned repositories)
* any subsequent submissions could be derived in a natural way from other git commits
(e.g. when a submission is improved, or even two approaches are merged)
* new versions of the challenge can be committed (a challenge can be updated at Gonito)
to the `master` (and `dont-peek`) branches
See also the following picture:
![Recommended commit structure](misc/commits.png)
### git-annex
In some cases, you don't want to store challenge/submissions files simply in git:
* very large data files, textual files (e.g. `train/in.tsv` even if
compressed as `train/in.tsv.xz`)
* binary training/testing data (PDF files, images, movies, recordings)
* data sensitive due to privacy/security concerns (a scenario where it's OK to store
metadata and some files in a widely accessible repository, but some files require
limited access)
* large ML models (note that Gonito does not require models for evaluation, but still
it might be a good practice to commit them along with output files and scripts)
Such cases can be handled in a natural manner using git-annex, a git
extension for handling files and their metadata without commiting
their content to the repository. The contents can be stored at a wide
range of [special
remotes](https://git-annex.branchable.com/special_remotes/), e.g. S3
buckets, WebDAV, rsync servers.
It's up to you which files are stored in git in a regular manner and
which are added with `git annex add`, but note that if a
challenge/submission file must be stored via git-annex and are required
for evaluation (e.g. `expected.tsv` files for the challenge or
`out.tsv` files for submissions), the git-annex special remote must be
given when a challenge is created or a submission is done and the
Gonito server must have access to such a special remote.
Authors
-------
* Filip Graliński
References
----------
@inproceedings{gralinski:2016:gonito,
title="{Gonito.net - Open Platform for Research Competition, Cooperation and Reproducibility}",
author={Grali{\'n}ski, Filip and Jaworski, Rafa{\l} and Borchmann, {\L}ukasz and Wierzcho{\'n}, Piotr},
booktitle="{Branco, Ant{\'o}nio and Nicoletta Calzolari and Khalid Choukri (eds.), Proceedings of the 4REAL Workshop: Workshop on Research Results Reproducibility and Resources Citation in Science and Technology of Language}",
pages={13--20},
year=2016,
url="http://4real.di.fc.ul.pt/wp-content/uploads/2016/04/4REALWorkshopProceedings.pdf"
}