Welcome! Here you will find some information in order to bootstrap a "dataClay environment". You can use it to familiarize that with mF2c dataClay, to start developing applications, to explore the different components, etc.
To read the usage manual, open the pdf file. To bootstrap your environment and start testing and hacking, keep reading.
You need:
- docker Get it through https://www.docker.com/ > Get Docker
- docker-compose Quickest way to get the latest release https://github.com/docker/compose/releases
- Python 3.5.x or 2.7.x
- Java 8
Also:
- A python virtualenv for the previous interpreter is strongly suggested, but not required.
A docker-compose.yml is provided to ease the process. You can simply do:
$> cd data_management/dockers
$> docker-compose down # stop and clean previous containers
$> docker-compose up
That will download and orchestrate the different images needed. Note that, by default, the dataClay LogicModule will be listening to port 1034.
Do not Ctrl+C the process. If you want the docker-compose to be in the
background, add the flag -d (detached mode). Otherwise, just leave that
opened and proceed into a new terminal. For further options on docker-compose
process, read its documentation.
At this point, you can follow specific README files included in the different demos available from the corresponding folder.
This module contains the mf2C implementation for dataClay. Here we will find the mF2C model (classes
that represents mF2C resources) and the mF2c dm_app responsible to react to any CIMI request. For
instance, when a CIMI get arrives, the dm_app performs it using dataClay objects.
((documentation of section in progress...))
This module contains necessary code to integrate dataClay with mF2C components. In particular, here we will find specific code to translate CIMI requests to requests to dataClay dm_app. ((documentation of section in progress...))