What is this ?
Pyhaystack is a module that allow python programs to connect to a haystack server using semantic data model for buildings (project-haystack).
Browse a campus, building, floor... find VAV boxes, AHU units, etc. Then extract history data from them and get the results ready for analysis using pandas or your own database implementation.
Which clients are implemented ?
Actually, connection can be established with :
Connection to Niagara AX or Niagara 4 requires the nHaystack module by J2 Innovations to be installed and properly configured on your Jace. Refer to documentation of nHaystack for details.
How do I install pyhaystack ?
pip install pyhaystack
Or you can also git clone the develop branch and use
python setup.py install
Some users reported problems when installing pyhaystack using the Python version provided by their OS (Mac OS users). We recommend to try the virtual environment approach when you are unsure about the python version our modules dependencies.
Using virtual env
You can find more information on how to use virtualenv but here is a short way of making it work.
sudo pip install virtualenv mkdir your project folder cd project virtualenv venv source venv/bin/activate
Once you are in your virtual env DO NOT use sudo to pip install. (in fact, this is the part that made me think of permission issue as I read somewhere that we should never sudo pip install anything)
So now you are in your virtual env (it's in parenthesis in the console) and you
pip install requests pip install hszinc pip install pyhaystack
(note that this time you won't see any weird message when trying to install pandas and you need xcode to perform the install....) You are now able to
import hszinc hszinc.MODE_ZINC from pyhaystack.client.skyspark import SkysparkHaystackSession
What is project-haystack ?
As stated in the web site
"Project Haystack is an open source initiative to streamline working with data from the Internet of Things. We standardize semantic data models and web services with the goal of making it easier to unlock value from the vast quantity of data being generated by the smart devices that permeate our homes, buildings, factories, and cities. Applications include automation, control, energy, HVAC, lighting, and other environmental systems."
Pyhaystack is robust and will be ready for asynchronous development.
We have chosen a state machine approach with observer pattern. See the docs for more informations.
This implementation has been mostly supported by VRT and Servisys. We are hoping that more people will join us in our effort to build a well working open-source software that will open the door of building data analysis to Python users.
For analysis, we also suggest using Pint to deal with units. It will bring a lot of possibilities to pyhaystack (ex. unit conversion)