hyperstream 0.3.8
Hyperstream is a large-scale, flexible and robust software package for processing streaming data
License: MIT

.. figure:: https://cdn.rawgit.com/IRC-SPHERE/HyperStream/dfbac332/hyperstream.svg
   :alt: HyperStream logo

   HyperStream logo

HyperStream
===========

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Hyperstream is a large-scale, flexible and robust software package for
processing streaming data.

-  HyperStream `homepage <https://irc-sphere.github.io/HyperStream/>`__
-  Tutorial
   `notebooks <http://nbviewer.jupyter.org/github/IRC-SPHERE/HyperStream/blob/master/examples/index.ipynb>`__
-  Gitter `chat room <https://gitter.im/IRC-SPHERE-HyperStream/Lobby>`__
-  Developer
   `documentation <http://hyperstream.readthedocs.io/en/latest/>`__

Hyperstream overcomes the limitations of other computational engines and
provides high-level interfaces to execute complex nesting, fusion, and
prediction both in online and offline forms in streaming environments.
Although developed specifically for SPHERE, Hyperstream is a general
purpose tool that is well-suited for the design, development, and
deployment of algorithms and predictive models in a wide space of
sequential predictive problems.

This software has been designed from the outset to be
domain-independent, in order to provide maximum value to the wider
community. Key aspects of the software include the capability to create
complex interlinked workflows, and a computational engine that is
designed to be "compute-on-request", meaning that no unnecessary
resources are used.

Installation
============

Docker images
-------------

If you do not want to install all the packages separately you can use
our Docker bundle available
`here <https://github.com/IRC-SPHERE/Hyperstream-Dockerfiles>`__.

Local machine
-------------

Install via pip

::

    pip install hyperstream
    python -c 'from hyperstream import HyperStream'

To get the latest version

::

    pip install -U git+git://github.com/IRC-SPHERE/HyperStream.git#egg=hyperstream
    pip install -r requirements.txt

Or clone the repository

.. code:: bash

    git clone git@github.com:IRC-SPHERE/HyperStream.git
    cd HyperStream
    virtualenv venv
    . venv/bin/activate
    pip install -r requirements.txt
    python -c 'from hyperstream import HyperStream'

Additionally, one of the requirements to run Hyperstream is a MongoDB
server. By default, Hyperstream tries to connect to the port 27017 on
the localhost.

To access via a cloud provider, you might try mLab, MongoDB Atlas, or
search for a different one. If you are using mLab, here are a few notes:

-  Set up an account via the mLab web site instructions. When asked to
   pick a server type (e.g. Amazon, Google, etc) you can just choose
   free option of 500MB. This is more than enough to get started.
-  mLab will ask you to create a database; any name is fine, but make
   sure you write down what it is.
-  After creating a database, note that you’ll need to create at least
   one database user in order to access the database.
-  You can test your database connection using MongoDB’s built-in
   command line tools

To install MongoDB locally go to the `official
documentation <https://docs.mongodb.com/manual/installation/>`__. E.g.
in a Debian OS it is possible to install with the following command

.. code:: bash

    sudo apt-get install mongodb

Once the MongoDB server is installed, it can be started with the
following command

.. code:: bash

    service mongod start

If installing MongoDB on OSX

.. code:: bash

    brew install mongodb

then

.. code:: bash

    ln -sfv /usr/local/opt/mongodb/*.plist ~/Library/LaunchAgents

run MongoDB service with

.. code:: bash

    launchctl load ~/Library/LaunchAgents/homebrew.mxcl.mongodb.plist

Running tests
=============

Run the following command

::

    nosetests

Note that for the MQTT logging test to succeed, you will need to have an
MQTT broker running (e.g. Mosquitto). For example:

::

    docker run -ti -p 1883:1883 -p 9001:9001 toke/mosquitto

or on OSX you will need pidof and mosquitto:

::

    brew install pidof
    brew install mosquitto
    brew services start mosquitto

Tutorials
=========

The following tutorials show how to use HyperStream in a step-by-step
guide.

-  `Tutorial 1:
   Introduction <https://nbviewer.jupyter.org/github/IRC-SPHERE/HyperStream/blob/master/examples/tutorial_01.ipynb>`__
-  `Tutorial 2: Creating
   tools <https://nbviewer.jupyter.org/github/IRC-SPHERE/HyperStream/blob/master/examples/tutorial_02.ipynb>`__
-  `Tutorial 3: Stream
   composition <https://nbviewer.jupyter.org/github/IRC-SPHERE/HyperStream/blob/master/examples/tutorial_03.ipynb>`__
-  `Tutorial 4: Real-time
   streams <https://nbviewer.jupyter.org/github/IRC-SPHERE/HyperStream/blob/master/examples/tutorial_04.ipynb>`__
-  `Tutorial 5:
   Workflows <https://nbviewer.jupyter.org/github/IRC-SPHERE/HyperStream/blob/master/examples/tutorial_05.ipynb>`__

Running the tutorials in a docker container
-------------------------------------------

It is possible to run all the tutorials in your own machine ussing
Docker containers defined in
`IRC-SPHERE/Hyperstream-Dockerfiles <https://github.com/IRC-SPHERE/HyperStream-Dockerfiles>`__.
You can do that by running the following commands:

.. code:: bash

    git clone https://github.com/IRC-SPHERE/Hyperstream-Dockerfiles.git
    cd Hyperstream-Dockerfiles
    docker-compose -f docker-compose-tutorials.yml -p hyperstream-tutorials up

And then open the url http://0.0.0.0:8888/tree in a web-browser

Running the tutorials in the cloned folder
------------------------------------------

To run the tutorials in the cloned repository you will need to install
additional dependencies. First you should activate the virtual
environment and installed the general requirements to run HyperStream
following the instructions above. After that, install the dependencies
for the tutorial with

.. code:: bash

    pip install -r requirements_tutorial.txt

and go to the experiments folder

.. code:: bash

    cd experiments

And run a Jupyter notebook

.. code:: bash

    jupyter notebook

Now you can follow the instructions from the first tutorial.

Simple use-case
---------------

.. code:: python

    from hyperstream import HyperStream, StreamId, TimeInterval
    from hyperstream.utils import utcnow, UTC
    from datetime import timedelta

    hs = HyperStream(loglevel=20)
    M = hs.channel_manager.memory
    T = hs.channel_manager.tools
    clock = StreamId(name="clock")
    clock_tool = T[clock].window().last().value()
    ticker = M.get_or_create_stream(stream_id=StreamId(name="ticker"))
    now = utcnow()
    before = (now - timedelta(seconds=30)).replace(tzinfo=UTC)
    ti = TimeInterval(before, now)
    clock_tool.execute(sources=[], sink=ticker, interval=ti, alignment_stream=None)
    list(ticker.window().tail(5))

The last list contains

.. code:: python

    [StreamInstance(timestamp=datetime.datetime(2017, 7, 27, 10, 33, 45, tzinfo=<UTC>), value=datetime.datetime(2017, 7, 27, 10, 33, 45, tzinfo=<UTC>)),
     StreamInstance(timestamp=datetime.datetime(2017, 7, 27, 10, 33, 46, tzinfo=<UTC>), value=datetime.datetime(2017, 7, 27, 10, 33, 46, tzinfo=<UTC>)),
     StreamInstance(timestamp=datetime.datetime(2017, 7, 27, 10, 33, 47, tzinfo=<UTC>), value=datetime.datetime(2017, 7, 27, 10, 33, 47, tzinfo=<UTC>)),
     StreamInstance(timestamp=datetime.datetime(2017, 7, 27, 10, 33, 48, tzinfo=<UTC>), value=datetime.datetime(2017, 7, 27, 10, 33, 48, tzinfo=<UTC>)),
     StreamInstance(timestamp=datetime.datetime(2017, 7, 27, 10, 33, 49, tzinfo=<UTC>), value=datetime.datetime(2017, 7, 27, 10, 33, 49, tzinfo=<UTC>))]

HyperStream Viewer
==================

The `HyperStream
Viewer <https://github.com/IRC-SPHERE/HyperStreamViewer>`__ is a
python/Flask web-app for interacting with HyperStream. In order to keep
HyperStream to a minimum, this web-app is released as a separate
repository that takes the core as a dependency.

License
=======

This code is released under the `MIT
license <https://github.com/IRC-SPHERE/HyperStream/blob/master/LICENSE>`__.

Acknowledgements
================

This work has been funded by the UK Engineering and Physical Sciences
Research Council (EPSRC) under Grant
`EP/K031910/1 <http://gow.epsrc.ac.uk/NGBOViewGrant.aspx?GrantRef=EP/K031910/1>`__
- "SPHERE Interdisciplinary Research Collaboration".

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