HyperStream Tutorial 4: Real-time streams

In this tutorial, we show how to create a new plugin that collects real-time data ussing a publicly available API. In this case, we use the Environment Agency flood-monitoring API.

Creating a plugin tool to use the API

1. Create a folder in plugins

First of all, we need to create a new folder to contain the new tool. The new folder needs to be in the folder plugins, in this example plugins/example/tools/environment_data_gov_uk/. Also, we need to create an __init__.py file in every subfolder.

    |- __init__.py
    |- example/
        |- __init__.py
        |- tools/
            |- __init__.py
            |- environment_data_gov_uk
                |- __init__.py
                |- 2017-06-21_v0.0.1.py

2. Write the plugin in Python

As we have seen in a previous tutorial, we can create a new plugin in Python, in this case the code of the plugin ./plugins/example/tools/environment_data_gov_uk/2017-06-21_v0.0.1.py uses the API to query only one of the water readings for the specified interval of time:

from datetime import datetime
from datetime import datetime, timedelta

from hyperstream import Tool, StreamInstance, StreamInstanceCollection
from hyperstream.utils import check_input_stream_count
from hyperstream.utils import UTC

from dateutil.parser import parse

import urllib
import urllib2
import json

# this uses Environment Agency flood and river level data from the real-time
# data API (Beta)
# For questions on the APIs please contact [email protected],
# a forum for announcements and discussion is under consideration.
class EnvironmentDataGovUk(Tool):
    def __init__(self, station):
        self.station = station
        super(EnvironmentDataGovUk, self).__init__()

    def _execute(self, sources, alignment_stream, interval):
        startdate = interval[0].strftime("%Y-%m-%d")
        enddate = interval[1].strftime("%Y-%m-%d")

        url = "https://environment.data.gov.uk/flood-monitoring/id/stations/{}/readings".format(self.station)
        values = {'startdate' : startdate,
                  'enddate' : enddate}
        url_parameters = urllib.urlencode(values)

        full_url = url + '?' + url_parameters
        response = urllib2.urlopen(full_url)
        data = json.load(response)

        for item in data['items']:
            dt = parse(item.get('dateTime'))
            if dt in interval:
                value = float(item.get('value'))
                yield StreamInstance(dt, value)

3. Add HyperStream configuration

Now, it is necessary to add information about this plugin into the hyperstream_config.json. In particular, we need to add the following information in the plugin section:

  • channel_id_prefix: This is to create Channels (explained in another tutorial).
  • channel_names: A list of available Channels
  • path: path to the new plugin
  • has_tools: If the new plugin has tools
  • has_assets: If it contains folders or files that are needed by the plugin

Next, we have an example of an configuration file with the new plugin:

    "mongo": {
        "host": "localhost",
        "port": 27017,
        "tz_aware": true,
        "db": "hyperstream"
    "plugins": [{
        "channel_id_prefix": "example",
        "channel_names": [],
        "path": "plugins/example",
        "has_tools": true,
        "has_assets": false
    "online_engine": {
        "interval": {
            "start": -60,
            "end": -10
        "sleep": 5,
        "iterations": 100


this uses Environment Agency flood and river level data from the real-time data API (Beta)

In [1]:
%load_ext watermark

import sys
from datetime import datetime
from datetime import datetime, timedelta

sys.path.append("../") # Add parent dir in the Path

from hyperstream import HyperStream, StreamId
from hyperstream import TimeInterval
from hyperstream.utils import UTC

from utils import plot_high_chart

%watermark -v -m -p hyperstream -g
CPython 2.7.6
IPython 5.3.0

hyperstream 0.3.0-beta

compiler   : GCC 4.8.4
system     : Linux
release    : 3.19.0-80-generic
machine    : x86_64
processor  : x86_64
CPU cores  : 4
interpreter: 64bit
Git hash   : f0e911526041b91fe7999a8968c80618d410e741

Select the water Station

For our example, we will query a water station called Bristol Avon Little Avon Axe and North Somerset St. This station has the station number 531118. It is possible to select another station by changing the station_number; a list of 50 other possible stations can be found following this link.

In [2]:
station_number = "531118"
station_name = "Bristol Avon Little Avon Axe and North Somerset St"

Tool and Stream

First we will create a Stream to store the data and an instance of the new tool.

In [3]:
hs = HyperStream(loglevel=20)
print hs

environment_stream = hs.channel_manager.memory.get_or_create_stream("environment")
environment_tool = hs.plugins.example.tools.environment_data_gov_uk(station=station_number)
HyperStream version 0.3.0-beta, connected to mongodb://localhost:27017/hyperstream, session id <no session>

Execute the tool

Now we will specify an interval of time for which we want the water levels. In this particular case we will ask for the last 7 days. Then, we can execute the tool for the specified interval of time. The result will be stored in the specified Stream.

In [4]:
now = datetime.utcnow().replace(tzinfo=UTC)
before = (now - timedelta(weeks=1)).replace(tzinfo=UTC)
ti = TimeInterval(before, now)

environment_tool.execute(sources=[], sink=environment_stream, interval=ti)


Now we can visualize all the data stored in the stream

In [5]:
my_time, my_data = zip(*[(key.__str__(), value) for key, value in environment_stream.window().items()])

plot_high_chart(my_time, my_data, type="high_stock", title=station_name, yax='meters')
Bristol Avon Little Avon Axe and North Somerset St
In [ ]: