TideHunter

HTTP streaming toolbox with flow control, written in Python.

Background

This project was born for a need in my day time job at Addictive Mobility (Addictive Tech Corp.). Before this project was open sourced, it went through two major overhauls. I briefly mentioned the techniques I used in previous versions in a blog post.

Highlights

• Accurate quota limit - total control over your stream quota.
• An instant off switch - when sht hits the fan and you don't want to crash your process.
• Redis backed control tools - semi-persisted, fast, and scalable.
• Core mechanisms based on the solid cURL and PycURL - inherits the built-in goodness (gzip support and more).
• OAuth support based on python-oauth2 - see this demo in action.

Installation

$ pip install tidehunter

Or to update:

$ pip install tidehunter --upgrade

Note: the package will install all Python dependencies for you. However you need to have both cURL (the headers from dev package are also required for PycURL) and Redis installed.

Usage

Example 1 (with limit):

from tidehunter.stream import StateCounter, Queue, Hunter

# The state machine and record counter (state counter)
sc = StateCounter(key='demo_sc', host='localhost', port=6379, db=0)

# The data queue
q = Queue(key='demo_q', host='localhost', port=6379, db=0)

# The Hunter!
conf = {
    'url': 'https://httpbin.org/stream/100',
    'limit': 5,  # desired limit
    'delimiter': '\n'
}
h = Hunter(conf=conf, sc=sc, q=q)

# Start streaming
h.tide_on()

# Consume the data which should be in the data queue now
while len(q):
    print q.get()  # profit x 5

# You can re-use the same Hunter object, and add a one-time limit
h.tide_on(limit=1)  # this time we only want one record

assert len(q) == 1  # or else there's a bug, create an issue!

print q.get()  # more profit

Example 2 (without limit):

Assume you have a process running the following code:

from tidehunter.stream import StateCounter, Queue, Hunter

# The state machine and record counter (state counter)
sc = StateCounter(key='demo_sc', host='localhost', port=6379, db=0)

# The data queue
q = Queue(key='demo_q', host='localhost', port=6379, db=0)

# The Hunter!
conf = {'url': 'https://some.forever.streaming.api.endpoint'}
h = Hunter(conf=conf, sc=sc, q=q)

# Start streaming, FOREVA
h.tide_on()

You can delegate the responsibility of data consumption and stream control to another process:

from tidehunter.stream import StateCounter, Queue

# The SAME state machine and record counter (state counter)
sc = StateCounter(key='demo_sc', host='localhost', port=6379, db=0)

# The SAME data queue
q = Queue(key='demo_q', host='localhost', port=6379, db=0)

while sc.started():
    data = q.get()  # dequeue and
    # ...do something with data

    if SHT_HITS_THE_FAN:
        sc.stop()  # instant off switch, end of while loop, as well as the process above

See demo for more examples.

Test (Unit Tests)

The tests are done through Travis-CI already.

However, running the full test within your local environment is just three lines, provided that you have Redis installed and running:

$ pip install -r requirements.txt
$ pip install -r test_requirements.txt
$ nosetests --with-coverage --cover-package=tidehunter

Documentation

Coming up very soon!

License

Copyright (c) 2013 Addictive Tech Corp., under The MIT License (MIT). See the full LICENSE.