Metadata-Version: 1.1
Name: tasa
Version: 0.2.2
Summary: A simple framework for distributed task workflow using redis.
Home-page: https://github.com/PaulMcMillan/tasa
Author: Paul McMillan
Author-email: paul@mcmillan.ws
License: Simplified BSD
Description: ========
        T-A S.A.
        ========
        
        A simple framework for distributed task workflow using redis. Designed
        to be easily extensible with code, rather than excessively featureful
        out of the box.
        
        Getting Started
        ---------------
        
        Tasa requires a version of Python 2.7. If you're using an older
        version, now is an excellent time to upgrade. If you're running Python
        3, compatibility patches are welcome.
        
        Quickstart example for Debian:
        
         #) sudo apt-get install redis-server python-pip nmap
         #) sudo pip install -U tasa
         #) wget https://raw.github.com/PaulMcMillan/tasa/master/examples/tnmap.py
         #) mkdir out
         #) tasa tnmap:Runner &
         #) tasa tnamp:Results &
         #) python tnmap.py 10.0.0.0/24
        
        This quickstart installs tasa, downloads an example script for
        distributed nmap, runs one task worker and one results worker, and
        then inserts a job to scan a portion of your local net.
        
        To actually use this example to distribute a task, on each worker node:
        
         #) sudo apt-get install python-pip nmap
         #) sudo pip install -U tasa
         #) wget https://raw.github.com/PaulMcMillan/tasa/master/examples/tnmap.py
         #) export REDIS_ADDRESS=redis://username:password@example.org:6379/0
         #) tasa tnmap:Runner
        
        Then run the results worker and inject jobs from the master
        machine. Experiment with changing values in the script - the example
        is actually general enough to run any process, not just nmap.
        
        Don't forget to configure your redis server to listen on an ip
        accessible to your clients, and for the love of Kaminsky, set a
        password even if you are on a private network. If you're on an
        untrusted network, you're responsible for encryption - either tunnel
        over an SSH port forward, or wrap redis in TLS using stud/stunnel.
        
        How does it work?
        -----------------
        
        Tasa is primarily a thin framework to help you build composable work
        flows. Break your problem into small chunks, run workers on several
        machines, and insert jobs into the worker's input queue, and consume
        them from the output.
        
        FAQ
        ---
        
        * I get a traceback with "redis.exceptions.ResponseError: operation
          not permitted"
        
          Did you remember to set `REDIS_ADDRESS` env var? This will happen if
          you added a redis password and did not set a connection string.
        
        * What version of redis-server do I need?
        
          Tasa is developed with redis 2.6.7. Older versions aren't explicitly
          tested, though the 2.4 branch will probably work with reduced
          functionality. Newer versions should work without trouble.
        
        Security
        --------
        
        The security of tasa depends entirely on how you use it. If you use a
        password and tunnel redis communications over an encrypted and
        authenticated transport, you'll do pretty well. The easiest way to do
        this is to use SSH port forwarding to transport redis traffic. You can
        also put stud in front of redis to do TLS, though this is more
        complex.
        
        The author uses tasa workers primary on disposable cloud hosts.
        
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
