Tiny Actor Run-Time in Python.
The initial ideas for tartpy are copied from @dalnefre and @tristanls. At the beginning, the goal was to replicate tart.js in Python. Lately, it has diverged slightly, to experiment with the new Python asynchrony model introduced in version 3.4.
tartpy aims to be an actor library with the following features:
- it implements the pure actor model (rather than the Erlang model),
- it can be used in practical situations to express lock-free and concurrent algorithms,
- it abstracts the network transport to allow arbitrary protocols,
- it implements a capability based approach to isolate actors, using membranes (again, the ideas are due to @dalnefre and @tristanls). The semantics of membranes may differ between tartpy and tartjs.
$ pip install git+https://github.com/waltermoreira/tartpy
or clone this repository and install with python3 setup.py install:
$ git clone https://github.com/waltermoreira/tartpy $ cd tartpy $ python3 setup.py install
Run tests with:
$ python3 setup.py test
Run example with:
There is also an IPython notebook showing the basic properties of actors.
Create a ring of M actors, sending N messages around the ring:
python3 tartpy/erlang_challenge.py M N
For M = 100000 and N = 10:
Starting 100000 actor ring Construction time: 1.5192079544067383 seconds Loop times: 0.7743091583251953 seconds 0.7793149948120117 seconds 0.7702958583831787 seconds 0.7602570056915283 seconds 0.7704610824584961 seconds 0.779731035232544 seconds 0.7654228210449219 seconds 0.7625432014465332 seconds 0.7740719318389893 seconds 0.7699680328369141 seconds Average: 0.7706375122070312 seconds
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|Filename, size & hash SHA256 hash help||File type||Python version||Upload date|
|tartpy-0.2.1-py3-none-any.whl (14.5 kB) Copy SHA256 hash SHA256||Wheel||3.4||Apr 27, 2014|
|tartpy-0.2.1.tar.gz (11.2 kB) Copy SHA256 hash SHA256||Source||None||Apr 27, 2014|