Atomos
Atomic primitives for Python.
Atomos is a library of atomic primitives, inspired by Java's java.util.concurrent.atomic. It provides atomic types for bools, ints, longs, and floats as well as a generalized object wrapper. In addition, it introduces atoms, a concept Clojure programmers will be familiar with.
Motivation
Mutable shared state is hard and guess what, it's ubuiquitous in Python. When working in a multi-threaded context or whenever an application is racing, locks can be a useful tool. However they can quickly become unweildy.
To address this, Atomos provides wrappers around primitives and objects which handle the locking semantics for us. These special primitives allow for writing cleaner, simpler code without having to orchestrate locks directly.
In particular Atomos introduces atoms, a new data type for managing shared mutable state. Atoms are a near-direct port of Clojure's eponymous data type. They work by wrapping a given object in compare-and-set semantics.
Installation
Atomos is available via PyPI.
$ pip install atomos
Usage
Say we have some shared state in our application. Maybe we have a chat server which holds state in memory about connected clients. If our application is threaded we will need some way of sharing this state between threads.
We can model this state as an atom. This will ensure that when multiple threads update and retrieve the state, its value is always consistent. For example:
>>> import atomos.atom as atom
>>> state = atom.Atom({'conns': 0, 'active_clients': set([])})
Our state
is an Atom
, which means we can update it using its swap
method.
This method works by taking a function which will take the existing state of
the atom and and any arguments or keyword arguments we provide it. It should
return an updated state.
For instance, as a client connects, we want to update the number of connections and the active client set. We can write a function which we can then pass to swap to safely mututate our state:
>>> def new_client(cur_state, client):
... cur_state['conns'] += 1
... cur_state['active_clients'].add(client)
... return cur_state
>>> state.swap(new_client, 'foo')
Here we have updated our state and can be sure that any other thread which may
have looked at the state only ever saw the state as it was before we called
swap
or after. However any race condition which might have existed between
incrementing the connections count and adding the client is eliminated, thanks
to our use of the atom.
Atomic Primitives
Atomos also provides atomic primitives as wrappers around int
, long
,
float
, and bool
as well as a general wrapper around any object type. We can
use these primitives to construct a thread-safe counter:
>>> import atomos.atomic
>>> counter = atomos.atomic.AtomicInteger()
>>> counter.get()
0
To increment the counter, we can call counter.add_and_get(1)
. This will
return the new value back to us, 1
.
For more complex object types we can use an AtomicReference
. For instance, we
can wrap any arbitrary class and protect updates to its value like this:
>>> class MyState(object):
... def __init__(self, foo, bar):
... self.foo = foo
... self.bar = bar
>>> state = atomos.atomic.AtomicReference(MyState(42, False))
So long as we interact with the MyState
instance via the state
wrapper, our
updates will always be protected.
Multiprocessing
Now it works with multiprocessing.
Just use the following import path:
import atomos.multiprocessing.atomic
Contribution
Contributions are welcome, please ensure PEP8 is followed and that new code is well-tested prior to making a pull request.