You can simply install Mars via pip:

pip install pymars

To run Mars on a single machine, there are two ways.

  • Threaded: a thread-based scheduling which is by default.

  • Local cluster: a process-based scheduling which owns the entire distributed runtime.


After installation, you can simply open a Python console and run

import mars.tensor as mt
from mars.session import new_session

a = mt.ones((5, 5), chunk_size=3)
b = a * 4
# if there isn't a local session,
# execute will create a default one first

# or create a session explicitly
sess = new_session()
b.execute(session=sess)  # run b

Local cluster

Users can start the distributed runtime of Mars on a single machine. First, install Mars distributed by run

pip install 'pymars[distributed]'

For now, local cluster mode can only run on Linux and Mac OS.

Then start a local cluster by run

import mars.tensor as mt
from mars.deploy.local import new_cluster
from mars.session import new_session

cluster = new_cluster()

# new cluster will start a session and set it as default one
# execute will then run in the local cluster
a = mt.random.rand(10, 10)

# cluster.session is the session created
(a + 1).execute(session=cluster.session)

# users can also create a session explicitly
# cluster.endpoint needs to be passed to new_session
session2 = new_session(cluster.endpoint)
(a * 2).execute(session=session2)