Get Started

pip install ezRay

Quick Start Guide

from ezRay import MultiCoreExecutionTool
import ray

# configure ezRay
instance_metadata:dict = {
    'num_cpus': 4,              # number of cpus to use
    'num_gpus': 0,              # number of gpus to use
    'address': None,            # remote cluster address. None for local.
    }

# setup ezRay
MultiCore = MultiCoreExecutionTool(instance_metadata = instance_metadata)

# launch ray dashboard (optional)
MultiCore.launch_dashboard()

# define any task
def do_something(foo:int, bar:int) -> int:
    return foo + bar

# or use a ray.remote object
@ray.remote
def do_something_remote(foo:int, bar:int) -> int:
    return foo - bar

# prepare your data in a dictionary. They keys work as identifiers, while the values should be dictionaries matching the function signature.
data = {
    1:{'foo' : 0, 'bar' : 1},
    2:{'foo' : 1, 'bar' : 2},
    3:{'foo' : 2, 'bar' : 3}
    }

# pass the data to ezRay
MultiCore.update_data(data)

# run the task
MultiCore.run(do_something)

# get the results
results_first_task = MultiCore.get_results()

## prepare for the next run
# this will automaticall archive current results
# alternatively you can use MultiCore.archive_results()
MultiCore.next()

# run a second task
MultiCore.run(do_something_remote)

# get current results
results_second_task = MultiCore.get_results()

# get the archived results
archive = MultiCore.get_archive()

Documentation

Pending, sry. No time. However, check out the sandbox in the examples folder or the docstrings in the code.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ezray-1.1.11.tar.gz (15.0 kB view details)

Uploaded Jun 17, 2026 Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

ezray-1.1.11-py3-none-any.whl (16.7 kB view details)

Uploaded Jun 17, 2026 Python 3

File details

Details for the file ezray-1.1.11.tar.gz.

File metadata

Download URL: ezray-1.1.11.tar.gz
Upload date: Jun 17, 2026
Size: 15.0 kB
Tags: Source
Uploaded using Trusted Publishing? No
Uploaded via: poetry/1.8.5 CPython/3.9.9 Windows/10

File hashes

Hashes for ezray-1.1.11.tar.gz
Algorithm	Hash digest
SHA256	`87d84ec58e1785c414466bc52fc228d282de016be8387ea059cbf4dddf658679`
MD5	`a677f1aa8e50881cd55dcc74a3654e49`
BLAKE2b-256	`2792fb223ae0c7b9791dcd8eb711cb0a06f636fbb86547bd631ac82a1d29d0de`

See more details on using hashes here.

File details

Details for the file ezray-1.1.11-py3-none-any.whl.

File metadata

Download URL: ezray-1.1.11-py3-none-any.whl
Upload date: Jun 17, 2026
Size: 16.7 kB
Tags: Python 3
Uploaded using Trusted Publishing? No
Uploaded via: poetry/1.8.5 CPython/3.9.9 Windows/10

File hashes

Hashes for ezray-1.1.11-py3-none-any.whl
Algorithm	Hash digest
SHA256	`1c654996cf5f2cc53b406942a56792776595189e07cdaae2aa1203cbcd70f9d9`
MD5	`284a59b073cb86dd8bab1c7e2ea8f414`
BLAKE2b-256	`1593e712f33f5cb3d12c4cc24c845165d314f98f6a4d9711c48bfd6a920f8c36`