Name | slurmipy JSON |
Version |
2024.0.4
JSON |
| download |
home_page | None |
Summary | A package to manage Dask clusters on SLURM systems and execute functions with Dask parallelization. |
upload_time | 2024-10-23 19:30:04 |
maintainer | None |
docs_url | None |
author | None |
requires_python | >=3.8 |
license | MIT License |
keywords |
python
slurm
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
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coveralls test coverage |
No coveralls.
|
# SlurmiPy
Run python functions on a SLURM cluster as easy as:
```
@slurm_cluster.execute
def hello_world():
print("YAY, I am running via SLURM!")
```
SlurmiPy provides a factory class for managing Dask clusters on SLURM-based systems and provides very easy exectution of python code on a SLURM cluster.
## Installation
```bash
pip install slurmipy
```
## Usage
Here iss a basic example of how to use `SlurmiPy` on NERSCs' Perlmutter Supercomputer:
```python
from slurmipy import SlurmiPy, configs
# Create a SLURM cluster with 4 jobs
slurm_cluster = SlurmiPy(jobs=4, **configs["perlmutter_shared_interactive"])
@slurm_cluster.execute
def process_data(data):
return [x**2 for x in data]
# Execute the function using the SLURM cluster
result = process_data([1, 2, 3, 4])
print(result) # Output: [1, 4, 9, 16]
```
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