https://github.com/eth-cscs/ipcluster_magic
Magic commands to support running MPI python code as well as multi-node Dask workloads on Jupyter notebooks.
https://github.com/eth-cscs/ipcluster_magic
dask-distributed ipyparallel jupyter-notebook mpi4py
Last synced: 9 months ago
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Magic commands to support running MPI python code as well as multi-node Dask workloads on Jupyter notebooks.
- Host: GitHub
- URL: https://github.com/eth-cscs/ipcluster_magic
- Owner: eth-cscs
- Created: 2019-10-09T12:59:39.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-02-24T12:55:19.000Z (almost 3 years ago)
- Last Synced: 2024-10-12T09:09:03.424Z (over 1 year ago)
- Topics: dask-distributed, ipyparallel, jupyter-notebook, mpi4py
- Language: Python
- Homepage: https://eth-cscs.github.io/ipcluster_magic/
- Size: 364 KB
- Stars: 4
- Watchers: 8
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# IPyCluster Magics
Magic commands to support running MPI python code as well as multi-node Dask workloads on Jupyter notebooks.
## Installation
This package is called `ipcmagic-cscs` in [PyPI](https://pypi.org/project/ipcmagic-cscs). It can be installed with
```bash
pip install ipcmagic-cscs[dask]
```
This installs all `ipcmagic-cscs` dependencies including Dask (`dask[complete]`).
If the Dask support is not needed, `ipcmagic-cscs` can be installed with
```bash
pip install ipcmagic-cscs
```
which doesn't include the installation of Dask and it's dependencies.
## Usage
See examples [here](https://github.com/eth-cscs/ipcluster_magic/tree/master/examples).