cloudknot - Release v0.6.1

v0.5.3 (February 03, 2022)

• DOC: Update minimal required permissions (#302)
• BF: Use separate cloudformation templates for gpu jobs (#299)

- Python
Published by github-actions[bot] over 2 years ago

cloudknot - Release v0.6

v0.5.3 (February 03, 2022)

• DOC: Update minimal required permissions (#302)
• BF: Use separate cloudformation templates for gpu jobs (#299)

- Python
Published by github-actions[bot] over 2 years ago

cloudknot - Release v0.5.3

v0.5.3 (February 03, 2022)

• DOC: Update minimal required permissions (#302)
• BF: Use separate cloudformation templates for gpu jobs (#299)

- Python
Published by github-actions[bot] over 4 years ago

cloudknot - Release v0.5.2

v0.5.2 (November 17, 2021)

• ENH: Allow user to set number of GPUs for each job (#295)
• Use boto3 to get valid ec2 instance types (#284)
• Allow longer names for knots and fail earlier if they are too long (#282)

- Python
Published by github-actions[bot] over 4 years ago

cloudknot - Release v0.5.1

v0.5.1 (March 27, 2021)

• ENH: Add nocache option to DockerImage.build() (#278)
• ENH: Add option to remove version pinning from pip requirements file (#277)
• FIX: Use default pickle protocol even for cloudpickle (#273)
• ENH: Add --ignore-installed option to ck.DockerImage (#275)
• ENH: Remove six (#274)

- Python
Published by github-actions[bot] about 5 years ago

cloudknot - Release v0.5.0

v0.5.0 (December 23, 2020)

• FIX: Windows carriage return (#268)
• FIX: Allow user to specify name for new DockerImage instances (#265)
• ENH: Enforce maximum name length for Pars and Knot (#263)
• ENH: Automatically set job_type in knot.map() by inspecting the length of the arguments. (#261)
• FIX: Require object names to conform to AWS URI regex (#260)
• Add functions to clean up the cloudknot config file (#250)
• [ENH] Improve AWS resource tagging and allow user to provide custom tags (#249)
• Test Job Definition Name (#246)

- Python
Published by github-actions[bot] over 5 years ago

cloudknot - Release v0.4.2

v0.4.2 (July 24, 2020)

• Remove config files for services we no longer use (#244)
• Create a better release message (#243)
• WIP: Fix zenodo metadata (#241)
• Use relative paths in docbuild.yml (#242)
• Allow user to refresh function for existing DockerImage (#240)
• Code style improvement suggestions from codacy (#237)
• Add publish_release script (#238)
• Add citation info to docs and update README badges (#236)
• Add back tags and use repo URI not image URI (#235)
• Adds some tools for maintenance. (#232)
• Update setup.py URL and bump version (#229)
• Fix volume_size and PARS policies issues (#233)

- Python
Published by github-actions[bot] almost 6 years ago

cloudknot - Release v0.4.1

refs/tags/v0.4.1 (July 24, 2020)

- Python
Published by github-actions[bot] almost 6 years ago

cloudknot - Cloudknot v0.3.1

Changes

• Fix bug that did not accept policy names in Knot and Pars initialization. Now users can supply either IAM policy ARNs or IAM policy names.

- Python
Published by richford almost 8 years ago

cloudknot - Cloudknot v0.3

Changes

• Use Cloudformation to manage resources on AWS

- Python
Published by richford almost 8 years ago

cloudknot - Cloudknot v0.2.1

Changes

• Bugfix for codecontext in cloudknot/_init.py

- Python
Published by richford over 8 years ago

cloudknot - Cloudknot v0.2

Changes

• All cloudknot docker images are now housed in a single unified ECR repository
• Created command line configuration tool cloudknot configure
• Cloudknot now checks for configuration and a running docker daemon on import

- Python
Published by richford over 8 years ago

cloudknot - Cloudknot v0.1.2

Changes

• Updated package data to include template files that cloudknot needs to run.

- Python
Published by richford over 8 years ago

cloudknot - Cloudknot v0.1.1

Welcome to cloudknot, a python library that lets you run arbitrary python functions on AWS Batch.

It's as easy to use as:

``` import cloudknot as ck

def myawesomefunc(b): """Here is a function I want to run on AWS Batch""" # Always import dependencies within the function import numpy as np

x = np.random.normal(0, b, 1024)
A = np.random.normal(0, b, (1024, 1024))

return np.dot(A, x)

Create a Knot, the primary object in cloudknot (read the docs)

knot = ck.Knot(name='myawesomefunc', func=myawesomefunc)

Submit 20 jobs (each one will run on AWS Batch and then send the results back here)

result_futures = knot.map(range(1, 20)) ```

You can find out more at: documentation: https://richford.github.io/cloudknot/ GitHub repo: https://github.com/richford/cloudknot

Give it a whirl. If you like it, star the repo on GitHub. And if you use it in your research, please let us know. We hope it makes your research computing experience easier.

- Python
Published by richford over 8 years ago