mlops

Describe the bug
data docs columns shrink to 1 character width with long query

To Reproduce
Steps to reproduce the behavior:

1. make a batch from a long query string
2. run validation
3. render result to data docs
4. See screenshot
   <img width="1525" alt="Data_documentation_compiled_by_Great_Expectations" src="https://user-images.githubusercontent.com/928247/103230647-30eca500-4

With a config like this

{
    "METAFLOW_DATASTORE_SYSROOT_S3": "s3://mf-test/metaflow/",
}

(note a slash after METAFLOW_DATASTORE_SYSROOT_S3)

metaflow.S3(run=self).put* produces double-slashes like here:

s3://mf-test/metaflow//data/DataLoader/1630978962283843/month=01/data.parquet

The trailing slash in the config shouldn't make a difference

Description

In Kedro Viz 3.14.0 we released the ability to automatically reload viz as the user types their code. The full PR for this can be seen here. Whilst this is documented on the kedro-viz github, it's not mentioned anywhere in the core documentation.

Possible Implementation

It would make sense to add the following g

🚨🚨 Feature Request

• Related to an existing Issue
• A new implementation (Improvement, Extension)

If your feature will improve HUB

Need a way to check if a dataset already exists.

hub.empty throws an error if a dataset exists and hub.load throws an error if the dataset does not exist.

Need a way to check if a dataset already exists without throwing a

Use case

Polyaxon tracking can be used to automatically log all information generated by Ludwig.

We should probably think about adding support for Polyaxon's tracking module in Ludwig contrib.

For SC Operator it may be a good idea to generate CRD manifests from inside a docker container.
This should provide reproducible generation step and avoid "produces different output on my machine" issues.

Linter should also fail if generation of manifests produce diff with the commited version.

What steps did you take

Code gets stuck in infinite loop is SageMaker training job gets stopped (unhandled use case)

What happened:

https://github.com/kubeflow/pipelines/blob/master/components/aws/sagemaker/train/src/sagemaker_training_component.py#L57-L66

Above code only caters for training job status Completed or Failed, so if the training job status is marked as `Stopped

Describe the issue

For every master merge, we create a new release. We also generate docs and create PR for every master merge.

We want to avoid release workflow in case of docs or boilerplate PR.

What if we do not do this?

We have extra releases that only have docs changes, which isn't desirable.

Related component(s)

Flytectl

Are you sure this issue hasn't b

In Aim Sequence is defined as a series of homogenious values (for example, Metric is a series of floating point values).
It is assumed that for the same sequence Run.track() is called for the objects of a same type. However this is not enforced.

Need to enhance the track method to check object's type before writing it to db. The following to be taken into account:

• tracking of a sequ

We have a _custom_command function: https://github.com/ploomber/ploomber/blob/2e0d764c8f914ba21480b275c545ea50ff800513/src/ploomber/cli/parsers.py#L399

that should really be an instance method of CustomParser: https://github.com/ploomber/ploomber/blob/2e0d764c8f914ba21480b275c545ea50ff800513/src/ploomber/cli/parsers.py#L36

Steps:

• make _custom_command an instance method
• re

We're using marshmallow to parse whylogs config from YAML

However, Pydantic is much more powerful as it allows users to set config via various mechanims, from YAML, JSON to Environment settings.

We should consider moving to pydantic

Include a API environment variable RUBRIX_DISABLE_ES_INDEX_TEMPLATE_CREATION allowing advanced users create its own es index settings and mappings.

See #443