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

Expected Behavior

Feature views should have the creation time (i.e., created_timestamp) at the first feast apply

Current Behavior

Features Views do not have creation time at feature view creation

Steps to reproduce

feast init fs
cd fs
feast apply
feast registry-dump
{
  "spec": {
    "name": "driver_id",
    "valueType": "INT64",
    "description": "driver 

Describe the bug

flytectl register files command doesn't fail without --countinueOnError. It should fail with exit code 0.

Expected behavior

• Flytectl register should fail if there is an error
• Flytectl register should not fail if the user passes the --countinueOnError

Additional context to reproduce

No response

Screenshots

No response

Are

In Aim Sequence is defined as a series of homogeneous 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

Our logo is pretty boring, anyone with good design skills can help us design one? :)

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