Sematic

Latest version: v0.40.0

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0.28.0

What's Changed

* [feature] Display metrics for pipelines (success rate, run count, runtime)
* [feature] Added support for setting and memorizing a dev debug flag for the Dashboard
* [deprecation] Deprecate Kubernetes 1.22 support
* [improvement] Backend improvements to syncing with Kubernetes job states
* [improvement] Several minor logging improvements and fixes
* [bugfix] Enable local server to run with python 3.10
* [bugfix] Ensured different users can rerun a pipeline
* [bugfix] Ensured pipeline reruns use the submitting user's credentials
* [bugfix] Ensure canceled/terminated runs have proper runtime display
* [bugfix] Properly display duration for cloned runs
* [bugfix] Fix matplotlib figure serialization, use Sematic Image type for support
* [bugfix] Make storage object URL redirects consistent
* [bugfix] Remove possible infinite reconnect loop when canceling local runs
* [bugfix] Fixed a bug where the Resolver Socket.io client would not be cleanly closed
* [bugfix] Fix corner case in the comparison of sqlite versions
* [bugfix] Wrap long pipeline import paths in pipeline/run display

**Full Changelog**: https://github.com/sematic-ai/sematic/compare/v0.27.0...v0.28.0

Compatibility
Sematic Servers on this version can support pip packages back to `v0.24.1`.

0.27.0

What's Changed

* [feature] Added new S3Location and S3Bucket types that render S3 links in the Dashboard, and
documented them
* [feature] Added a new Image type that render images in the Dashboard, and documented it
* [example] Added TorchLightning + Resnet + Ray example
* [example] Added Ray AIR example
* [example] Added various enhancements to the example Testing Pipeline
* [improvement] BREAKING CHANGE: `image_layers` field in `sematic_pipeline` bazel macro
now ONLY gets passed to image layering, and not also to the Sematic binary target.
if you are using `image_layers` to express dependencies of a pipeline, you will now
need to duplicate them in the `deps` field.
* [improvement] Added support for Python 3.10
* [improvement] Added support for Python 3.10-style type hints
* [improvement] The Dashboard login flow will now redirect to the requested page instead of to
the homepage
* [improvement] Displaying the user who started a Run in the Dashboard Run list page and in the
Run history drop-down
* [improvement] Various documentation updates and fixes
* [improvement] Various log message improvements and enhancements
* [improvement] Sped up Docker image generation through various improvements
* [improvement] Automatically update npm dependencies when building the wheel
* [improvement] Added deep-linking selected panel stickiness in the Dashboard
* [improvement] Filtered only pipelines launched by the current user in the Dashboard homepage
last run widget
* [improvement] Documented Ray integration architecture
* [improvement] Improved wheel building portability by defaulting to bash
* [improvement] Improved reaction time of the CloudResolver after a very long-running cloud Run
has ended
* [improvement] Improved handling of incorrect cleanup of or errors in subprocess spawned by
user code
* [improvement] Various internal refactorings, cleanups, and build improvements
* [improvement] Switched from MB and GB to GiB and MiB in the Ray configurations, for
consistency and standardization reasons
* [improvement] Added checks and documentation for the new libmagic dependency
* [improvement] Resolution failures caused by Resolver errors now get marked as failed instead
of canceled
* [bugfix] Pinned MNIST example pipeline dependencies after a new dependency release broke the
execution
* [bugfix] Fixed a bug that prevented the browser back/forward buttons from working correctly
in the Dashboard
* [bugfix] Fixed a bug that sometimes prevented the Dashboard Run tree panel from updating
* [bugfix] Fixed sorting of the Runs in the Dashboard Run tree panel by creation time
* [bugfix] Fixed a race condition where Kubernetes job updates would be incorrectly handled,
and added safeguards for incorrect Run state transitions
* [bugfix] Fixed a bug where killing a subprocess spawned by user code would prematurely
terminate the Run, or leave the Resolver in an inconsistent state
* [bugfix] Fixed a race condition that would prevent a fresh deployment on Kubernetes due to
missing resources
* [bugfix] Fixed a bug in the Dashboard that prevented the log panel error messages from
refreshing when seeking to a different Run
* [bugfix] Fixed a bug where failure to notify the Dashboard or Resolver with Run updates via
socketio messages would cause the Resolution to fail

**Full Changelog**: https://github.com/sematic-ai/sematic/compare/v0.26.0...v0.27.0

Compatibility
Sematic Servers on this version can support pip packages back to `v0.24.1`.

0.26.0

What's Changed

* [feature] Added optional anonymized user analytics to track Sematic usage
* [improvement] Atomic database migrations with Helm hooks
* [improvement] Move future pickle storage to new server-generated locations
* [improvement] Refactor in-app links to use react router
* [improvement] Minor UI test improvements with Cypress
* [improvement] Minor documentation fixes for rerun-from-here
* [bugfix] Fix noop SQL migrations

**Full Changelog**: https://github.com/sematic-ai/sematic/compare/v0.25.0...v0.26.0

Compatibility
Sematic servers on this version can support pip packages back to v0.24.1

0.25.0

What's Changed

* [feature] New dashboard page showing a searchable list of runs
* [feature] Enable links to runs using only the run id (pipeline path not required)
* [improvement] Expose image layer caching configuration for bazel-built pipelines
* [improvement] Make allocation timeouts for Ray clusters configurable
* [improvement] Small changes to layout of pipeline display page
* [improvement] Have Ray workers use same Kubernetes SA as Sematic workers
* [improvement] Minor user docs improvements
* [bugfix] Fix a bug that was preventing configuration of Slack via helm
* [bugfix] Remove error occurring when a local settings file configures server-only settings
* [bugfix] Be more resilient against non-standard failures during `torch` imports
* [bugfix] More robust cleanup of Ray clusters on pipeline cancellation

**Full Changelog**: https://github.com/sematic-ai/sematic/compare/v0.24.1...v0.25.0

Compatibility
Sematic servers on this version can support pip packages back to v0.22.1

0.24.1

What's Changed
* [improvement] Show more detailed errors on failures of DB migrations
* [bugfix] Reduce wheel size

**Full Changelog**: https://github.com/sematic-ai/sematic/compare/v0.24.0...v0.24.1

Compatibility
Sematic servers on this version can support pip packages back to v0.22.1

0.24.0

What's Changed
* [feature] Introduction of RayCluster[^1]
* [feature] "Tee" cloud function logs so they appear in Sematic dashboard and the pod logs
* [improvement] Visualize better which run was the true "root failure" when a resolution fails
* [improvement] Improve an error message when using untyped dicts in type annotations
* [improvement] Various improvements to Sematic internal test infrastructure
* [bugfix] Remove a possible server crash for local servers running on Macs
* [bugfix] Eliminate a bug that could leave runs hanging if multiple cancellation events were sent
* [bugfix] Fix a bug that removed a useful default for image tag in the Helm chart
* [bugfix] Rename an incorrectly named helm-chart value for Slack integration
* [bugfix] Gracefully terminate runs when a resolver pod restarts mid-resolution

**Full Changelog**: https://github.com/sematic-ai/sematic/compare/v0.23.0...v0.24.0

Compatibility
Sematic servers on this version can support pip packages back to v0.22.1

[^1]: This feature is for Sematic's "Enterprise Edition" only. Please reach out if
you are interested in using Sematic EE.

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