Hi Prefectionists!
We’ve been really busy over here at Prefect, getting lots of great feedback from early adopters. Thank you all for that!
There’s a lot of work going on behind the scenes as we work on building some exciting new features that will be exclusive to the General Availability of Prefect 2.0, but we want to keep the enhancements flowing to you. In that spirit, there are a lot of quality-of-life improvements here!
Community contributions
While most of the development of Prefect 2.0 is still happening internally, we’re incredibly excited to be getting contributions in our open source repository. Big shoutout to our contributors for this last release:
- @dannysepler
- @ColeMurray
- @albarrentine
- @mkarbo
- @AlessandroLollo
FlowRunner improvements
- Flow runners now pass all altered settings to their jobs instead of just the API key and URL
- The
KubernetesFlowRunner
supports configuration of a service account name - The
SubprocessFlowRunner
streams output by default to match the other flow runners
TaskRunner improvements
- The
DaskTaskRunner
has improved the display of task keys in the Dask dashboard - The
DaskTaskRunner
now submits the execution graph to Dask allowing optimization by the Dask scheduler
New collections for Dask and Ray coming soon
Note that the Dask and Ray task runners will be moving out of the core Prefect library into dedicated prefect-ray
and prefect-dask
collections with the next release. Why?
- This will reduce the number of code dependencies we require for most use cases.
- Since we now have concurrent execution built into the core library (via
ConcurrentTaskRunner
), these packages do not need to be bundled with Prefect. - Lastly, we’re looking forward to building additional tasks and flows specific to Ray and Dask in their respective collections.
Prefect Collections
We’ve received our first user-contributed collection. It includes tasks for Cube.js, check it out!
The following collections have also been recently released:
You can see a list of all available collections in the Prefect Collections Catalog.
Windows compatibility
We’re excited to announce that we’ve begun work on Windows compatibility. Our full test suite isn’t passing yet, but we have core features working on Windows. We expect the majority of the edge cases to be addressed in an upcoming release.
Documentation improvements
We’ve added some new documentation and made lots of improvements to existing documentation and tutorials:
- Added documentation for associating conda environments with separate Prefect profiles
- Added storage steps and advanced examples to the Deployments tutorial
- Expanded documentation of storage options
- Added workspace details to the Prefect Cloud documentation
- Improved schedules documentation with examples
- Revised the Kubernetes tutorial to include work queue setup
- Improved tutorial examples of task caching
CLI
- Deployments can be deleted from the CLI
- The CLI displays help by default
-
prefect version
is robust to server connection errors -
prefect config view
shows sources by default -
prefect deployment create
exits with a non-zero exit code if one of the deployments fails to be created -
prefect config set
allows setting values that contain equal signs -
prefect config set
validates setting types before saving them -
prefect profile inpect
displays settings in a profile instead of duplicating prefect config view behavior -
prefect storage create
trims long descriptions
Bug squashing
We’ve eradicated some bugs, replacing them with good behavior:
- Flow runs are now robust to log worker failure
- Deployment creation is now robust to
ObjectAlreadyExists
errors - Futures from async tasks in sync flows are now marked as synchronous
- Tildes (~) in user-provided paths for
PREFECT_HOME
are expanded - Fixed parsing of deployments defined in YAML
- Deployment deletion cleans up scheduled runs
Optimizations and reactors
You might not see these fixes in your day-to-day, but we’re dedicated to improving performance and maintaining our reputation as maintainers of an approachable and clean project.
- The
state_name
is attached to run models for improved query performance - Lifespan management for the ephemeral Orion application is now robust to deadlocks
- The
hello
route has moved out of theadmin
namespace so it is available on Prefect Cloud - Improved readability and performance of profile management code
- Improved lower-bounds dependency parsing
- Tests are better isolated and will not run against a remote API
- Improved representation of Prefect
Setting
objects - Added extensive tests for
prefect config
andprefect profile
commands - Moved testing utilities and fixtures to the core library for consumption by collections
Give it a try
pip install -U "prefect>=2.0b4"
Docs to get started: Prefect 2.0
Happy Engineering!