This release brings some exciting enhancements and fixes!
Enhanced UI Customization 📆
- Now featuring relative time spans like "Past 7 days" for better insight into current and upcoming flow runs across the UI.
- Flow Runs Page: Enhanced with customizable date and time filters. Save custom filters with specific date ranges for tailored views
- Flows Page: Updated with similar date and time filtering capabilities
See a demonstration here!
Get type-checked input from humans in the loop
Human-in-the-loop flows just got an upgrade. You can now pause or suspend a flow and wait for type-checked input. To get started, declare the structure of the input data using a Pydantic model, and Prefect will render a form dynamically in the UI when a human resumes the flow. Form validation will ensure that the data conforms to your Pydantic model, and your flow will receive tbe input.
Prefect's new RunInput class powers this experience. RunInput is a subclass of Pydantic's BaseModel. Here's an example of a RunInput that uses dates, literals, and nested Pydantic models to show you what's possible:
class Person(RunInput):
first_name: str
last_name: str
birthday: datetime.date
likes_tofu: bool
age: int = Field(gt=0, lt=150)
shirt_size: Literal[ShirtSize.SMALL, ShirtSize.MEDIUM, ShirtSize.LARGE,
ShirtSize.XLARGE]
shirt_color: Literal["red", "blue", "green"]
preferred_delivery_time: datetime.datetime
shipping_address: ShippingAddress
billing_address: BillingAddress | SameAsShipping = Field(
title="", default_factory=SameAsShipping
)Check out our guide on how to create human-in-the-loop flows to learn more!
Enhancements and Fixes 🛠️
- Fixed environment variable parsing during deployment and prompt and role assignment in the
ContainerInstanceProvisioner - Enhanced dashboard header to adapt to various tag and date input sizes
- Addressed an error encountered when deploying flows with options
See the release notes for details!