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Upcoming modifications to Put on OS watch faces

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Upcoming modifications to Put on OS watch faces



Upcoming modifications to Put on OS watch faces

Posted by François Deschênes Product Supervisor – Put on OS

Immediately, we’re asserting essential modifications to Put on OS watch face growth that may have an effect on how builders publish and replace watch faces on Google Play. As a part of our ongoing effort to boost Put on OS app high quality, we’re transferring in the direction of supporting solely the Watch Face Format and eradicating help for AndroidX / Wearable Assist Library (WSL) watch faces.

We launched Watch Face Format at Google I/O in 2023 to make it simpler to create watch faces which are customizable and power-efficient. The Watch Face Format is a declarative XML format, so there isn’t any executable code concerned in making a watch face, and there’s no code embedded within the watch face APK.

What’s altering?

Builders might want to migrate revealed watch faces to the Watch Face Format by January 14, 2026. Builders utilizing Watch Face Studio to construct watch faces might want to resubmit their watch faces to the Play Retailer utilizing Watch Face Studio model 1.8.7 or above – see beneath for extra particulars.

When are these modifications coming?

Beginning January 27, 2025 (already in impact):

Beginning January 14, 2026:

    • Availability: Customers won’t be able to put in legacy watch faces on any Put on OS gadgets from the Play Retailer. Legacy watch faces already put in on a Put on OS system will proceed to work.
    • Updates: Builders won’t be able to publish updates for legacy watch faces to the Play Retailer.
    • Monetization: The next received’t be potential for legacy watch faces: one-off watch face purchases, in-app purchases, and subscriptions. Present purchases and subscriptions will proceed to work, however they won’t renew, together with auto-renewals.

What ought to builders do subsequent?

To arrange for these modifications and to proceed publishing watch faces to the Play Retailer, builders utilizing AndroidX or WSL to construct watch faces should migrate their watch faces to the Watch Face Format and resubmit to the Play Retailer by January 14, 2026.

Builders utilizing Watch Face Studio to construct watch faces might want to resubmit their watch faces to the Play Retailer utilizing Watch Face Studio model 1.8.7 or above:

    • You should definitely republish for all Play tracks, together with all testing tracks in addition to manufacturing.
    • Take away any bundles from these tracks that had been created utilizing Watch Face Studio variations previous to 1.8.7.

Advantages of the Watch Face Format

Watch Face Format was developed to help builders in creating watch faces. This format gives quite a few benefits to each builders and finish customers:

    • Simplified growth: Streamlined workflows and visible design instruments make constructing watch faces simpler.
    • Enhanced efficiency: Optimized for battery effectivity and clean interactions.
    • Elevated safety: Strong security measures shield consumer information and privateness.
    • Ahead-compatible: Entry to the newest options and capabilities of Put on OS.

Sources to assist with migration

To get began migrating your watch faces to the Watch Face Format, try the next developer steering:

We encourage builders to start the migration course of as quickly as potential to make sure a seamless transition and continued availability of your watch faces on Google Play.

We perceive that this alteration requires effort. In case you have additional questions, please consult with the Put on OS neighborhood announcement. Please report any points utilizing the problem tracker.

Cyborg tadpoles are serving to us find out how mind improvement begins – NanoApps Medical – Official web site

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Cyborg tadpoles are serving to us find out how mind improvement begins – NanoApps Medical – Official web site


How does our mind, which is able to producing complicated ideas, actions and even self-reflection, develop out of primarily nothing? An experiment in tadpoles, by which an digital implant was included right into a precursor of their brains on the earliest embryonic stage, could have edged us nearer to answering this query.

TanStack and the Way forward for Frontend with Tanner Linsley

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TanStack and the Way forward for Frontend with Tanner Linsley


TanStack is an open-source assortment of high-performance libraries for JavaScript and TypeScript functions, primarily centered on state administration, information fetching, and desk utilities. It contains well-liked libraries like TanStack Question, TanStack Desk, and TanStack Router. These libraries emphasize declarative APIs, optimized efficiency, and developer-friendly options, and they’re more and more well-liked for contemporary frontend improvement.

Tanner Linsley is the creator of TanStack and he joins the podcast with Nick Nisi to speak concerning the undertaking, SSG, kind security, the TanStack Begin full-stack React framework, and far more.

Nick Nisi is a convention organizer, speaker, and developer centered on instruments throughout the net ecosystem. He has organized and emceed a number of conferences and has led NebraskaJS for greater than a decade. Nick presently works as a developer expertise engineer at WorkOS.

 

 

Please click on right here to see the transcript of this episode.

Sponsors

This episode of Software program Engineering Day by day is dropped at you by Capital One.

How does Capital One stack? It begins with utilized analysis and leveraging information to construct AI fashions. Their engineering groups use the facility of the cloud and platform standardization and automation to embed AI options all through the enterprise. Actual-time information at scale permits these proprietary AI options to assist Capital One enhance the monetary lives of its prospects. That’s know-how at Capital One.

Be taught extra about how Capital One’s fashionable tech stack, information ecosystem, and utility of AI/ML are central to the enterprise by visiting www.capitalone.com/tech.

Guidelines for implementing DevSecOps Practices for Cellular Apps

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Guidelines for implementing DevSecOps Practices for Cellular Apps


Shift left. Safe quick. Launch typically.

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Databricks provides new instruments like Lakebase, Lakeflow Designer, and Agent Bricks to raised help constructing AI apps and brokers within the enterprise

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Databricks provides new instruments like Lakebase, Lakeflow Designer, and Agent Bricks to raised help constructing AI apps and brokers within the enterprise


At its Knowledge + AI Summit, Databricks introduced a number of new instruments and platforms designed to raised help enterprise prospects who’re making an attempt to leverage their knowledge to create company-specific AI purposes and brokers. 

Lakebase 

Lakebase is a managed Postgres database designed for working AI apps and brokers. It provides an operational database layer to Databricks’ Knowledge Intelligence Platform. 

In response to the corporate, operational databases are an essential basis for contemporary purposes, however they’re based mostly on an outdated structure that’s extra suited to slowly altering apps, which is not the fact, particularly with the introduction of AI. 

Lakebase makes an attempt to unravel this downside by bringing steady autoscaling to operational databases to help agent workloads and unify operational and analytical knowledge. 

In response to Databricks, the important thing advantages of Lakebase are that it separates compute and storage, is constructed on open supply (Postgres), has a novel branching functionality very best for agent improvement, provides automated syncing of information to and from lakehouse tables, and is absolutely managed by Databricks.

It’s launching with a number of supported companions to facilitate third-party integration, enterprise intelligence, and governance instruments. These embody Accenture, Airbyte, Alation, Anomalo, Atlan, Boomi, Cdata, Celebal Applied sciences, Cloudflare, Collibra, Confluent, Dataiku, dbt Labs, Deloitte, EPAM, Fivetran, Hightouch, Immuta, Informatica, Lovable, Monte Carlo, Omni, Posit, Qlik, Redis, Retool, Sigma, Snowplow, Spotfire, Striim, Superblocks, ThoughtSpot and Tredence.

Lakebase is at the moment accessible as a public preview, and the corporate expects so as to add a number of vital enhancements over the following few months. 

“We’ve spent the previous few years serving to enterprises construct AI apps and brokers that may cause on their proprietary knowledge with the Databricks Knowledge Intelligence Platform,” stated Ali Ghodsi, co-founder and CEO of Databricks. “Now, with Lakebase, we’re creating a brand new class within the database market: a contemporary Postgres database, deeply built-in with the lakehouse and immediately’s improvement stacks. As AI brokers reshape how companies function, Fortune 500 firms are prepared to exchange outdated methods. With Lakebase, we’re giving them a database constructed for the calls for of the AI period.”

Lakeflow Designer

Coming quickly as a preview, Lakeflow Designer is a no-code ETL functionality for creating manufacturing knowledge pipelines. 

It includes a drag-and-drop UI and an AI assistant that enables customers to explain what they need in pure language.

“There’s plenty of stress for organizations to scale their AI efforts. Getting high-quality knowledge to the precise locations accelerates the trail to constructing clever purposes,” stated Ghodsi. “Lakeflow Designer makes it attainable for extra individuals in a company to create manufacturing pipelines so groups can transfer from thought to influence sooner.”

It’s based mostly on Lakeflow, the corporate’s resolution for knowledge engineers for constructing knowledge pipelines. Lakeflow is now usually accessible, with new options equivalent to Declarative Pipelines, a brand new IDE, new point-and-click ingestion connectors for Lakeflow Join, and the power to put in writing on to the lakehouse utilizing Zerobus. 

Agent Bricks

That is Databricks’ new software for creating brokers for enterprise use circumstances. Customers can describe the duty they need the agent to do, join their enterprise knowledge, and Agent Bricks handles the creation.

Behind the scenes, Brokers Bricks will create artificial knowledge based mostly on the client’s knowledge with the intention to complement coaching the agent. It additionally makes use of a variety of optimization methods to refine the agent. 

“For the primary time, companies can go from thought to production-grade AI on their very own knowledge with velocity and confidence, with management over high quality and price tradeoffs,” stated Ghodsi. “No guide tuning, no guesswork and all the safety and governance Databricks has to supply. It’s the breakthrough that lastly makes enterprise AI brokers each sensible and highly effective.”

And every part else…

Databricks One is a brand new platform that brings knowledge intelligence to enterprise groups. Customers can ask questions on their knowledge in pure language, leverage AI/BI dashboards, and use custom-built Databricks apps. 

The corporate introduced the Databricks Free Version and is making its self-paced programs in Databricks Academy free as nicely. These adjustments have been made with college students and aspiring professionals in thoughts.

Databricks additionally introduced a public preview for full help of Apache Iceberg tables within the Unity Catalog. Different new upcoming Unity Catalog options embody new metrics, a curated inside market of licensed knowledge merchandise, and integration of Databricks’ AI Assistant. 

Lastly, the corporate donated its declarative ETL framework to the Apache Spark mission, the place it’ll now be generally known as Apache Spark Declarative Pipelines.

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