<!here> Happening now! ☝️

Hi everyone 👋 We’ve built a visual tool to create Kedro pipelines—no CLI needed—and would love your feedback! 👉 Try it here: demo.kedro.org/kedro-builder What it is A drag-and-drop interface where you can: • Create Kedro projects visually • Add datasets and function nodes • Connect components into pipelines • View the generated code • Export a ready-to-use Kedro project Great for • Quick prototyping • Understanding how datasets, nodes, and pipelines fit together How to try it 1️⃣ Follow a quick flow: • Create a new project • Add a dataset (CSV, Parquet, etc.) • Add a function node • Connect them into a simple pipeline • View the generated code • Export your project 2️⃣ Or explore freely: • Try the 42 supported dataset types • Build more complex pipelines • Test validation and error handling • Inspect the generated Kedro code While testing, we’d love your thoughts on: • Was it intuitive to use? • Did the generated code look correct? • Would you use this for learning or prototyping? • Was there anything that felt confusing or unclear? • Is there anything you’d like to see added or improved? You can share feedback via feedback button in the tool or DM me directly. Thanks for helping make Kedro more accessible 🙏

Spec-Driven Development for Data Practitioners In the next edition of ☕ Kedro Coffee Chat 🔶, @Rashida Kanchwala will explore spec-driven development and how OpenSpec can be combined with Kedro to build reliable, well-defined data workflows. 📅 When: 08 May, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: https://www.linkedin.com/events/7458142146634698752/ 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

<!here> 🗞️ Hot off the press: Generative AI workflows need engineering discipline to scale beyond the demo It's been less than a year since we released Kedro 1.0 K, and a lot has changed in how we think about and build data pipelines. Agentic workflows have moved past the novelty stage and teams are now implementing them alongside traditional ML steps. We've shipped a number of features across the Kedro ecosystem to meet these evolving needs: the LLM context node for preparing everything required to run an LLM, datasets for configuring and managing prompts, tracing, and evaluation. Now the team has published an article sharing our vision for how Kedro fits into the agentic workflow, bringing engineering discipline to ensure these systems don't stay as demos but actually make it to production! You can find the article here: https://medium.com/quantumblack/generative-ai-workflows-need-engineering-discipline-to-scale-beyond-the-demo-a9928135e393 🔗

Should AI Write Your Docs? A Team Discussion ☕ In the next edition of ☕ Kedro Coffee Chat 🔶, @Laura Couto will explore the use of AI for writing documentation: what works, what doesn't, and where the line should be. Building on a recent team discussion, she'll share pros and cons from real experience. 📅 When: 22 May, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: https://www.linkedin.com/events/7463191435249561600/ 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

KKK Kedro 1.4.0, Kedro-Datasets 9.4.0, and Kedro-Telemetry 0.8.0 are out! KKK Hi <!here>, we’re excited to announce three new releases! 🥳🥳🥳 • Kedro 1.4.0 brings official python 3.14 support, all new

KedroServiceSession

, and project inspection API • Kedro-Datasets 9.4.0 adds python 3.14 support, several new

huggingface

datasets as well as the

opik.EvaluationDataset

as an experimental dataset • Kedro-Telemetry 0.8.0 also adds python 3.14 support and fixes bugs in the dataset type collection 🚀 What can you expect in these releases? K Kedro 1.4.0 • Major features and improvements: ◦ Official support for Python 3.14 ◦ First version of the

KedroServiceSession

which enables runtime parameter injection per run as well as multiple runs per session ◦ Ability to inspect the project snapshot via the inspection API ◦ Improved

%load_node

and scoped parameter type-hint validation when selected pipelines are being run ◦ For more changes, see the full release notes • 📚 Documentation changes: ◦ Added documentation for

KedroServiceSession

◦ Fixed API docs the

session

and

context

modules ──────────────────────── K Kedro-Datasets 9.4.0 • Major features and improvements: ◦ New HuggingFace Datasets:

ArrowDataset

,

ParquetDataset

,

JSONDataset

and

CSVDataset

◦ Support for Python 3.14 (except for

tensorflow.TensorFlowModelDataset

and

geopandas.GenericDataset

due to no support in underlying libraries) ◦ Credentials support in

ibis.FileDataset

◦ New experimental dataset:

opik.EvaluationDataset

◦ Some experimental datasets for

langfuse

,

opik

and

langchain

have been renamed to simplify the naming convention ◦ See full release notes for more details ──────────────────────── K Kedro-Telemetry 0.8.0 • Major features and improvements: ◦ Support for Python 3.14 ◦ Fixed bug related to collection of dataset types ──────────────────────── 🙌 Community contributions: A huge thank you to everyone who contributed to these releases! Kedro 1.4.0: BhavayChopra, jeevan6996, Rahul Bansod, PragnyaKhandelwal, datascienceio, Guillaume Tauzin, Prince Kumar Kedro-Datasets 9.4.0: datascienceio, Guillaume Tauzin, Ian Whalen, Sai Asish Y, Kaushal Dhungel, Anton Nikishin 🔗 Helpful links • Kedro-datasets GitHub repository • Kedro core GitHub repository • VSCode-Kedro GitHub repository • Kedro docs You too can contribute by using these features and providing feedback. Follow our roadmap for more updates, comment on the tickets, and suggest future features to the community. Until next time, The Kedro Team 💛

<!here> 🎉 Kedro went open source 7 years ago today, back in 2019! Happy anniversary to everyone who has been part of the journey - our users, contributors, maintainers, and advocates. Thank you for helping build, improve, and grow the Kedro ecosystem over the years. Here's to many more years of better data and AI engineering together! 🎂🚀

KKK Kedro-Viz 12.4.0, and VSCode-Kedro 0.8.0 are out! KKK Hi everyone, we’re excited to announce two new releases! 🥳🥳🥳 • Kedro-Viz 12.4.0 brings official Python 3.14 support, and expose full internal Kedro node name as

kedro_node_name

. • VSCode-Kedro 0.8.0 adds a native VS Code right-click action on Kedro Viz task nodes to open an untitled debug notebook prefilled with

%load_node <node_name>

. 🚀 What can you expect in these releases? K Kedro-Viz 12.4.0 • Major features and improvements: ◦ Official support for Python 3.14 ◦ Expose full internal Kedro node name as

kedro_node_name

◦ Add

NodeContextMenu

support for VSCode ◦ Add Consent Management Platform (CMP) script to Kedro-Viz docs ◦ For more changes, see the full release notes ──────────────────────── K VSCode-Kedro 0.8.0 • Major features and improvements: ◦ Adds a native VSCode right-click action on Kedro Viz task nodes to open an untitled debug notebook prefilled with

%load_node <node_name>

. ◦ For more changes, see the full release notes 🙌 Community contributions: A huge thank you to everyone who contributed to these releases! Kedro-Viz 12.4.0: Eoin Shaughnessy and tuanaiseo 🔗 Helpful links • Kedro-Viz GitHub repository • VSCode-Kedro GitHub repository You too can contribute by using these features and providing feedback. Follow our roadmap for more updates, comment on the tickets, and suggest future features to the community. Until next time, The Kedro Team 💛

Kedro in VS Code: From Pipeline View to One-Click Node Debugging ☕ In the next edition of ☕ Kedro Coffee Chat 🔶*,* @Jitendra Gundaniya will be introducing the Kedro VS Code extension and a new one-click node debugging workflow. We will look at how developers can move from a visual Kedro-Viz pipeline inside VS Code to an interactive notebook prepared with

%load_node

, making it easier to inspect and debug individual Kedro nodes. 📅 When: 05 June, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: https://www.linkedin.com/events/7468274192220655616/ 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

Today marks the 7th anniversary Kedro goes open source. K🎂 They say 7 years represents a full cycle, a time to reflect on our journey and look forward to the next major milestone. Kudos to everyone here who contributes to and supports this open-source community. Here’s to the next 7 years! 🪅

GraphRAG with Kedro ☕ In the next edition of ☕ Kedro Coffee Chat 🔶, @Laura Couto will demo a complete GraphRAG system built entirely with Kedro. Starting from 55,500 synthetic patient records, she'll walk through five modular pipelines that clean the data, build a knowledge graph, index it into a vector database, and power an agentic Q&A interface all with every dataset tracked in the catalog. If you've been curious about how Kedro handles GenAI workflows end-to-end. 📅 When: 19 June, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: https://www.linkedin.com/events/7473343901513326593/ 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

<!here> You don't want to miss this one!! ☕ ☝️

KKK Kedro 1.5.0 and Kedro-Datasets 9.5.0 are out! KKK Hi everyone, we’re excited to announce a new Kedro release! 🥳🥳🥳 Kedro 1.5.0 introduces a brand new Server API layer powered by

KedroServiceSession

, a

kedro server start

CLI command, selective pipeline loading, and updated deployment documentation. announcement Read all about Kedro Server API and KedroServiceSession here! https://kedro.org/blog/kedro-as-a-service Kedro-datasets 9.5.0 introduces a security fix to

PyTorchDataset

,

send_individually

option to

APIDataset

and other minor improvements. 🚀 What can you expect in this release? K Kedro K Major features and improvements: • New HTTP Server API layer built on

KedroServiceSession

to execute pipelines from HTTP requests, with endpoints for: -

/run

— run pipelines with optional runtime parameters -

/health

— check the server’s health status -

/snapshot

— retrieve the current project snapshot • New CLI command

kedro server start

to launch the server • Selective pipeline loading: when

--pipelines

is specified, only the requested pipeline modules are imported, speeding up startup • Refreshed the Amazon EMR Serverless, AWS Step Functions, and AWS Batch deployment guides with strategy-first layouts, namespace-based grouping, container image guidance, and end-to-end walkthroughs • And more! Read the release notes for a full list of changes! K Kedro Datasets K • Added `send_individually`option to`APIDataset`to send list items as individual requests instead of batched arrays. • Hardened experimental `pytorch.PyTorchDataset`:`weights_only=True`is now enforced by default on load to block arbitrary code execution from untrusted`.pt`files, user-supplied`load_args`and`save_args`are now correctly passed to`torch.load`and`torch.save`(previously silently dropped), and the misleading “pickle-safe” docstring was corrected. • Fixed`ibis.FileDataset`to support remote filepaths (e.g.

s3://

,

abfss://

,

hf://

) and added an`fs_args`argument to authenticate the filesystem used for version discovery. • And more! Read the release notes for a full list of changes! 🙌 Community contributions: A huge thank you to everyone who contributed to this release: PragnyaKhandelwal, Anton Nikishin, GDaamn, Feng Jikui, Rudra Dudhat, Jean-Baptiste Braun, Gargi, and Simon 🔗 Helpful links • Kedro GitHub repository • Kedro-datasets GitHub repository • <http://(http://docs.kedro.org|Kedro docs> You too can contribute by using these features and providing feedback. Follow our roadmap for more updates, comment on the tickets, and suggest future features to the community. Until next time, The Kedro Team 💛

<!here> We're not bringing one, but two releases across the Kedro ecosystem today! K ☝️

All about the Data Catalog ☕ In the next edition of ☕ Kedro Coffee Chat 🔶, @Merel goes all in on the Data Catalog, Kedro's single source of truth for your data. She'll walk through the catalog fundamentals, configuration environments, configuration patterns, templating, and Dataset Factories, which let you swap many repetitive catalog entries for one clean pattern. Whether you're brand new to the catalog or want to stop hardcoding filepaths for good, come hang out. 📅 When: 03 July, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: https://www.linkedin.com/events/7478403211779870720/ 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

<!here> Looking forward to telling you all about Kedro's power feature: Data Catalog ☝️

Hi everyone! We’ve recently released K Kedro 1.5.0 K with some exciting new features - the Kedro Server API and the new KedroServiceSession! 📣 Read the full blog post here: kedro.org/blog/kedro-as-a-service We’ve been working on enabling “Kedro as a service” - making Kedro pipelines callable within long-running processes and over HTTP. This unlocks interactive apps, repeated-execution loops, API driven workflows and integration with AI agentic systems. The two new pieces are now available to try: 🌐 Kedro Server API — a FastAPI server with

GET /health

,

POST /run

, and

GET /snapshot

uv pip install 'kedro[server]'
kedro server start --host 127.0.0.1 --port 8000

🔁 KedroSeviceSession — run pipelines repeatedly in one process; state loads once, each run stays isolated:

with KedroServiceSession.create() as session:
    session.run(runtime_params={"param1": "value1"})
    session.run(runtime_params={"param1": "value2"})

We’d love your feedback! How would you use Kedro as a service? What’s missing for your use case? Drop a comment here or open an issue/discussion on GitHub. 🙏

Reflection Hub ☕ In the next edition of ☕ Kedro Coffee Chat 🔶, @Ravi Kumar Pilla will introduce Reflection Hub which is a system for building reusable reflection and learning capabilities into enterprise AI agents and workflows. If you're interested in making your AI workflows smarter with each run, this is one you won't want to miss. 📅 When: 17 July, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: linkedin.com/events/7483455868638814208 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

In the next edition of ☕ Kedro Coffee Chat 🔶, @Sajid Alam will preview dataset validation, a new capability that catches bad data at the I/O boundary before it ever reaches your nodes. Declare a validator on a catalog entry with one line of YAML, and Kedro validates every load and save in pipeline runs, notebooks and CI, reporting every failed check at once instead of a mystery stack trace deep inside a node. There will be a live demo on a spaceflights project, a peek at how it works under the hood, and the roadmap to release. 📅 When: 07 August, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: linkedin.com/posts/in-this-edition-of-kedro-coffee-chat…?rcm=… 📣 These sessions are public and open to everyone. Join us live or catch the recording.

Kedro Skills: Supercharging Your AI Coding Assistant ☕ In the next edition of ☕ Kedro Coffee Chat 🔶, @Ankita Katiyar will show a quick walkthrough of the kedro-skills plugin and how its skills enhance AI-assisted Kedro development. 📅 When: 04 Sept, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: linkedin.com/events/7501248705807876096 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

<!here> Tune in tomorrow to learn about our newly released Kedro Skills ☕ 🤩

🚀 Introducing Kedro Skills Kedro Skills is a new standalone package that you install alongside your Kedro project. Kedro Skills provides reusable Kedro-specific knowledge and guidance to your AI coding assistant, helping it understand how to work with your project and follow Kedro best practices. Our first skill is catalog-config, which helps your coding agent configure the Kedro Data Catalog using Kedro conventions and best practices. Getting started is simple:

pip install kedro-skills
kedro skills list
kedro skills install catalog-config

It works across Cursor, GitHub Copilot, Claude Code and Codex CLI. But this is only the beginning. 👀 We don't want to decide all the skills Kedro users need ourselves, we'd love Kedro community to help shape what comes next. 👉 Try the first skill and tell us where it helps, or where it doesn't. 👉 Got a repetitive Kedro task your coding agent struggles with? That could be our next skill. Open an issue in the kedro-skills GitHub repo so we can explore it. 👉 Have an idea for a skill already? Build it, improve an existing one, and contribute it back to the community. Our goal is to grow Kedro Skills into a community-driven collection of reusable Kedro knowledge that makes AI-assisted development with Kedro better for everyone. 🔗 Check out kedro-skills on GitHub and let us know: what skill should we build next?

<!here> Hey everyone! I'll be speaking at Data Expo in Utrecht 🇳🇱 this Thursday on why software engineering principles aren't optional for AI systems, they're what determines whether you actually benefit from AI or just end up with fragile, unmanageable systems. I'll be drawing on our experience building Kedro, especially how deliberate we are about modularity, separation of concerns and observability. Would love to see you there if you're around, or happy to share more after if you're curious! K

Kedro 1.6.0 is out! 🎉 Hi <!here>, we’re excited to announce a new Kedro release! 🥳 Kedro 1.6.0 introduces dataset validation, making it easier to catch data quality issues directly as part of your Kedro workflow. This release also brings more control over runners from the CLI, richer project inspection metadata, thread-safety improvements, and several security and reliability fixes. 🚀 What can you expect in this release? K Kedro K Major features and improvements: • Dataset validation: You can now declare a validator directly in your catalog configuration, and Kedro will automatically validate datasets on load and save, with built-in Pandera support for pandas/Polars and support for custom validators. • The new

—runner-params

option for kedro run lets you pass runner configuration such as

max_workers

directly from the command line. • Project snapshots now include node function names and source locations metadata. •

get_project_snapshot()

also now supports optional

runtime_params

. • We’ve fixed concurrency issues around pipeline loading and introduced a serving_mode for KedroServiceSession that preloads pipelines when running Kedro as a service. • Plus plenty of bug fixes and smaller improvements Breaking changes & security fix This release includes an important security fix and one configuration change for users of the Kedro HTTP server: • Dataset type values resolved through runtime_params supplied to POST /run can no longer select an AbstractDataset class from the request. Trusted callers such as

kedro run --params

are unaffected. •

RUNNER_MODULES_WHITELIST

has been renamed to

RUNNER_MODULE_ALLOWLIST

. If your project uses the old setting, you’ll need to rename it when upgrading to Kedro 1.6.0; otherwise, those entries will be ignored and the HTTP server will reject the configured runner modules. Documentation improvements • Including a new dataset validation guide, a Kedro cheatsheet, and a new “Vibe coding with skills” page for our new kedro-skills. 👉 Read the full Kedro 1.6.0 release notes for all the details. 🙌 Community contributions A huge thank you to everyone who contributed to this release: eeshsaxena, Versus-DEV, Shizoqua, BALOGUN DAVID TAIWO, kingjaiteh, and Muhtasim Munif Fahim. 💛 🔗 Helpful links • Kedro GitHub repository • Kedro documentation • Kedro Skills Give Kedro 1.6.0 a try and let us know what you think! Your feedback and contributions continue to help shape where Kedro goes next. Until next time, The Kedro Team 💛

K Kedro 1.7.0 is out! K Kedro 1.7.0 brings

llm_context_node

and its related tools to assemble agentic context to stable features out of experimental, and lets you pass runtime parameters to

GET /snapshot

. It also includes a security fix for logging configuration, so check the breaking changes before you upgrade. 🚀 What can you expect in this release? Major features and improvements • Added an optional

params

query parameter to

GET /snapshot

for resolving

${runtime_params:...}

interpolation per request, using the same format as

kedro run --params

. • Graduated

llm_context_node

,

LLMContextNode

,

LLMContext

and

tool

from experimental to stable. They no longer emit a

KedroExperimentalWarning

. Breaking changes to the API • Security fix: Custom logging handler, filter or formatter classes referenced in

conf/logging.yml

are no longer imported unless their module is on the logging allowlist. Only the

logging

standard-library package (including

logging.handlers

) and

kedro.logging

are trusted by default. Projects that point

conf/logging.yml

at their own logging classes must now list those modules in the

KEDRO_LOGGING_MODULE_ALLOWLIST

environment variable (comma-separated) to keep them working. 🔗 Helpful links • Kedro GitHub repository • Kedro documentation Try Kedro 1.7.0 and tell us what you think. Share feedback, report bugs, or request eatures on GitHub, or come and chat with us on Slack! Until next time, The Kedro Team 💛

K Kedro-Viz 12.5.0 is out! K Kedro-Viz 12.5.0 adds a help menu to the toolbar, so you can reach our support channels without leaving the app. It also fixes several bugs and updates dependencies to match Kedro. 🚀 What can you expect in this release? Major features and improvements • Add a help menu to the global toolbar linking to Kedro-Viz support channels. (#2756) Bug fixes and other changes • Fix version and run-status API requests for embedded and static Kedro-Viz. (#2753) • Fix for

autoreload

to ignore notebook file changes. (#2712) • Align pandas requirement with Kedro (

pandas>=2.0,<4.0

). (#2694) • Raise

ipython

lower bound to

8.10

to fix Windows Python 3.10 lower-bound e2e failure. (#2787) • Update Node.js version from v18 to v24 and bump

canvas

to v3 and `jest`/`jest-environment-jsdom` for compatibility. (#2754) • Fix toolbar

tooltip

not dismissing on mouse leave. (#2770) 🔗 Helpful links • Kedro-Viz GitHub repository • Kedro-Viz documentation Upgrade to Kedro-Viz 12.5.0 and let us know how it works for you. Report bugs or request features on GitHub, or find us on Slack! Until next time, The Kedro Team 💛

Inspect, Don’t Run: Understanding a Kedro Project with ProjectSnapshot ☕ In the next edition of ☕ Kedro Coffee Chat 🔶, @Jitendra Gundaniya will explore Kedro’s ProjectSnapshot API. We’ll inspect a real project’s pipelines, datasets and parameter names without running its pipeline, then see how Kedro-Viz builds a graph from that structure. We’ll finish with a simple CI check that catches missing input names before a run. 📅 When: 02 Oct, 1 PM (GMT+1) youtube YouTube: linkedin LinkedIn: linkedin.com/events/7511415653879394304 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

<!here> Hi Kedro community! 👋 We've just published two new blog posts on Medium exploring how Kedro can help build modular, reusable, and production-ready AI systems! 🧠 Using Kedro to Build Reusable Reflection Systems for Enterprise AI Agents Learn how to use Kedro to implement agentic reflection, enabling AI agents to evaluate, critique, and iteratively improve their outputs. Discover how Kedro's modular pipelines make reflection workflows more structured, reusable, and maintainable 🕸️ Building Production-Ready GraphRAG Systems with Kedro Explore how to build GraphRAG systems with Kedro, combining knowledge graphs and LLMs to generate richer, more context-aware responses. See how Kedro helps turn complex GraphRAG workflows into modular, reproducible, and maintainable pipelines. We'd love to hear what you think! 💛 If you're experimenting with agentic AI or other LLM-powered applications using Kedro, we'd love for you to check out these articles, share your thoughts, and tell us what you're building! Happy building! 🚀 And thanks @Laura Couto @Ravi Kumar Pilla @Jo Stichbury for the great work!

Evaluating Kedro Skills with promptfoo ☕ We all use skills to teach our AI coding assistants how to work with our tools. But how do we know they actually work? In the next edition of ☕ Kedro Coffee Chat 🔶 @Laura Couto will show you how to evaluate these skills using promptfoo, testing the same tasks with and without the skill across different models. 📅 When: 06 Nov, 1 PM (GMT) youtube YouTube: linkedin LinkedIn: linkedin.com/events/7524105822411509761 📣 These sessions are public and open to everyone. Join us live or catch the recording afterwards.

Hi everyone, we’re excited to announce the new Kedro, Kedro Viz, Kedro-Datasets, and Kedro-Docker releases! 🥳 Kedro 1.8.0 makes your kedro projects easier to run as a service or deployed, with node groups in project snapshots and a new way to validate node groupings before deployment. This release also brings a round of reliability fixes across the catalog, config loader, and CLI. Also, the kedro docs have moved to Zensical! 🚀 What can you expect in these releases? K Kedro 1.8.0 K •

KedroServiceSession

now supports dataset injection per run with the

runtime_datasets

arguments. • Node grouping: node groups now available via

GET /snapshot

and

kedro.inspection.validate_deployment_grouping

can be used to check grouped nodes before deployment. •

OmegaConfigLoader

now supports passing

kwargs

to

custom_resolvers

• Security hardening to logging configuration. • And more! Read the full release notes for Kedro 1.8.0 here! K Kedro-Datasets 10.0.0 K • Spark and NetCDF:

spark.SparkHiveDataset

now supports external Hive table locations via

save_args.path

, and the experimental

netcdf.NetCDFDataset

gains standard Kedro versioning for local and S3 files. • Public `load`/`save` and

os.PathLike

support:

os.PathLike

filepaths now work across the remaining datasets, and

load

and

save

are publicly exposed for

spark.SparkDatasetV2

,

databricks.ManagedTableDataset

, and the experimental vector store datasets. • Safer file writes:

matplotlib.MatplotlibDataset

and the Hugging Face

CSVDataset

,

JSONDataset

and

ParquetDataset

can no longer write outside the dataset directory. • Plus plenty of bug fixes across Spark, Polars and pandas datasets, along with docs improvements. Read the full release notes for all the changes. K Kedro-Viz 12.6.0 K • Workflow tracking:

is_sequential_runner

now accepts the runner class name, so workflow tracking stays on during a sequential run. • What’s new panel: The “What’s new” panel now highlights node previews. • Docs and README: Fixed the broken banner image in

README.md

(also shown on PyPI), and aligned

CONTRIBUTING.md

with the Kedro contributing guide. K Kedro-Docker 0.7.0 K • Modernised the generated

Dockerfile

with a multi-stage build that installs dependencies into a virtual environment from

uv.lock

, falling back to

requirements.txt

. • The default base image now uses the Python version from the project’s

.python-version

file, or the current Python version if there is none. • Added a

--pipelines

option to

kedro docker build

to build an image that runs specific pipelines. • Refreshed the generated

.dockerignore

. 🙌 Community contributions A huge thank you to everyone who contributed to this release: Rodrigo-Palma, Charan Rathore, inchang-ing, Max Gorbuk, Shahzeb Ali, Krish Singh, akira-in-tech, Tanmay Singh, Shizoqua, Dhruv Gupta, AAKASH S S, JokeGbenro, Mohamed Fouad and Harkamal S. Additionally, thanks to leetomo2528, and to Hongwei Li, Junmin Zhu, Zhun Wang, Jiacheng Zhong, Han Dai, Suyue Guo, Songyang Peng and Ziyue Pan for identifying and reporting the security issue. 💛 🔗 Helpful links • Kedro GitHub repository • Kedro Plugins repository • Kedro Viz repository • Kedro documentation • Kedro Skills Let us know what you think! Your feedback and contributions continue to help shape where Kedro goes next. Until next time, The Kedro Team 💛