Awesome

Awesome Kedro

An opinionated Python framework for creating reproducible, maintainable and modular data science code.

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This is an open-source repository to collect together anything related to Kedro such as blog posts, example projects, plugins, videos, and more.

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Awesome Kedro

Awards and highlights

Kedro won Best Technical Tool or Framework for AI in the 2019 Awards AI competition
Kedro documentation won a merit award in the UK Technical Communication Awards 2020, and was overall winner in the UK Technical Communication Awards 2023.
The Kedro framework is listed on the 2020 ThoughtWorks Technology Radar and the 2020 Data & AI Landscape.
Kedro has received an honorable mention in the User Experience category in Fast Company’s 2022 Innovation by Design Awards.

Blog posts

In no particular order:

For more:

#kedro tag on dev.to

Companies using Kedro

There are Kedro users across the world, who work at start-ups, major enterprises and academic institutions like Absa, Acensi, Advanced Programming Solutions SL, AI Singapore, AMAI GmbH, Anacision GmbH, Augment Partners, AXA UK, Belfius, Beamery, Caterpillar, CRIM, Dendra Systems, Element AI, GetInData, GMO, Indicium, Imperial College London, ING, Jungle Scout, Helvetas, Leapfrog, McKinsey & Company, Mercado Libre Argentina, Modec, Mosaic Data Science, NaranjaX, NASA, NHS AI Lab, Open Data Science LatAm, Prediqt, Prospect, QuantumBlack, ReSpo.Vision, Retrieva, Roche, Sber, Société Générale, Telkomsel, Universidad Rey Juan Carlos, UrbanLogiq, Wildlife Studios, WovenLight and XP.

Example projects

Churn Prediction with Kedro by Laíza Parizotto, a project that tackles a data science challenge of predicting customer churn for a fictional financial institution, using Kedro to build an effective pipeline for a production-ready machine learning model.
Response Recommendation System for BarefootLaw by Kasun Amarasinghe, Carlos Caro, Nupoor Gandhi and Raphaelle Roffo, an extensive Data Science for Social Good (DSSG) at Imperial College London project that recommends responses to law related queries
Augury by Craig Franklin, machine-learning functionality for predicting AFL match results in the Tipresias app
CausalLift by Yusuke Minami, a Python package for Uplift Modeling in real-world business
PipelineX by Yusuke Minami, a Python package to develop pipelines for rapid Machine/Deep Learning experimentation using Kedro and MLflow. Example projects using PyTorch, Pandas, and OpenCV are available.
kedro-mlflow-example by Tom Goldenberg, a project that demonstrates how to integrate MLflow with a Kedro codebase
kedro-wdbc-tf by Abhinav Prakash, this project uses a Kedro template to create Deep Learning workflow. The model training was done with TensorFlow against the wdbc (Breast Cancer) dataset.
twitter-sentiment-analysis by Avi Agarwal, a project that demonstrates how to use Kedro to train and evaluate an NLP-based machine learning model.
Anomaly Detection Pipeline with Kedro by Kenneth Leung, a project that demonstrates how to use Kedro for fraud detection on credit card transaction data using an Isolation Forest machine learning model.
FontR by Maciej M, a project implementing Adobe's DeepFont research in Kedro to perform font recognition.
Spaceship-Titanic using Kedro and MLflow by Mauricio Araujo, Spaceship-Titanic Kaggle competition with a fully automated machine learning lifecycle using Kedro and MLflow.
pipelinex_image_processing by Minyus, a Kedro pipeline for image processing using OpenCV, Scikit-image, TensorFlow/Keras, and MLflow.
Price Prediction Pipeline by Pedro Alves, a data processing and data science pipeline for a ficticious Diamond enterprise using Scikit-Learn, Docker and Pandas.
Healthcare Data Analysis with Kedro by Pablo Villar, a end to end project through kedro pipelines (preprocessing, processing and data_science) with an app made in Streamlit where you can interact with the data.
Spaceflights price prediction as a service and Monte Carlo simulations by Takieddine Kadiri, a kedro projects that utilize Kedro Boot to serve the spaceflights price prediction model through Rest API (FatApi) and Data App (Streamlit). It also provides an example of a Monte Carlo simulations for estimating Pi using Kedro Boot.

Kedro plugins

find-kedro - Automatically construct pipelines using pytest style pattern matching.
kedro-accelerator - Speeds up pipelines by parallelizing I/O in the background.
kedro-airflow - Makes it easy to deploy Kedro projects to Airflow.
kedro-airflow-k8s - Enables running a Kedro pipeline with Airflow on a Kubernetes cluster.
kedro-argo - Converts Kedro pipelines to Argo pipelines.
kedro-auto-catalog - A configurable replacement for kedro catalog create that allows you to create default dataset types other than MemoryDataset.
kedro-azureml - Enables running a Kedro pipeline with Azure ML Pipelines service.
kedro-dataframe-dropin - Lets you swap out pandas datasets for modin or RAPIDs equivalents for specialised use to speed up your workflows (e.g on GPUs).
kedro-datasets - A collection of Kedro data connectors.
kedro-docker - Makes it easy to package Kedro projects with Docker.
kedro-dolt - Allows you to expand the data versioning abilities of data scientists and engineers
kedro-fast-api - kedro fast-api is a kedro plugin to easily create a fast-api for a kedro project for models' deployment.
kedro-great - The easiest way to integrate Kedro and Great Expectations.
kedro-grpc-server - Creates a gRPC server for your kedro pipelines.
kedro-kubeflow - Lets you run and schedule pipelines on Kubernetes clusters using Kubeflow Pipelines.
kedro-mlflow - Allows usage of MLFlow in Kedro projects.
kedro-neptune - Integration of Kedro with Neptune.ai.
kedro-pandas-profiling - "Profiles" data in the catalog. (⚠️public archive)
kedro-pandera - Integration of Kedro with Pandera to provide catalog-level data validation.
kedro-partitioned - Extends the functionality on processing partitioned data.
kedro-sagemaker - Enables running a Kedro pipeline with Amazon SageMaker service.
kedro-snowflake - Enables to run full Kedro pipelines in Snowflake.
kedro-softfail-runner - Custom Kedro Runner to enable soft-failing pipeline.
kedro-static-viz - Generates a static Kedro-Viz site (HTML, CSS, JS)
kedro-viz - Helps visualise Kedro data and analytics pipelines.
kedro-vertexai - Enables running a Kedro pipeline with Vertex AI Pipelines service.
kedro-wings - Automatically creates catalog entries to simplify Kedro pipeline writing.- more-kedro - (Hook) library for on the fly typing and validation of parameter dictionaries and default value backed data loading.
steel-toes - Prevent changing downstream catalog data on your teammates while developing in parallel.
vineyard-kedro - Custom DataSet and Runner which enables sharing intermediate data between tasks in Kedro pipelines using Vineyard, a cloud-native in-memory object manager.
kedro-tf-image - Kedro pipelines for preprocessing images using TensorFlow.
kedro-graphql - A Kedro plugin for serving Kedro projects as GraphQL APIs.
kedro-boot - Integrate you kedro project with any application
kedro-popmon - A Kedro plugin for integration of popmon capabilities.
kedro-expectations - Adding Data Validation to Kedro pipelines with up-to-date Great Expectations version.