Package: xedro
What is Kedro?Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code. It borrows concepts from software engineering and applies them to machine-learning code; applied concepts include modularity, separation of concerns and versioning.How do I install Kedro?To install Kedro from the Python Package Index (PyPI) simply run:pip install kedroIt is also possible to install Kedro usingconda:conda install -c conda-forge kedroOurGet Started guidecontains full installation instructions, and includes how to set up Python virtual environments.What are the main features of Kedro?A pipeline visualisation generated usingKedro-Viz| Feature | What is this? ||----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|| Project Template | A standard, modifiable and easy-to-use project template based onCookiecutter Data Science. || Data Catalog | A series of lightweight data connectors used to save and load data across many different file formats and file systems, including local and network file systems, cloud object stores, and HDFS. The Data Catalog also includes data and model versioning for file-based systems. || Pipeline Abstraction | Automatic resolution of dependencies between pure Python functions and data pipeline visualisation usingKedro-Viz. || Coding Standards | Test-driven development usingpytest, produce well-documented code usingSphinx, create linted code with support forflake8,isortandblackand make use of the standard Python logging library. || Flexible Deployment | Deployment strategies that include single or distributed-machine deployment as well as additional support for deploying on Argo, Prefect, Kubeflow, AWS Batch and Databricks. |How do I use Kedro?TheKedro documentationincludes three examples to help get you started:A typical "Hello World" example, for anentry-level description of the main Kedro conceptsAnintroduction to the project templateusing the Iris datasetA more detailedspaceflights tutorialto give you hands-on experienceWhy does Kedro exist?Kedro is built upon our collective best-practice (and mistakes) trying to deliver real-world ML applications that have vast amounts of raw unvetted data. We developed Kedro to achieve the following:To address the main shortcomings of Jupyter notebooks, one-off scripts, and glue-code because there is a focus oncreatingmaintainable data science codeTo enhanceteam collaborationwhen different team members have varied exposure to software engineering conceptsTo increase efficiency, because applied concepts like modularity and separation of concerns inspire the creation ofreusable analytics codeThe humans behind KedroKedro is maintained bya product teamand a number ofcontributors from across the world.Can I contribute?Yes! Want to help build Kedro? Check out ourguide to contributing to Kedro.Where can I learn more?There is a growing community around Kedro. Have a look at theKedro FAQsto find projects using Kedro and links to articles, podcasts and talks.Who likes Kedro?There are Kedro users across the world, who work at start-ups, major enterprises and academic institutions likeAbsa,Acensi,Advanced Programming Solutions SL,AI Singapore,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,Open Data Science LatAm,Prediqt,QuantumBlack,Retrieva,Roche,Sber,Société Générale,Telkomsel,Universidad Rey Juan Carlos,UrbanLogiq,Wildlife Studios,WovenLightandXP.Kedro has also wonBest Technical Tool or Framework for AIin the 2019 Awards AI competition and a merit award for the 2020UK Technical Communication Awards. It is listed on the 2020ThoughtWorks Technology Radarand the 2020Data & AI Landscape.How can I cite Kedro?If you're an academic, Kedro can also help you, for example, as a tool to solve the problem of reproducible research. Use the "Cite this repository" button onour repositoryto generate a citation from theCITATION.cff file.