Explore projects
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Platform Engineering / Modules / ichec-platform-core
GNU General Public License v3.0 or laterCommon platform utilities for use in the team's libraries
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Platform Engineering / Modules / Web / ichec-django-core
GNU Affero General Public License v3.0Core Django functionality - useful for most portals
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MARINERG-i / test-access-service
GNU Affero General Public License v3.0Service to manage test facility access
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Platform Engineering / Modules / Web / ichec-angular-core
GNU Affero General Public License v3.0Core Angular library to support portal development at ICHEC
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MARINERG-i / data-access-service
GNU Affero General Public License v3.0Service to manage project datasets
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MARINERG-i / facility-service
GNU Affero General Public License v3.0Service to manage users, organisations and facilities
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Package to read in a series of extreme precipitation event records from comma-separated-value (CSV) files for different stations, and conduct an extreme event analysis on them (for annual and seasonal periods), including event-counts, exceedance histograms, return periods, and funtional fits with generalized Pareto distritbutions (GPDs).
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This is a self-learning FastAPI backend for the SkillMatch prototype. It leverages SQLModel and Pydantic for defining and validating data models, managing relationships between employees, projects, and skills, and handling database interactions efficiently. The project demonstrates building a structured, scalable API with a clear separation of routers, services, and database layers, suitable for experimentation and learning modern Python backend development.
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Platform Engineering / Modules / Web / ichec-django
GNU Affero General Public License v3.0ICHEC Reference Django Deployment
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Platform Engineering / Modules / CICD / ichec-cicd
GNU General Public License v3.0 or laterICHEC utilities for managing CICD pipelines
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Performance Engineering / recipes / machine_learning
GNU General Public License v3.0 onlyMachine learning examples and benchmarks for HPC applications
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Package to perform bias-correction (and optionally statistical downscaling) of climate projection fields based on quantile mapping between historical simulations and observations.
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