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PyCast S2S

PyCast S2S is a collection of tools for post-processing climate forecasts. It is tailored towards the integration in operational workflows, allowing for automated bias-correction and forecast evaluation. PyCast is written in Python and uses state-of-the-art libraries for data processing.

Climate forecasting
Earth & Environment
open source
+ 1

Jupyter Notebook
Python

pycmor

A Python package that simplifies the conversion of climate model output into CMOR-compliant formats, supporting CMIP6 and CMIP7 standards. Provides a modular, plugin-based pipeline for processing NetCDF data from diverse Earth system models.

CF-conventions
climate model output
CMIP6
+ 7

Python

py-cordex

py-cordex is a Python library for managing CORDEX grids, handling rotated/projection-based domains, and supporting CMORization of regional climate data. It enables compliant metadata, grid generation, and integration with xarray for climate workflows.

CORDEX
Earth & Environment
python

Python
Makefile

pyMarAI

Neural network model and PyQt5-based user interface for image segmentation of microscopic tumor spheroids. Usable with nnU-Net deep-learning framework. Trained on microscopic images of mouse pheochromocytoma (MPC) cells. Provides pipelines for handling data, running delineation, curating results...

Artifical Intelligence
cancer
Convolutional Neural Networks
+ 6

Python

PyQuickMaps

A slim python library to link maps and sampling data with prediction methods. Needs scipy, numpy, matplotlib, pykrige, osgeo, rasterio.

Data Visualization
Earth & Environment
Predictive Mapping
+ 1

Python

PyTango

PyTango is a python module that exposes to Python the complete Tango C++ API. This means that you can write not only Tango applications (scripts, CLIs, GUIs) that access Tango device servers but also Tango device servers themselves, all of this in pure python.