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meta.yaml
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meta.yaml
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{% set name = "xmip" %}
{% set version = "0.7.1" %}
{% set hash = "48611b6e7b503dc4f7b2129bd82bf8c59acc763f73fdecc0770f704bb75697c5" %}
package:
name: {{ name|lower }}
version: {{ version }}
source:
url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
sha256: {{ hash }}
build:
noarch: python
number: 0
script: {{ PYTHON }} -m pip install . -vv
requirements:
host:
- python >=3.7
- pip
- pytest-runner
- setuptools_scm
run:
- python >=3.7
- xarray
- pandas
- numpy
- pint-xarray
- importlib-metadata # Only need for Python < 3.8 (but doesn't hurt on other versions) I think so could be removed in future
test:
imports:
- xmip
commands: python -c "import xmip; assert xmip.__version__ == '{{ version }}', xmip.__version__"
about:
home: https://github.com/jbusecke/xMIP
license: MIT
license_family: MIT
license_file: LICENSE.txt
summary: Some code to homogenize naming and parse variables in an xgcm compatible xarray dataset
description: |
Frustrated with how 'dirty' CMIP6 data still is? Do you just want to run a
simple (or complicated) analysis on various models and end up having to
write logic for each seperate case? Then this package is for you.
Developed during the cmip6-hackathon this package provides utility
functions that play nicely with intake-esm.
dev_url: https://github.com/jbusecke/cmip6_preprocessing
extra:
recipe-maintainers:
- jbusecke