{% set name = "xarray" %}
{% set version = "2023.6.0" %}

package:
  name: {{ name|lower }}
  version: {{ version }}

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name }}-{{ version }}.tar.gz
  sha256: 267a231ee4efc0341ebbffc6d4ec60e4a66e4849c16e0305c03fcefeca77698c

build:
  number: 0
  skip:  True  # [py<39]
  script: {{ PYTHON }} -m pip install . --no-deps --no-build-isolation -vv

requirements:
  host:
    - python
    - pip
    - setuptools
    - setuptools_scm
    - wheel

  run:
    - python
    - numpy >=1.21
    - pandas >=1.4
    - packaging >=21.3

test:
  imports:
    - xarray
    - xarray.backends
  requires:
    - pip
  commands:
    - pip check

about:
  home: https://github.com/pydata/xarray
  license: Apache-2.0
  license_file: LICENSE
  license_family: Apache
  summary: N-D labeled arrays and datasets in Python.
  description: |
    xarray (formerly xray) is an open source project and Python package
    that makes working with labelled multi-dimensional arrays simple,
    efficient, and fun!

    xarray introduces labels in the form of dimensions, coordinates and
    attributes on top of raw NumPy_-like arrays, which allows for a more
    intuitive, more concise, and less error-prone developer experience.
    The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.

    xarray was inspired by and borrows heavily from pandas_, the popular data analysis package focused on labelled tabular data.
    It is particularly tailored to working with netCDF_ files, which were the source of xarray's data model, and integrates tightly with dask_ for parallel computing.
  dev_url: https://github.com/pydata/xarray
  doc_url: https://docs.xarray.dev/en/stable/

extra:
  recipe-maintainers:
    - jhamman
    - ocefpaf
    - shoyer