<commit_before>{% set name = "Squidpy" %}
{% set version = "1.2.1" %}

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

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name|lower }}/{{ name|lower }}-{{ version }}.tar.gz
  sha256: a32609afb16e7f7d1675e3ed4b10bab5c9509a9ab5dae7732fc28b399aaece7b

build:
  number: 0
  script: {{ PYTHON }} -m pip install . --no-deps --ignore-installed -vv
  skip: true  # [py<38]

requirements:
  host:
    - pip
    - python
    - setuptools_scm
  run:
    - python
    - aiohttp >=3.8.1
    - anndata >=0.7.4
    - dask-image >=0.5.0
    - dask[array] >=2021.02.0
    - docrep >=0.3.1
    - fsspec >=2021.11.0
    - leidenalg >=0.8.2
    - matplotlib-scalebar >=0.8.0
    - networkx >=2.6.0
    - numba >=0.52.0
    - numpy >=1.18.0
    - omnipath >=1.0.5
    - pandas >=1.2.0
    - Pillow
    - scanpy >=1.8.0
    - scikit-image >=0.19
    - scikit-learn >=0.24.0
    - statsmodels >=0.12.0
    - tifffile !=2022.4.22
    - tqdm >=4.50.2
    - typing_extensions
    - validators >=0.18.2
    - xarray >=0.16.1
    - zarr >=2.6.1

test:
  imports:
    - squidpy

about:
  home: https://github.com/scverse/squidpy
  license: BSD-3-Clause
  license_file: LICENSE
  summary: Spatial Single Cell Analysis in Python
  description: |
    Squidpy is a tool for the analysis and visualization of spatial molecular data.
    It builds on top of Scanpy and AnnData, from which it inherits modularity and scalability.
    It provides analysis tools that leverages the spatial coordinates of the data, as well as tissue images if available.
  doc_url: https://squidpy.readthedocs.io
  dev_url: https://github.com/scverse/squidpy

extra:
  recipe-maintainers:
    - giovp
    - michalk8<commit_msg>Update meta.yml<commit_after>{% set name = "Squidpy" %}
{% set version = "1.2.1" %}

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

source:
  url: https://pypi.io/packages/source/{{ name[0] }}/{{ name|lower }}/{{ name|lower }}-{{ version }}.tar.gz
  sha256: a32609afb16e7f7d1675e3ed4b10bab5c9509a9ab5dae7732fc28b399aaece7b

build:
  number: 0
  script: {{ PYTHON }} -m pip install . -vv
  noarch: python

requirements:
  host:
    - pip
    - python >=3.8
    - setuptools_scm
  run:
    - python >=3.8
    - aiohttp >=3.8.1
    - anndata >=0.7.4
    - dask-image >=0.5.0
    - dask[array] >=2021.02.0
    - docrep >=0.3.1
    - fsspec >=2021.11.0
    - leidenalg >=0.8.2
    - matplotlib-scalebar >=0.8.0
    - networkx >=2.6.0
    - numba >=0.52.0
    - numpy >=1.18.0
    - omnipath >=1.0.5
    - pandas >=1.2.0
    - Pillow >=8.0.0
    - scanpy >=1.8.0
    - scikit-image >=0.19
    - scikit-learn >=0.24.0
    - statsmodels >=0.12.0
    - tifffile !=2022.4.22
    - tqdm >=4.50.2
    - typing_extensions
    - validators >=0.18.2
    - xarray >=0.16.1
    - zarr >=2.6.1
  run_constrained:
    - napari >=0.4.14,<0.5

test:
  imports:
    - {{ name|lower }}
  commands:
    - pip check
  requires:
    - pip

about:
  home: https://github.com/scverse/squidpy
  license: BSD-3-Clause
  license_file: LICENSE
  summary: Spatial Single Cell Analysis in Python
  description: |
    Squidpy is a tool for the analysis and visualization of spatial molecular data.
    It builds on top of Scanpy and AnnData, from which it inherits modularity and scalability.
    It provides analysis tools that leverages the spatial coordinates of the data,
    as well as tissue images if available.
  doc_url: https://squidpy.readthedocs.io
  dev_url: https://github.com/scverse/squidpy

extra:
  recipe-maintainers:
    - giovp
    - michalk8
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