enchant2.yaml

package:
  name: enchant2
  version: 2.8.2
  epoch: 3
  description: enchant spellchecking library
  copyright:
    - license: LGPL-2.1-only

environment:
  contents:
    packages:
      - autoconf
      - automake
      - build-base
      - busybox
      - ca-certificates-bundle
      - coreutils
      - glib-dev
      - groff
      - hunspell-dev
      - libtool
      - patch
      - pkgconf-dev
      - vala

pipeline:
  - uses: git-checkout
    with:
      repository: https://github.com/AbiWord/enchant
      tag: v${{package.version}}
      expected-commit: 2e2739acea4926ae2584823b5f75480243b191df

  - runs: ./bootstrap

  - uses: autoconf/configure
    with:
      opts: |
        --with-hunspell \
        --enable-relocatable

  - uses: autoconf/make

  - uses: autoconf/make-install

  - uses: strip

subpackages:
  - name: enchant2-dev
    pipeline:
      - uses: split/dev
    test:
      pipeline:
        - uses: test/pkgconf
        - uses: test/tw/ldd-check

  - name: enchant2-doc
    description: enchant2 docs
    pipeline:
      - uses: split/manpages
    test:
      pipeline:
        - uses: test/docs

update:
  enabled: true
  git:
    strip-prefix: v

test:
  environment:
    contents:
      packages:
        - enchant2-dev
        - hunspell-dev
        - hunspell-dictionaries-all
        - py3-pip
        - python3
  pipeline:
    - runs: |
        pip3 install spello pyenchant
        enchant-2 -v
        enchant-2 -h
        enchant-lsmod-2 -v
        enchant-lsmod-2 -h
    - runs: |
        python -c '
        import enchant
        from spello.model import SpellCorrectionModel

        d = enchant.Dict("en_US")

        word = "recieve"
        assert not d.check(word), f"{word} should be misspelled"
        suggestions = d.suggest(word)
        expected_suggestions = ["receive", "relieve", "reverie"]
        assert set(expected_suggestions).issubset(set(suggestions)), f"Suggestions for {word} are incorrect. Got: {suggestions}"

        sp = SpellCorrectionModel(language="en")
        sp.train(["I want to play cricket", "this is a text corpus"])

        sentence = "i wnt to plai kricket"
        correction = sp.spell_correct(sentence)
        expected_correction = {
            "original_text": "i wnt to plai kricket",
            "spell_corrected_text": "i want to play cricket",
            "correction_dict": {
                "wnt": "want",
                "plai": "play",
                "kricket": "cricket"
            }
        }
        assert correction == expected_correction, f"Correction for {sentence} is incorrect. Expected: {expected_correction}, but got: {correction}"'
    - uses: test/tw/ldd-check