# This file created by conda-build 3.21.6
# meta.yaml template originally from:
# D:\a\1\s\recipe, last modified Thu Dec  2 22:51:54 2021
# ------------------------------------------------

package:
  name: r-udpipe
  version: 0.8.8
source:
  sha256: 2bb59392cb3c67505324bdde4be6cf0d2cf930f496b00bbd37b852510c1d542e
  url:
    - https://cran.r-project.org/src/contrib/Archive/udpipe/udpipe_0.8.8.tar.gz
    - https://cran.r-project.org/src/contrib/udpipe_0.8.8.tar.gz
build:
  merge_build_host: true
  number: '0'
  rpaths:
    - lib/
    - lib/R/lib/
  string: r40ha856d6a_0
requirements:
  build:
    - m2-bash 4.3.042 5
    - m2-coreutils 8.25 102
    - m2-filesystem 2016.04 4
    - m2-gcc-libs 5.3.0 4
    - m2-gmp 6.1.0 3
    - m2-libbz2 1.0.6 3
    - m2-libiconv 1.14 3
    - m2-libintl 0.19.7 4
    - m2-make 4.1 5
    - m2-msys2-runtime 2.5.0.17080.65c939c 3
    - m2-sed 4.2.2 3
    - m2-zip 3.0 2
    - m2w64-binutils 2.25.1 5
    - m2w64-bzip2 1.0.6 6
    - m2w64-crt-git 5.0.0.4636.2595836 2
    - m2w64-gcc 5.3.0 6
    - m2w64-gcc-ada 5.3.0 6
    - m2w64-gcc-fortran 5.3.0 6
    - m2w64-gcc-libgfortran 5.3.0 6
    - m2w64-gcc-libs 5.3.0 7
    - m2w64-gcc-libs-core 5.3.0 7
    - m2w64-gcc-objc 5.3.0 6
    - m2w64-gmp 6.1.0 2
    - m2w64-headers-git 5.0.0.4636.c0ad18a 2
    - m2w64-isl 0.16.1 2
    - m2w64-libiconv 1.14 6
    - m2w64-libmangle-git 5.0.0.4509.2e5a9a2 2
    - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
    - m2w64-make 4.1.2351.a80a8b8 2
    - m2w64-mpc 1.0.3 3
    - m2w64-mpfr 3.1.4 4
    - m2w64-pkg-config 0.29.1 2
    - m2w64-toolchain 5.3.0 7
    - m2w64-toolchain_win-64 2.4.0 0
    - m2w64-tools-git 5.0.0.4592.90b8472 2
    - m2w64-windows-default-manifest 6.4 3
    - m2w64-winpthreads-git 5.0.0.4634.697f757 2
    - m2w64-zlib 1.2.8 10
    - msys2-conda-epoch 20160418 1
  host:
    - _r-mutex 1.0.1 anacondar_1
    - intel-openmp 2021.4.0 h57928b3_3556
    - libblas 3.9.0 12_win64_mkl
    - liblapack 3.9.0 12_win64_mkl
    - m2w64-bwidget 1.9.10 2
    - m2w64-bzip2 1.0.6 6
    - m2w64-expat 2.1.1 2
    - m2w64-fftw 3.3.4 6
    - m2w64-flac 1.3.1 3
    - m2w64-gcc-libgfortran 5.3.0 6
    - m2w64-gcc-libs 5.3.0 7
    - m2w64-gcc-libs-core 5.3.0 7
    - m2w64-gettext 0.19.7 2
    - m2w64-gmp 6.1.0 2
    - m2w64-gsl 2.1 2
    - m2w64-libiconv 1.14 6
    - m2w64-libjpeg-turbo 1.4.2 3
    - m2w64-libogg 1.3.2 3
    - m2w64-libpng 1.6.21 2
    - m2w64-libsndfile 1.0.26 2
    - m2w64-libtiff 4.0.6 2
    - m2w64-libvorbis 1.3.5 2
    - m2w64-libwinpthread-git 5.0.0.4634.697f757 2
    - m2w64-libxml2 2.9.3 3
    - m2w64-mpfr 3.1.4 4
    - m2w64-pcre2 10.34 0
    - m2w64-speex 1.2rc2 3
    - m2w64-speexdsp 1.2rc3 3
    - m2w64-tcl 8.6.5 3
    - m2w64-tk 8.6.5 3
    - m2w64-tktable 2.10 5
    - m2w64-wineditline 2.101 5
    - m2w64-xz 5.2.2 2
    - m2w64-zlib 1.2.8 10
    - mkl 2021.4.0 h0e2418a_729
    - msys2-conda-epoch 20160418 1
    - r-base 4.0.5 hddad469_4
    - r-data.table 1.14.2 r40h6d2157b_0
    - r-lattice 0.20_45 r40h6d2157b_0
    - r-matrix 1.3_4 r40hd2e18ed_0
    - r-rcpp 1.0.7 r40ha856d6a_0
    - tbb 2021.4.0 h2d74725_1
    - ucrt 10.0.20348.0 h57928b3_0
    - vc 14.2 hb210afc_5
    - vs2015_runtime 14.29.30037 h902a5da_5
  run:
    - m2w64-gcc-libs
    - r-base >=4.0,<4.1.0a0
    - r-data.table >=1.9.6
    - r-matrix
    - r-rcpp >=0.11.5
test:
  commands:
    - '"%R%" -e "library(''udpipe'')"'
about:
  home: https://bnosac.github.io/udpipe/en/index.html, https://github.com/bnosac/udpipe
  license: MPL-2.0
  license_family: OTHER
  license_file: LICENSE
  summary: 'This natural language processing toolkit provides language-agnostic ''tokenization'',
    ''parts of speech tagging'', ''lemmatization'' and ''dependency parsing'' of raw
    text. Next to text parsing, the package also allows you to train annotation models
    based on data of ''treebanks'' in ''CoNLL-U'' format as provided at <https://universaldependencies.org/format.html>.
    The techniques are explained in detail in the paper: ''Tokenizing, POS Tagging,
    Lemmatizing and Parsing UD 2.0 with UDPipe'', available at <doi:10.18653/v1/K17-3009>.
    The toolkit also contains functionalities for commonly used data manipulations
    on texts which are enriched with the output of the parser. Namely functionalities
    and algorithms for collocations, token co-occurrence, document term matrix handling,
    term frequency inverse document frequency calculations, information retrieval
    metrics (Okapi BM25), handling of multi-word expressions, keyword detection (Rapid
    Automatic Keyword Extraction, noun phrase extraction, syntactical patterns) sentiment
    scoring and semantic similarity analysis.'
extra:
  copy_test_source_files: true
  final: true
  recipe-maintainers:
    - conda-forge/r
