# This file created by conda-build 3.15.1
# meta.yaml template originally from:
# C:\projects\r-textclean-feedstock-27to0\recipe, last modified Sun Sep 30 16:43:23 2018
# ------------------------------------------------

package:
    name: r-textclean
    version: 0.9.3
source:
    fn: textclean_0.9.3.tar.gz
    sha256: 3f6f3b0abaa3567a1d29f5457087aad31277f3c1473747989c9804479881f24d
    url:
        - https://cran.r-project.org/src/contrib/Archive/textclean/textclean_0.9.3.tar.gz
        - https://cran.r-project.org/src/contrib/textclean_0.9.3.tar.gz
build:
    merge_build_host: true
    number: '0'
    rpaths:
        - lib/
        - lib/R/lib/
    string: r351h6115d3f_0
requirements:
    build:
        - m2-gcc-libs 5.3.0 4
        - m2-libbz2 1.0.6 3
        - m2-msys2-runtime 2.5.0.17080.65c939c 3
        - m2-zip 3.0 2
        - msys2-conda-epoch 20160418 1
    host:
        - 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-icu 58.2 heb44b8b_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 4
        - m2w64-mpfr 3.1.4 4
        - m2w64-pcre 8.38 2
        - 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
        - msys2-conda-epoch 20160418 1
        - r-assertthat 0.2.0 r351h6115d3f_1
        - r-base 3.5.1 h8933c1f_1
        - r-bh 1.66.0_1 r351_1
        - r-bindr 0.1.1 r351h6115d3f_1
        - r-bindrcpp 0.2.2 r351h6115d3f_1
        - r-cli 1.0.0 r351h6115d3f_1
        - r-crayon 1.3.4 r351h6115d3f_1
        - r-data.table 1.11.4 r351h6115d3f_2
        - r-dplyr 0.7.6 r351h6115d3f_1
        - r-dtt 0.1_2 r351h6115d3f_1
        - r-english 1.1_4 r351h6115d3f_1
        - r-fansi 0.3.0 r351h6115d3f_0
        - r-glue 1.3.0 r351h301d43c_2
        - r-lattice 0.20_35 r351h6115d3f_0
        - r-lexicon 1.0.0 r351h6115d3f_2
        - r-magrittr 1.5 r351h6115d3f_1
        - r-mgsub 1.5.0 r351h6115d3f_1
        - r-nlp 0.1_11 r351h6115d3f_0
        - r-pillar 1.3.0 r351h6115d3f_0
        - r-pkgconfig 2.0.2 r351h6115d3f_1
        - r-plogr 0.2.0 r351h6115d3f_1
        - r-purrr 0.2.5 r351h6115d3f_1
        - r-qdapregex 0.7.2 r351h6115d3f_1
        - r-r6 2.2.2 r351h6115d3f_1
        - r-rcpp 0.12.17 r351h6115d3f_2
        - r-rlang 0.2.1 r351h301d43c_2
        - r-slam 0.1_43 r351h6115d3f_0
        - r-stringi 1.2.4 r351h6115d3f_1
        - r-syuzhet 1.0.4 r351h6115d3f_1
        - r-textshape 1.6.0 r351h6115d3f_0
        - r-tibble 1.4.2 r351h6115d3f_2
        - r-tidyr 0.8.1 r351h6115d3f_2
        - r-tidyselect 0.2.4 r351h6115d3f_2
        - r-utf8 1.1.4 r351h6115d3f_0
        - r-zoo 1.8_3 r351h6115d3f_0
    run:
        - r-base >=3.5.1,<3.5.2.0a0
        - r-data.table
        - r-english >=1.0_2
        - r-glue >=1.3.0
        - r-lexicon >=1.0.0
        - r-mgsub >=1.5.0
        - r-qdapregex
        - r-stringi
        - r-textshape >=1.0.1
test:
    commands:
        - '"%R%" -e "library(''textclean'')"'
about:
    home: https://github.com/trinker/textclean
    license: GPL-2
    license_family: GPL2
    license_file: C:\bld\r-textclean_1538325933527\_h_env\R\share\licenses\GPL-2
    summary: Tools to clean and process text.  Tools are geared at checking for substrings
        that are not optimal for analysis and replacing or removing them (normalizing)
        with more analysis friendly substrings (see Sproat, Black, Chen, Kumar, Ostendorf,
        & Richards (2001) <doi:10.1006/csla.2001.0169>) or extracting them into new
        variables. For example, emoticons are often used in text but not always easily
        handled by analysis algorithms.  The replace_emoticon() function replaces
        emoticons with word equivalents.
extra:
    copy_test_source_files: true
    final: true
    recipe-maintainers:
        - CurtLH
        - bgruening
        - cbrueffer
        - daler
        - dbast
        - jdblischak
        - johanneskoester
