function mbert_env_setup() not working on my windows 10 machine.

[BraianPita]

mbert_env_setup()

This function is not working correctly and there is little information about it on the documentation. It gives no errors but it doesn't create the conda environment. I tried to create a conda environment manually but I get multiple different errors through the process. I was hoping to get some insight on why it might not be setting up the environment on my windows machine.

[stefangeiss]

I encountered a similar issue
download_mbert(noise = TRUE)
produces
Error in use_condaenv(condaenv = condaenv, conda = miniconda_conda(), :
Unable to locate conda environment 'rectr_condaenv'.

sessionInfo()
R version 4.2.3 (2023-03-15 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 22621)

Matrix products: default

locale:
[1] LC_COLLATE=German_Germany.utf8 LC_CTYPE=German_Germany.utf8 LC_MONETARY=German_Germany.utf8 LC_NUMERIC=C LC_TIME=German_Germany.utf8

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] future_1.32.0 hunspell_3.0.2 rvest_1.0.3 gridExtra_2.3 pbapply_1.6-0 imputeTS_3.3 DescTools_0.99.47 matrixStats_0.62.0 reshape2_1.4.4 zoo_1.8-11
[11] readtext_0.81 stm_1.3.6 udpipe_0.8.10 forcats_0.5.2 purrr_0.3.5 readr_2.1.4 tidyr_1.2.1 ggplot2_3.3.6 tidyverse_1.3.2 stringr_1.5.0
[21] car_3.1-1 carData_3.0-5 quanteda_3.3.0 dplyr_1.0.10 tibble_3.1.8 rectr_0.1.3

loaded via a namespace (and not attached):
[1] googledrive_2.0.0 minqa_1.2.5 colorspace_2.0-3 class_7.3-21 fs_1.5.2 gridtext_0.1.5 ggtext_0.1.2 gld_2.6.6 rstudioapi_0.14
[10] proxy_0.4-27 furrr_0.3.1 listenv_0.9.0 bit64_4.0.5 fansi_1.0.3 mvtnorm_1.1-3 lubridate_1.8.0 ggpattern_1.0.0 xml2_1.3.4
[19] codetools_0.2-19 splines_4.2.3 rootSolve_1.8.2.3 jsonlite_1.8.4 nloptr_2.0.3 broom_1.0.1 dbplyr_2.2.1 png_0.1-8 compiler_4.2.3
[28] httr_1.4.4 backports_1.4.1 assertthat_0.2.1 Matrix_1.5-1 gargle_1.2.1 cli_3.4.1 tools_4.2.3 gtable_0.3.1 glue_1.6.2
[37] lmom_2.9 rappdirs_0.3.3 fastmatch_1.1-3 Rcpp_1.0.9 cellranger_1.1.0 fracdiff_1.5-1 vctrs_0.5.0 urca_1.3-3 nlme_3.1-160
[46] lmtest_0.9-40 timeDate_4021.106 globals_0.16.2 stopwords_2.3 lme4_1.1-30 lifecycle_1.0.3 googlesheets4_1.0.1 MASS_7.3-58.1 scales_1.2.1
[55] vroom_1.6.3 hms_1.1.3 parallel_4.2.3 expm_0.999-6 quantmod_0.4.20 curl_4.3.3 Exact_3.2 reticulate_1.28 stringi_1.7.12
[64] tseries_0.10-52 e1071_1.7-12 TTR_0.24.3 boot_1.3-28.1 rlang_1.0.6 pkgconfig_2.0.3 lattice_0.20-45 stinepack_1.4 bit_4.0.5
[73] tidyselect_1.2.0 parallelly_1.35.0 plyr_1.8.7 magrittr_2.0.3 R6_2.5.1 generics_0.1.3 DBI_1.1.3 pillar_1.9.0 haven_2.5.1
[82] withr_2.5.0 mgcv_1.8-41 xts_0.12.2 abind_1.4-5 nnet_7.3-18 modelr_0.1.9 crayon_1.5.2 utf8_1.2.2 tzdb_0.3.0
[91] grid_4.2.3 readxl_1.4.1 data.table_1.14.4 digest_0.6.30 reprex_2.0.2 forecast_8.18 RcppParallel_5.1.7 munsell_0.5.0 quadprog_1.5-8

[chainsawriot]

@stefangeiss I never use Windows. But you can setup the environment manually.

Run the following in R

#your miniconda path
reticulate::miniconda_path()

#path of the yaml file
system.file("python", "rectr.yml", package = 'rectr') 

In shell (Replace $MINICONDA_PATH and $YAML_PATH accordingly)

$MINICONDA_PATH/bin/conda env create -f=$YAML_PATH -n rectr_condaenv