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dplyr: namespace ‘Rcpp’ 0.12.14 is being loaded, but >= 0.12.15 is required

See original GitHub issue

Creating the conda env:

$ conda create -n test_env conda-forge::r-ape conda-forge::r-dplyr conda-forge::r-tidyr conda-forge::r-ggplot2
Solving environment: done


==> WARNING: A newer version of conda exists. <==
  current version: 4.5.8
  latest version: 4.5.9

Please update conda by running

    $ conda update -n base conda



## Package Plan ##

  environment location: /ebio/abt3_projects/software/dev/miniconda3_dev/envs/test_env

  added / updated specs:
    - conda-forge::r-ape
    - conda-forge::r-dplyr
    - conda-forge::r-ggplot2
    - conda-forge::r-tidyr


The following packages will be downloaded:

    package                    |            build
    ---------------------------|-----------------
    r-mgcv-1.8_24              |   r341h470a237_1         2.4 MB  conda-forge
    r-ape-5.1                  |   r341hfc679d8_1         1.5 MB  conda-forge
    r-tidyr-0.8.1              |   r341hfc679d8_1         404 KB  conda-forge
    r-matrix-1.2_14            |   r341h470a237_1         2.4 MB  conda-forge
    ------------------------------------------------------------
                                           Total:         6.7 MB

The following NEW packages will be INSTALLED:

    bzip2:            1.0.6-h470a237_2       conda-forge
    ca-certificates:  2018.4.16-0            conda-forge
    cairo:            1.14.12-he56eebe_3     conda-forge
    curl:             7.61.0-h93b3f91_1      conda-forge
    fontconfig:       2.13.0-h0c61d53_4      conda-forge
    freetype:         2.8.1-hfa320df_1       conda-forge
    gettext:          0.19.8.1-0             conda-forge
    glib:             2.55.0-h464dc38_2      conda-forge
    graphite2:        1.3.11-hfc679d8_0      conda-forge
    gsl:              2.1-2                  conda-forge
    harfbuzz:         1.8.5-h2bb21d5_0       conda-forge
    icu:              58.2-hfc679d8_0        conda-forge
    jpeg:             9c-h470a237_0          conda-forge
    krb5:             1.14.6-0               conda-forge
    libffi:           3.2.1-3                conda-forge
    libgcc:           7.2.0-h69d50b8_2
    libgcc-ng:        7.2.0-hdf63c60_3
    libgfortran:      3.0.0-1
    libiconv:         1.15-h470a237_1        conda-forge
    libpng:           1.6.34-ha92aebf_1      conda-forge
    libssh2:          1.8.0-h5b517e9_2       conda-forge
    libstdcxx-ng:     7.2.0-hdf63c60_3
    libtiff:          4.0.9-he6b73bb_1       conda-forge
    libuuid:          1.0.3-1                conda-forge
    libxcb:           1.13-h470a237_2        conda-forge
    libxml2:          2.9.8-h422b904_2       conda-forge
    ncurses:          5.9-10                 conda-forge
    openssl:          1.0.2o-h470a237_1      conda-forge
    pango:            1.40.14-h9105a7a_2     conda-forge
    pcre:             8.39-0                 conda-forge
    pixman:           0.34.0-2               conda-forge
    pthread-stubs:    0.4-h470a237_1         conda-forge
    r-ape:            5.1-r341hfc679d8_1     conda-forge
    r-assertthat:     0.2.0-r3.4.1_0         conda-forge
    r-base:           3.4.1-4                conda-forge
    r-bh:             1.66.0_1-r3.4.1_0      conda-forge
    r-bindr:          0.1.1-r3.4.1_0         conda-forge
    r-bindrcpp:       0.2.2-r341h9d2a408_0   conda-forge
    r-cli:            1.0.0-r3.4.1_0         conda-forge
    r-colorspace:     1.3_2-r341h470a237_1   conda-forge
    r-crayon:         1.3.4-r3.4.1_0         conda-forge
    r-dichromat:      2.0_0-r3.4.1_0         conda-forge
    r-digest:         0.6.15-r341h470a237_1  conda-forge
    r-dplyr:          0.7.6-r341h9d2a408_0   conda-forge
    r-ggplot2:        3.0.0-r341h6115d3f_0   conda-forge
    r-glue:           1.3.0-r341h470a237_1   conda-forge
    r-gtable:         0.2.0-r3.4.1_0         conda-forge
    r-labeling:       0.3-r3.4.1_0           conda-forge
    r-lattice:        0.20_34-r3.4.1_0       conda-forge
    r-lazyeval:       0.2.1-r341h470a237_1   conda-forge
    r-magrittr:       1.5-r3.4.1_0           conda-forge
    r-mass:           7.3_50-r341hc070d10_1  conda-forge
    r-matrix:         1.2_14-r341h470a237_1  conda-forge
    r-mgcv:           1.8_24-r341h470a237_1  conda-forge
    r-munsell:        0.5.0-r341_0           conda-forge
    r-nlme:           3.1_131-r341ha44fe06_1 conda-forge
    r-pillar:         1.2.2-r341h6115d3f_1   conda-forge
    r-pkgconfig:      2.0.1-r3.4.1_0         conda-forge
    r-plogr:          0.2.0-r341h6115d3f_0   conda-forge
    r-plyr:           1.8.4-r341hfc679d8_1   conda-forge
    r-purrr:          0.2.4-r341h470a237_1   conda-forge
    r-r6:             2.2.2-r3.4.1_0         conda-forge
    r-rcolorbrewer:   1.1_2-r3.4.1_0         conda-forge
    r-rcpp:           0.12.17-r341h9d2a408_1 conda-forge
    r-reshape2:       1.4.3-r341hfc679d8_1   conda-forge
    r-rlang:          0.2.1-r341h470a237_1   conda-forge
    r-scales:         0.5.0-r341hfc679d8_1   conda-forge
    r-stringi:        1.2.3-r341hfc679d8_1   conda-forge
    r-stringr:        1.3.1-r341_0           conda-forge
    r-tibble:         1.4.2-r341h470a237_1   conda-forge
    r-tidyr:          0.8.1-r341hfc679d8_1   conda-forge
    r-tidyselect:     0.2.4-r341hfc679d8_1   conda-forge
    r-utf8:           1.1.3-r341h470a237_1   conda-forge
    r-viridislite:    0.3.0-r3.4.1_0         conda-forge
    r-withr:          2.1.1-r3.4.1_0         conda-forge
    readline:         7.0-0                  conda-forge
    tk:               8.6.8-0                conda-forge
    xorg-kbproto:     1.0.7-h470a237_2       conda-forge
    xorg-libice:      1.0.9-h470a237_4       conda-forge
    xorg-libsm:       1.2.2-h470a237_5       conda-forge
    xorg-libx11:      1.6.5-h470a237_2       conda-forge
    xorg-libxau:      1.0.8-h470a237_6       conda-forge
    xorg-libxdmcp:    1.1.2-h470a237_7       conda-forge
    xorg-libxext:     1.3.3-h470a237_4       conda-forge
    xorg-libxrender:  0.9.10-h470a237_2      conda-forge
    xorg-renderproto: 0.11.1-h470a237_2      conda-forge
    xorg-xextproto:   7.3.0-h470a237_2       conda-forge
    xorg-xproto:      7.0.31-h470a237_7      conda-forge
    xz:               5.2.4-h470a237_0       conda-forge
    zlib:             1.2.11-h470a237_3      conda-forge

Proceed ([y]/n)?


Downloading and Extracting Packages
r-mgcv-1.8_24        |  2.4 MB | ########################################################################################################################################### | 100%
r-ape-5.1            |  1.5 MB | ########################################################################################################################################### | 100%
r-tidyr-0.8.1        |  404 KB | ########################################################################################################################################### | 100%
r-matrix-1.2_14      |  2.4 MB | ########################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
#     $ conda activate test_env
#
# To deactivate an active environment, use
#
#     $ conda deactivate

Testing:

$ conda activate test_env
$ R

> library(dplyr)

Error generated:

Error: package or namespace load failed for ‘dplyr’ in loadNamespace(j <- i[[1L]], c(lib.loc, .libPaths()), versionCheck = vI[[j]]):
 namespace ‘Rcpp’ 0.12.14 is being loaded, but >= 0.12.15 is required

Issue Analytics

State:
Created 5 years ago
Comments:16 (16 by maintainers)

Top GitHub Comments

1reaction

nick-youngblutcommented, Aug 7, 2018

It’s weird though that my older conda install (conda 4.3.29 with R 3.3.2) doesn’t include my home directory R install in the libPaths, but my newer version of conda (conda 4.5.9 with R 3.4.1) does. So the old version of conda + R is not looking in my HOME directory. Why should R installed in a conda env look into a HOME directory? I thought the whole point of conda envs was to isolate the software in the envs.

0reactions

jdblischakcommented, Sep 11, 2018

From a normal Ubuntu 18.04 Docker container:

@bgruening I wasn’t able to reproduce the behavior you observed. Using Ubuntu 18.04 and installing pandas in an environment (via conda activate), I still get an error due to the user-installation of numpy:

docker run --rm -it ubuntu:bionic
# Install conda
apt update
apt install -y --no-install-recommends bzip2 ca-certificates curl
curl -s -L https://repo.continuum.io/miniconda/Miniconda3-4.5.11-Linux-x86_64.sh > miniconda.sh
openssl md5 miniconda.sh | grep e1045ee415162f944b6aebfe560b8fee
bash miniconda.sh -b -p /opt/conda
ln -s /opt/conda/etc/profile.d/conda.sh /etc/profile.d/conda.sh
source /opt/conda/etc/profile.d/conda.sh
conda activate
conda config --set show_channel_urls True
conda config --add channels conda-forge
conda update --all --yes
# Install old version of numpy
# - Had to use Python 3.6. Always got errors with Python 3.7
# - Had to install gcc with APT. Always got error with conda
conda install -y python=3.6
apt install -y gcc
pip install --user 'numpy==1.8.2'
python -c 'import numpy;print( numpy.__version__)'
# 1.8.2
# Create conda environment
conda create -n pandas -y pandas
conda activate pandas
python -c 'import numpy;print( numpy.__version__)'
# 1.8.2
python -c 'import pandas'
# Traceback (most recent call last):
#   File "<string>", line 1, in <module>
#   File "/opt/conda/envs/pandas/lib/python3.6/site-packages/pandas/__init__.py", line 23, in <module>
#     from pandas.compat.numpy import *
#   File "/opt/conda/envs/pandas/lib/python3.6/site-packages/pandas/compat/numpy/__init__.py", line 24, in <module>
#     'this pandas version'.format(_np_version))
# ImportError: this version of pandas is incompatible with numpy < 1.9.0
# your numpy version is 1.8.2.
# Please upgrade numpy to >= 1.9.0 to use this pandas version

But I guess I completely misunderstood the problem here. Nevermind, sorry for the noise.

No need to apologize! I think it is important to discuss and understand this issue with user-installed packages. It is so often over-looked, but it can cause conda users a lot of pain (e.g. this current issue).

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