[0KRunning with gitlab-runner 12.4.1 (05161b14) [0;m[0K on renkulab-runner-500GB-12.4.1 m6yQ1wRz [0;msection_start:1590684939:prepare_executor [0K[0KUsing Docker executor with image docker:stable ... [0;m[0KPulling docker image docker:stable ... [0;m[0KUsing docker image sha256:f038f0462ba57cd4635fffba0f75f3f4f7421775ce041956e3af0fee613b227d for docker:stable ... [0;msection_end:1590684946:prepare_executor [0Ksection_start:1590684946:prepare_script [0KRunning on runner-m6yQ1wRz-project-3645-concurrent-0 via b1401e20dcd2... section_end:1590684948:prepare_script [0Ksection_start:1590684948:get_sources [0K[32;1mFetching changes with git depth set to 50...[0;m Initialized empty Git repository in /builds/gitlab/avi.srivastava/adv_scrnaseq_2020/.git/ [32;1mCreated fresh repository.[0;m From https://renkulab.io/gitlab/avi.srivastava/adv_scrnaseq_2020 * [new ref] refs/pipelines/36339 -> refs/pipelines/36339 * [new branch] renku/autosave/avi.srivastava/master/0ef71c9/0ef71c9 -> origin/renku/autosave/avi.srivastava/master/0ef71c9/0ef71c9 [32;1mChecking out e74ed327 as renku/autosave/avi.srivastava/master/0ef71c9/0ef71c9...[0;m [32;1mUpdating/initializing submodules recursively...[0;m Submodule 'adv_scrnaseq_2020' (https://github.com/fmicompbio/adv_scrnaseq_2020.git) registered for path 'adv_scrnaseq_2020' Cloning into '/builds/gitlab/avi.srivastava/adv_scrnaseq_2020/adv_scrnaseq_2020'... Submodule path 'adv_scrnaseq_2020': checked out '1e4926fc686a58af971844858abd1e85784a38a2' section_end:1590684988:get_sources [0Ksection_start:1590684988:restore_cache [0Ksection_end:1590684990:restore_cache [0Ksection_start:1590684990:download_artifacts [0Ksection_end:1590684992:download_artifacts [0Ksection_start:1590684992:build_script [0K[32;1m$ docker login -u gitlab-ci-token -p $CI_JOB_TOKEN http://$CI_REGISTRY[0;m WARNING! Using --password via the CLI is insecure. Use --password-stdin. WARNING! Your password will be stored unencrypted in /root/.docker/config.json. Configure a credential helper to remove this warning. See https://docs.docker.com/engine/reference/commandline/login/#credentials-store Login Succeeded [32;1m$ CI_COMMIT_SHA_7=$(echo $CI_COMMIT_SHA | cut -c1-7)[0;m [32;1m$ docker build --tag $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA_7 .[0;m Sending build context to Docker daemon 1.515GB Step 1/10 : FROM renku/renkulab-bioc:RELEASE_3_11-renku0.10.3-a2b490a ---> 0b7455e603f4 Step 2/10 : RUN pip3 install --upgrade pip && pip3 install --upgrade setuptools wheel ---> Using cache ---> 24f3a34c517f Step 3/10 : COPY requirements.txt /tmp/ ---> Using cache ---> 61affef27c0f Step 4/10 : RUN pip3 install -r /tmp/requirements.txt ---> Using cache ---> 0bebb40901dc Step 5/10 : COPY install.R /tmp/ ---> Using cache ---> 0c3e70a86ffd Step 6/10 : RUN R CMD BATCH /tmp/install.R /tmp/install.Rout ---> Using cache ---> ac3e50fc9ea6 Step 7/10 : RUN pip3 install anndata2ri rpy2 ---> Using cache ---> 863bf04d3c7b Step 8/10 : RUN conda update -n base conda && conda install -c bioconda salmon ---> Using cache ---> 36cc248a5047 Step 9/10 : ENV RETICULATE_PYTHON /opt/conda/bin/python ---> Using cache ---> fbc6079ef1dd Step 10/10 : RUN echo "# available conda environments:" > software_info.txt && conda env list >> software_info.txt && echo "# conda installed packges:" >> software_info.txt && conda list -n base >> software_info.txt && echo "# R installed packages:" >> software_info.txt && R -e "df <- installed.packages(); write.table(df[, 3, drop=FALSE], 'software_info.txt', append = TRUE, quote=FALSE, col.names=FALSE)" ---> Using cache ---> 5a71e5e79437 Successfully built 5a71e5e79437 Successfully tagged registry.renkulab.io/avi.srivastava/adv_scrnaseq_2020:e74ed32 [32;1m$ docker push $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA_7[0;m The push refers to repository [registry.renkulab.io/avi.srivastava/adv_scrnaseq_2020] ad6d4fca7f15: Preparing 31d3c39f4f7b: Preparing 07f472909693: Preparing 8db65fb820a4: Preparing d3fc6f00da14: Preparing fc3f8c6ed452: Preparing 8780fc8227d6: Preparing deffb126cf83: Preparing c757425d6954: Preparing 1d0ac05a9d3d: Preparing 0b36595b25a1: Preparing 4eb590aac189: Preparing 376a33659591: Preparing 3b1549740685: Preparing 5545678e85e0: Preparing 961347879ea8: Preparing 695133b5a3ec: Preparing 7fbc9878cd2f: Preparing 964b072de0ec: Preparing 34eed33aab83: Preparing 466a385e7fd9: Preparing df01fce194f9: Preparing 98f7dc7a500f: Preparing a23a915aa1af: Preparing a8bc77ba8727: Preparing c4e70d8a6063: Preparing cae0f313ad2f: Preparing e8356d1f8311: Preparing a0da82abd0c0: Preparing ba621727a9ce: Preparing c74eb79ddf0d: Preparing 06ef1fba7fab: Preparing cdc02322ea04: Preparing 2bc00e48944d: Preparing 92854490f0e7: Preparing 1cc953b9caf7: Preparing 28ba7458d04b: Preparing 838a37a24627: Preparing a6ebef4a95c3: Preparing b7f7d2967507: Preparing 8780fc8227d6: Waiting deffb126cf83: Waiting c757425d6954: Waiting 1d0ac05a9d3d: Waiting 0b36595b25a1: Waiting 4eb590aac189: Waiting 376a33659591: Waiting 3b1549740685: Waiting 5545678e85e0: Waiting 961347879ea8: Waiting 695133b5a3ec: Waiting 7fbc9878cd2f: Waiting 964b072de0ec: Waiting 34eed33aab83: Waiting 466a385e7fd9: Waiting fc3f8c6ed452: Waiting cdc02322ea04: Waiting 2bc00e48944d: Waiting 838a37a24627: Waiting 92854490f0e7: Waiting a6ebef4a95c3: Waiting b7f7d2967507: Waiting df01fce194f9: Waiting 1cc953b9caf7: Waiting e8356d1f8311: Waiting 28ba7458d04b: Waiting 98f7dc7a500f: Waiting a0da82abd0c0: Waiting c74eb79ddf0d: Waiting 06ef1fba7fab: Waiting a23a915aa1af: Waiting ba621727a9ce: Waiting cae0f313ad2f: Waiting a8bc77ba8727: Waiting c4e70d8a6063: Waiting 07f472909693: Layer already exists d3fc6f00da14: Layer already exists 8db65fb820a4: Layer already exists 31d3c39f4f7b: Layer already exists ad6d4fca7f15: Layer already exists fc3f8c6ed452: Layer already exists 8780fc8227d6: Layer already exists deffb126cf83: Layer already exists c757425d6954: Layer already exists 1d0ac05a9d3d: Layer already exists 0b36595b25a1: Layer already exists 4eb590aac189: Layer already exists 376a33659591: Layer already exists 3b1549740685: Layer already exists 5545678e85e0: Layer already exists 961347879ea8: Layer already exists 695133b5a3ec: Layer already exists 7fbc9878cd2f: Layer already exists 466a385e7fd9: Layer already exists 34eed33aab83: Layer already exists 964b072de0ec: Layer already exists 98f7dc7a500f: Layer already exists df01fce194f9: Layer already exists a23a915aa1af: Layer already exists a8bc77ba8727: Layer already exists c4e70d8a6063: Layer already exists cae0f313ad2f: Layer already exists a0da82abd0c0: Layer already exists e8356d1f8311: Layer already exists ba621727a9ce: Layer already exists c74eb79ddf0d: Layer already exists 06ef1fba7fab: Layer already exists cdc02322ea04: Layer already exists 2bc00e48944d: Layer already exists 92854490f0e7: Layer already exists 1cc953b9caf7: Layer already exists 28ba7458d04b: Layer already exists a6ebef4a95c3: Layer already exists 838a37a24627: Layer already exists b7f7d2967507: Layer already exists e74ed32: digest: sha256:9d5dd9ffe9ffe80e74668c4d4fdb852af40b1dbf45420ae869642aedd45270cb size: 8705 section_end:1590685009:build_script [0Ksection_start:1590685009:after_script [0Ksection_end:1590685011:after_script [0Ksection_start:1590685011:archive_cache [0Ksection_end:1590685013:archive_cache [0Ksection_start:1590685013:upload_artifacts_on_success [0Ksection_end:1590685015:upload_artifacts_on_success [0K[32;1mJob succeeded [0;m