Full reproducibility source code for testing if the inhomog and gevolution relativistic cosmological simulation packages satisfy a perturbative test, and publishing the results.
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Boud Roukema d9b47736f8 Fix bug #63043; bypass bug #62700. 2 weeks ago
reproduce Fix bug #63043; bypass bug #62700. 2 weeks ago
tex Update to Maneage 775fc03..27ff6f7 3 months ago
.dir-locals.el Configure step: compiler checks done before basic settings 3 years ago
.file-metadata Minor typo corrected in referencing Libidn 2 years ago
.gitignore Updated Git, Coreutils and Emacs, new script to prepare tarballs 5 months ago
COPYING Added generic copying/license file to top 4 years ago
README-hacking.md IMPORTANT: download.mk removed, content moved to initialize.mk 4 months ago
README.md Merge branch 'gevcurvtest' into maneage_merge_b 2 months ago
TODO Notation to clarify 2.0; TODO note on R dependencies 11 months ago
paper.tex Minor copyediting 3 months ago
project Update to Maneage 775fc03..27ff6f7 3 months ago

README.md

Reproducible source for Borkowska & Roukema (2022)

Copyright (C) 2018-2022 Mohammad Akhlaghi mohammad@akhlaghi.org Copyright (C) 2020-2022 Justyna Borkowska, Boud Roukema See the end of the file for license conditions.

This is the reproducible project source for the paper titled "Does relativistic cosmology software handle emergent volume evolution?", by Justyna Borkowska and Boudewijn F. Roukema that is submitted for peer review and available as the preprint ArXiv:2112.14174 and at Zenodo.6794222.

To reproduce the results and final paper, the only dependency is a minimal Unix-based building environment including a C and C++ compiler (already available on your system if you have ever built and installed software from source) and a downloader (Wget or cURL). Git is not mandatory: if you don't have Git to run the first command below, go to the URL given in the command on your browser, and download the project's source (there is a button to download a compressed tarball of the project). If you have received this source from ArXiv:2112.14174 or Zenodo.6794222 (without any .git directory inside), please see the "Building project tarball" section below.

$ git clone https://codeberg.org/boud/gevcurvtest
$ mkdir tmp_build && pwd  # remember the name of this temporary build directory
$ cd gevcurvtest
$ ./project configure  # give the name of the temporary build directory when asked
$ ./project configure --existing-conf # sometimes you may need this second try
$ ./project make

This paper is made reproducible using Maneage (MANaging data linEAGE). To learn more about its purpose, principles and technicalities, please see README-hacking.md, or the Maneage webpage at https://maneage.org.

Resources required

The './project configure' (download/compile/install) component of 'gevcurvtest' will take roughly:

  • assuming: cpus: on 4 cores at 2.0-2.5 GHz
  • time: about 2-3 hours of wall clock time
  • memory: about 10 Gb of RAM at the highest load
  • disk: about 5 Gb of disk space in the .build/software/ directory

The cpu, time, memory and disk resources requirements of './project make' for 'gevcurvtest' are roughly:

  • assuming: cpus: at least 4 threads
  • time: less than 3-4 hours of wall clock time
  • memory: less than 5 Gb
  • disk: less than 4 Gb in .build/analysis/

Building the project

This project was designed to have as few dependencies as possible without requiring root/administrator permissions.

  1. Necessary dependencies:

    1.1: Minimal software building tools like C compiler, Make, and other tools found on any Unix-like operating system (GNU/Linux, BSD, Mac OS, and others). All necessary dependencies will be built from source (for use only within this project) by the ./project configure script (next step).

    1.2: (OPTIONAL) Tarball of dependencies. If they are already present (in a directory given at configuration time), they will be used. Otherwise, a downloader (wget or curl) will be necessary to download any necessary tarball. The necessary tarballs are also collected in the archived project on zenodo.6794222. Unpack that tarball and you should see all the tarballs of this project's software. When ./project configure asks for the "software tarball directory", give the address of the unpacked directory that has all the tarballs.

  2. Configure the environment (top-level directories in particular) and build all the necessary software for use in the next step. It is recommended to set directories outside the current directory. Please read the description of each necessary input clearly and set the best value. Note that the configure script also downloads, builds and locally installs (only for this project, no root privileges necessary) many programs (project dependencies). So it may take a while to complete.

    $ ./project configure
    
  3. Run the following command to reproduce all the analysis and build the final paper.pdf on 4 threads; this should be default by at most your real number of threads divided by 4. If your CPU has a different number of threads, change the number (you can see the number of threads available to your operating system by running ./.local/bin/nproc). For this project, a high number of threads is not needed.

    $ ./project make -j4
    

Building project tarball (possibly from arXiv)

If the paper is also published on arXiv, it is highly likely that the authors also uploaded/published the full project there along with the LaTeX sources. If you have downloaded (or plan to download) this source from arXiv, some minor extra steps are necessary as listed below. This is because this tarball is mainly tailored to automatic creation of the final PDF without using Maneage (only calling LaTeX, not using the './project' command)!

You can directly run 'latex' on this directory and the paper will be built with no analysis (all necessary built products are already included in the tarball). One important feature of the tarball is that it has an extra Makefile to allow easy building of the PDF paper without worring about the exact LaTeX and bibliography software commands.

Only building PDF using tarball (no analysis)

  1. If you got the tarball from arXiv and the arXiv code for the paper is 1234.56789, then the downloaded source will be called 1234.56789 (no suffix). However, it is actually a .tar.gz file. So take these steps to unpack it to see its contents.

    $ arxiv=1234.56789
    $ mv $arxiv $arxiv.tar.gz
    $ mkdir $arxiv
    $ cd $arxiv
    $ tar xf ../$arxiv.tar.gz
    
  2. No matter how you got the tarball, if you just want to build the PDF paper, simply run the command below. Note that this won't actually install any software or do any analysis, it will just use your host operating system (assuming you already have a LaTeX installation and all the necessary LaTeX packages) to build the PDF using the already-present plots data.

    $ make              # Build PDF in tarball without doing analysis
    
  3. If you want to re-build the figures from scratch, you need to make the following corrections to the paper's main LaTeX source (paper.tex): uncomment (remove the starting %) the line containing \newcommand{\makepdf}{}, see the comments above it for more.

Building full project from tarball (custom software and analysis)

As described above, the tarball is mainly geared to only building the final PDF. A few small tweaks are necessary to build the full project from scratch (download necessary software and data, build them and run the analysis and finally create the final paper).

  1. If you got the tarball from arXiv, before following the standard procedure of projects described at the top of the file above (using the ./project script), its necessary to set its executable flag because arXiv removes the executable flag from the files (for its own security).

    $ chmod +x project
    
  2. Make the following changes in two of the LaTeX files so LaTeX attempts to build the figures from scratch (to make the tarball; it was configured to avoid building the figures, just using the ones that came with the tarball).

    • paper.tex: uncomment (remove the starting %) of the line containing \newcommand{\makepdf}{}, see the comments above it for more.

    • tex/src/preamble-pgfplots.tex: set the tikzsetexternalprefix variable value to tikz/, so it looks like this: \tikzsetexternalprefix{tikz/}.

  3. Remove extra files. In order to make sure arXiv can build the paper (resolve conflicts due to different versions of LaTeX packages), it is sometimes necessary to copy raw LaTeX package files in the tarball uploaded to arXiv. Later, we will implement a feature to automatically delete these extra files, but for now, the project's top directory should only have the following contents (where reproduce and tex are directories). You can safely remove any other file/directory.

    $ ls
    COPYING  paper.tex  project  README-hacking.md  README.md  reproduce/  tex/
    

Building on ARM

As of 2021-10-13, very little testing of Maneage has been done on arm64 (tested in aarch64). However, some testing has been done on the PinePhone, running Debian/Mobian. In principle default Maneage branch (not all high-level software have been tested) should run fully (configure + make) from the raw source to the final verified pdf. Some issues that you might need to be aware of are listed below.

Older packages

In old packages that may be still needed and that have an old config.guess file (e.g. from 2002, such as fftw2-2.1.5-4.2, that are not in the base Maneage branch) may crash during the build. A workaround is to provide an updated (e.g. 2018) 'config.guess' file (automake --add-missing --force-missing --copy) in 'reproduce/software/patches/' and copy it over the old file during the build of the package.

An un-killable running job

Vampires may be a problem on the pinephone/aarch64. A "vampire" is defined here as a job that is in the "R" (running) state, using nearly 95-100% of a cpu, for an extremely long time (hours), without producing any output to its log file, and is immune to being killed by the user or root with 'kill -9'. A reboot and relaunch of the './project configure --existing-conf' command is the only solution currently known (as of 2021-10-13) for vampires. These are known to have occurred with linux-image-5.13-sunxi64.

RAM/swap space

Adding atleast 3 Gb of swap space (man swapon, man mkswap, man dd) on the eMMC may help to reduce the chance of having errors due to the lack of RAM.

Time scale

On the PinePhone v1.2b, apart from the time wasted by vampires, expect roughly 24 hours' wall time in total for the full 'configure' phase. The default 'maneage' example calculations, diagrams and pdf production are light and should be very fast.

Building in Docker containers

[Not tested for the gevcurvtest project.]

Docker containers are a common way to build projects in an independent filesystem, and an almost independent operating system. Containers thus allow using GNU/Linux operating systems within proprietary operating systems like macOS or Windows. But without the overhead and huge file size of virtual machines. Furthermore containers allow easy movement of built projects from one system to another without rebuilding. Just note that Docker images are large binary files (+1 Gigabytes) and may not be usable in the future (for example with new Docker versions not reading old images). Containers are thus good for temporary/testing phases of a project, but shouldn't be what you archive for the long term!

Hence if you want to save and move your maneaged project within a Docker image, be sure to commit all your project's source files and push them to your external Git repository (you can do these within the Docker image as explained below). This way, you can always recreate the container with future technologies too. Generally, if you are developing within a container, its good practice to recreate it from scratch every once in a while, to make sure you haven't forgot to include parts of your work in your project's version-controlled source. In the sections below we also describe how you can use the container only for the software environment and keep your data and project source on your host.

Dockerfile for a Maneaged project, and building a Docker image

Below is a series of recommendations on the various components of a Dockerfile optimized to store the built state of a maneaged project as a Docker image. Each component is also accompanied with explanations. Simply copy the code blocks under each item into a plain-text file called Dockerfile, in the same order of the items. Don't forget to implement the suggested corrections (in particular step 4).

NOTE: Internet for TeXLive installation: If you have the project software tarballs and input data (optional features described below) you can disable internet. In this situation, the configuration and analysis will be exactly reproduced, the final LaTeX macros will be created, and all results will be verified successfully. However, no final paper.pdf will be created to visualize/combine everything in one easy-to-read file. Until task 15267 is complete, we need internet to install TeXLive packages (using TeXLive's own package manager tlmgr) in the ./project configure phase. This won't stop the configuration, and it will finish successfully (since all the analysis can still be reproduced). We are working on completing this task as soon as possible, but until then, if you want to disable internet and you want to build the final PDF, please disable internet after the configuration phase. Note that only the necessary TeXLive packages are installed (~350 MB), not the full TeXLive collection!

  1. Summary: If you are already familiar with Docker, then the full Dockerfile to get the project environment setup is shown here (without any comments or explanations, because explanations are done in the next items). Note that the last two COPY lines (to copy the directory containing software tarballs used by the project and the possible input databases) are optional because they will be downloaded if not available. You can also avoid copying over all, and simply mount your host directories within the image, we have a separate section on doing this below ("Only software environment in the Docker image"). Once you build the Docker image, your project's environment is setup and you can go into it to run ./project make manually.

    FROM debian:stable-slim
    RUN apt update && apt install -y gcc g++ wget
    RUN useradd -ms /bin/sh maneager
    RUN printf '123\n123' | passwd root
    USER maneager
    WORKDIR /home/maneager
    RUN mkdir build
    RUN mkdir software
    COPY --chown=maneager:maneager ./project-source /home/maneager/source
    COPY --chown=maneager:maneager ./software-dir   /home/maneager/software
    COPY --chown=maneager:maneager ./data-dir       /home/maneager/data
    RUN cd /home/maneager/source \
        && ./project configure --build-dir=/home/maneager/build \
                               --software-dir=/home/maneager/software \
                               --input-dir=/home/maneager/data
    
  2. Choose the base operating system: The first step is to select the operating system that will be used in the docker image. Note that your choice of operating system also determines the commands of the next step to install core software.

    FROM debian:stable-slim
    
  3. Maneage dependencies: By default the "slim" versions of the operating systems don't contain a compiler (needed by Maneage to compile precise versions of all the tools). You thus need to use the selected operating system's package manager to import them (below is the command for Debian). Optionally, if you don't have the project's software tarballs, and want the project to download them automatically, you also need a downloader.

    # C and C++ compiler.
    RUN apt update && apt install -y gcc g++
    
    # Uncomment this if you don't have 'software-XXXX.tar.gz' (below).
    #RUN apt install -y wget
    
  4. Define a user: Some core software packages will complain if you try to install them as the default (root) user. Generally, it is also good practice to avoid being the root user. Hence with the commands below we define a maneager user and activate it for the next steps. But just in case root access is necessary temporarily, with the passwd command, we are setting the root password to 123.

    RUN useradd -ms /bin/sh maneager
    RUN printf '123\n123' | passwd root
    USER maneager
    WORKDIR /home/maneager
    
  5. Copy project files into the container: these commands make the assumptions listed below. IMPORTANT: you can also avoid copying over all, and simply mount your host directories within the image, we have a separate section on doing this below ("Only software environment in the Docker image").

    • The project's source is in the maneaged/ sub-directory and this directory is in the same directory as the Dockerfile. The source can either be from cloned from Git (highly recommended!) or from a tarball. Both are described above (note that arXiv's tarball needs to be corrected as mentioned above).

    • (OPTIONAL) By default the project's necessary software source tarballs will be downloaded when necessary during the ./project configure phase. But if you already have the sources, its better to use them and not waste network traffic (and resulting carbon footprint!). Maneaged projects usually come with a software-XXXX.tar.gz file that is published on Zenodo (link above). If you have this file, put it in the same directory as your Dockerfile and include the relevant lines below.

    • (OPTIONAL) The project's input data. The INPUT-FILES depends on the project, please look into the project's reproduce/analysis/config/INPUTS.conf for the URLs and the file names of input data. Similar to the software source files mentioned above, if you don't have them, the project will attempt to download its necessary data automatically in the ./project make phase.

    # Make the project's build directory and copy the project source
    RUN mkdir build
    COPY --chown=maneager:maneager ./maneaged /home/maneager/source
    
    # Optional (for software)
    COPY --chown=maneager:maneager ./software-XXXX.tar.gz /home/maneager/
    RUN tar xf software-XXXX.tar.gz && mv software-XXXX software && rm software-XXXX.tar.gz
    
    # Optional (for data)
    RUN mkdir data
    COPY --chown=maneager:maneager ./INPUT-FILES /home/maneager/data
    
  6. Configure the project: With this line, the Docker image will configure the project (build all its necessary software). This will usually take about an hour on an 8-core system. You can also optionally avoid putting this step (and the next) in the Dockerfile and simply execute them in the Docker image in interactive mode (as explained in the sub-section below, in this case don't forget to preserve the build container after you are done).

    # Configure project (build full software environment).
    RUN cd /home/maneager/source \
           && ./project configure --build-dir=/home/maneager/build \
                                  --software-dir=/home/maneager/software \
                                  --input-dir=/home/maneager/data
    
  7. Project's analysis: With this line, the Docker image will do the project's analysis and produce the final paper.pdf. The time it takes for this step to finish, and the storage/memory requirements highly depend on the particular project.

    # Run the project's analysis
    RUN cd /home/maneager/source && ./project make
    
  8. Build the Docker image: The Dockerfile is now ready! In the terminal, go to its directory and run the command below to build the Docker image. We recommend to keep the Dockerfile in an empty directory and run it from inside that directory too. This is because Docker considers that directories contents to be part of the environment. Finally, just set a NAME for your project and note that Docker only runs as root.

    sudo su
    docker build -t NAME ./
    

Interactive tests on built container

If you later want to start a container with the built image and enter it in interactive mode (for example for temporary tests), please run the following command. Just replace NAME with the same name you specified when building the project. You can always exit the container with the exit command (note that all your changes will be discarded once you exit, see below if you want to preserve your changes after you exit).

docker run -it NAME

Running your own project's shell for same analysis environment

The default operating system only has minimal features: not having many of the tools you are accustomed to in your daily command-line operations. But your maneaged project has a very complete (for the project!) environment which is fully built and ready to use interactively with the commands below. For example the project also builds Git within itself, as well as many other high-level tools that are used in your project and aren't present in the container's operating system.

# Once you are in the docker container
cd source
./project shell

Preserving the state of a built container

All interactive changes in a container will be deleted as soon as you exit it. THIS IS A VERY GOOD FEATURE IN GENERAL! If you want to make persistent changes, you should do it in the project's plain-text source and commit them into your project's online Git repository. As described in the Docker introduction above, we strongly recommend to not rely on a built container for archival purposes.

But for temporary tests it is sometimes good to preserve the state of an interactive container. To do this, you need to commit the container (and thus save it as a Docker "image"). To do this, while the container is still running, open another terminal and run these commands:

# These two commands should be done in another terminal
docker container list

# Get 'XXXXXXX' of your desired container from the first column above.
# Give the new image a name by replacing 'NEW-IMAGE-NAME'.
docker commit XXXXXXX NEW-IMAGE-NAME

Copying files from the Docker image to host operating system

The Docker environment's file system is completely indepenent of your host operating system. One easy way to copy files to and from an open container is to use the docker cp command (very similar to the shell's cp command).

docker cp CONTAINER:/file/path/within/container /host/path/target

Only software environment in the Docker image

You can set the docker image to only contain the software environment and keep the project source and built analysis files (data and PDF) on your host operating system. This enables you to keep the size of the Docker image to a minimum (only containing the built software environment) to easily move it from one computer to another. Below we'll summarize the steps.

  1. Get your user ID with this command: id -u.

  2. Make a new (empty) directory called docker temporarily (will be deleted later).

    mkdir docker-tmp
    cd docker-tmp
    
  3. Make a Dockerfile (within the new/empty directory) with the following contents. Just replace UID with your user ID (found in step 1 above). Note that we are manually setting the maneager (user) password to 123 and the root password to '456' (both should be repeated because they must be confirmed by passwd).

    FROM debian:stable-slim
    RUN useradd -ms /bin/sh --uid UID maneager; \
        printf '123\n123' | passwd maneager; \
        printf '456\n456' | passwd root
    USER maneager
    WORKDIR /home/maneager
    RUN mkdir build; mkdir build/analysis
    
  4. Create a Docker image based on the Dockerfile above. Just replace MANEAGEBASE with your desired name (this won't be your final image, so you can safely use a name like maneage-base). Note that you need to have root/administrator previlages when running it, so

    sudo docker build -t MANEAGEBASE ./
    
  5. You don't need the temporary directory any more (the docker image is saved in Docker's own location, and accessible from anywhere).

    cd ..
    rm -rf docker-tmp
    
  6. Put the following contents into a newly created plain-text file called docker-run, while setting the mandatory variables based on your system. The name docker-run is already inside Maneage's .gitignore file, so you don't have to worry about mistakenly commiting this file (which contains private information: directories in this computer).

    #!/bin/sh
    #
    # Create a Docker container from an existing image of the built
    # software environment, but with the source, data and build (analysis)
    # directories directly within the host file system. This script should
    # be run in the top project source directory (that has 'README.md' and
    # 'paper.tex'). If not, replace the '$(pwd)' part with the project
    # source directory.
    
    # MANDATORY: Name of Docker container
    docker_name=MANEAGEBASE
    
    # MANDATORY: Location of "build" directory on this system (to host the
    # 'analysis' sub-directory for output data products and possibly others).
    build_dir=/PATH/TO/THIS/PROJECT/S/BUILD/DIR
    
    # OPTIONAL: Location of project's input data in this system. If not
    # present, a 'data' directory under the build directory will be created.
    data_dir=/PATH/TO/THIS/PROJECT/S/DATA/DIR
    
    # OPTIONAL: Location of software tarballs to use in building Maneage's
    # internal software environment.
    software_dir=/PATH/TO/SOFTWARE/TARBALL/DIR
    
    
    
    
    
    # Internal proceessing
    # --------------------
    #
    # Sanity check: Make sure that the build directory actually exists.
    if ! [ -d $build_dir ]; then
        echo "ERROR: '$build_dir' doesn't exist"; exit 1;
    fi
    
    # If the host operating system has '/dev/shm', then give Docker access
    # to it also for improved speed in some scenarios (like configuration).
    if [ -d /dev/shm ]; then shmopt="-v /dev/shm:/dev/shm";
    else                     shmopt=""; fi
    
    # If the 'analysis' and 'data' directories (that are mounted), don't exist,
    # then create them (otherwise Docker will create them as 'root' before
    # creating the container, and we won't have permission to write in them.
    analysis_dir="$build_dir"/analysis
    if ! [ -d $analysis_dir ]; then mkdir $analysis_dir; fi
    
    # If the data or software directories don't exist, put them in the build
    # directory (they will remain empty, but this helps in simplifiying the
    # mounting command!).
    if ! [ -d $data_dir ]; then
        data_dir="$build_dir"/data
        if ! [ -d $data_dir ]; then mkdir $data_dir; fi
    fi
    if ! [ -d $software_dir ]; then
        software_dir="$build_dir"/tarballs-software
        if ! [ -d $software_dir ]; then mkdir $software_dir; fi
    fi
    
    # Run the Docker image while setting up the directories.
    sudo docker run -v "$software_dir":/home/maneager/tarballs-software \
                    -v "$analysis_dir":/home/maneager/build/analysis \
                    -v "$data_dir":/home/maneager/data \
                    -v "$(pwd)":/home/maneager/source \
                    $shmopt -it $docker_name
    
  7. Make the docker-run script executable.

    chmod +x docker-run
    
  8. You can now start the Docker image by executing your newly added script like below (it will ask for your root password). You will notice that you are in the Docker container with the changed prompt.

    ./docker-run
    
  9. You are now within the container. First, we'll add the GNU C and C++ compilers (which are necessary to build our own programs in Maneage) and the GNU WGet downloader (which may be necessary if you don't have a core software's tarball already). Maneage will build pre-defined versions of both and will use them. But for the very first packages, they are necessary. In the process, by setting the PS1 environment variable, we'll define a color-coding for the interactive shell prompt (red for root and purple for the user).

    su
    echo 'export PS1="[\[\033[01;31m\]\u@\h \W\[\033[32m\]\[\033[00m\]]# "' >> ~/.bashrc
    source ~/.bashrc
    apt update
    apt install -y gcc g++ wget
    exit
    echo 'export PS1="[\[\033[01;35m\]\u@\h \W\[\033[32m\]\[\033[00m\]]$ "' >> ~/.bashrc
    source ~/.bashrc
    
  10. Now that the compiler is ready, we can start Maneage's configuration. So let's go into the project source directory and run these commands to build the software environment.

    cd source
    ./project configure --input-dir=/home/maneager/data \
                        --build-dir=/home/maneager/build \
                        --software-dir=/home/maneager/tarballs-software
    
  11. After the configuration finishes successfully, it will say so. It will then ask you to run ./project make. But don't do that yet. Keep this Docker container open and don't exit the container or terminal. Open a new terminal, and follow the steps described in the sub-section above to preserve (or "commit") the built container as a Docker image. Let's assume you call it MY-PROJECT-ENV. After the new image is made, you should be able to see the new image in the list of images with this command (in yet another terminal):

    docker image list      # In the other terminal.
    
  12. Now that you have safely "committed" your current Docker container into a separate Docker image, you can exit the container safely with the exit command. Don't worry, you won't loose the built software environment: it is all now saved separately within the Docker image.

  13. Re-open your docker-run script and change MANEAGEBASE to MY-PROJECT-ENV (or any other name you set for the environment you committed above).

    emacs docker-run
    
  14. That is it! You can now always easily enter your container (only for the software environemnt) with the command below. Within the container, any file you save/edit in the source directory of the docker container is the same file on your host OS and any file you build in your build/analysis directory (within the Maneage'd project) will be on your host OS. You can even use your container's Git to store the history of your project in your host OS. See the next step in case you want to move your built software environment to another computer.

    ./docker-run
    
  15. In case you want to store the image as a single file as backup or to move to another computer, you can run the commands below. They will produce a single project-env.tar.gz file.

    docker save -o my-project-env.tar MY-PROJECT-ENV
    gzip --best project-env.tar
    
  16. To load the tarball above into a clean docker environment (for example on another system) copy the my-project-env.tar.gz file there and run the command below. You can then create the docker-run script for that system and run it to enter. Just don't forget that if your analysis_dir directory is empty on the new/clean system. So you should first run the same ./project configure ... command above in the docker image so it connects the environment to your source. Don't worry, it won't build any software and should finish in a second or two. Afterwards, you can safely run ./project make and continue working like you did on the old system.

    docker load --input my-project-env.tar.gz
    

Deleting all Docker images

After doing your tests/work, you may no longer need the multi-gigabyte files images, so its best to just delete them. To do this, just run the two commands below to first stop all running containers and then to delete all the images:

docker ps -a -q | xargs docker rm
docker images -a -q | xargs docker rmi -f

This file and .file-metadata (a binary file, used by Metastore to store file dates when doing Git checkouts) are part of the reproducible project mentioned above and share the same copyright notice (at the start of this file) and license notice (below).

This project is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This project is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this project. If not, see https://www.gnu.org/licenses/.