# z - Advanced topic: Reproducible Analytical Pipelines with Nix

## Introduction

Isolated environments are great to run pipelines in a safe and reproducible manner. This vignette details how to build a reproducible analytical pipeline using an environment built with Nix that contains the right version of R and packages.

## An example of a reproducible analytical pipeline using Nix

Suppose that you’ve used `{targets}` to build a pipeline for a project and that you did so using a tailor-made Nix environment. Here is the call to `rix()` that you could have used to build that environment:

    path_default_nix <- tempdir()

    rix(
      r_ver = "4.2.2",
      r_pkgs = c("targets", "tarchetypes", "rmarkdown"),
      system_pkgs = NULL,
      git_pkgs = list(
        package_name = "housing",
        repo_url = "https://github.com/rap4all/housing/",
        commit = "1c860959310b80e67c41f7bbdc3e84cef00df18e"
      ),
      ide = "none",
      project_path = path_default_nix,
      overwrite = TRUE
    )

This call to `rix()` generates the following `default.nix` file:

    let
     pkgs = import (fetchTarball "https://github.com/rstats-on-nix/nixpkgs/archive/2023-02-13.tar.gz") {};

      rpkgs = builtins.attrValues {
        inherit (pkgs.rPackages)
          rmarkdown
          tarchetypes
          targets;
      };

        housing = (pkgs.rPackages.buildRPackage {
          name = "housing";
          src = pkgs.fetchgit {
            url = "https://github.com/rap4all/housing/";
            rev = "1c860959310b80e67c41f7bbdc3e84cef00df18e";
            sha256 = "sha256-s4KGtfKQ7hL0sfDhGb4BpBpspfefBN6hf+XlslqyEn4=";
          };
          propagatedBuildInputs = builtins.attrValues {
            inherit (pkgs.rPackages)
              dplyr
              ggplot2
              janitor
              purrr
              readxl
              rlang
              rvest
              stringr
              tidyr;
          };
        });

      system_packages = builtins.attrValues {
        inherit (pkgs)
          glibcLocales
          nix
          R;
      };

    in

    pkgs.mkShell {
      LOCALE_ARCHIVE = if pkgs.system == "x86_64-linux" then "${pkgs.glibcLocales}/lib/locale/locale-archive" else "";
      LANG = "en_US.UTF-8";
       LC_ALL = "en_US.UTF-8";
       LC_TIME = "en_US.UTF-8";
       LC_MONETARY = "en_US.UTF-8";
       LC_PAPER = "en_US.UTF-8";
       LC_MEASUREMENT = "en_US.UTF-8";

      buildInputs = [ housing rpkgs  system_packages   ];

    }

The environment that gets built from this `default.nix` file contains R version 4.2.2, the `{targets}` and `{tarchetypes}` packages, as well as the `{housing}` packages, which is a package that is hosted on GitHub only with some data and useful functions for the project. Because it is on GitHub, it gets installed using the `buildRPackage` function from Nix. You can use this environment to work on you project, or to launch a `{targets}` pipeline. This GitHub repository contains the finalized project.

On your local machine, you could execute the pipeline in the environment by running this in a terminal:

    cd /absolute/path/to/housing/ && nix-shell default.nix --run "Rscript -e 'targets::tar_make()'"

If you wish to run the pipeline whenever you drop into the Nix shell, you could add a Shell-hook to the generated `default.nix` file:

    path_default_nix <- tempdir()

    rix(
      r_ver = "4.2.2",
      r_pkgs = c("targets", "tarchetypes", "rmarkdown"),
      system_pkgs = NULL,
      git_pkgs = list(
        package_name = "housing",
        repo_url = "https://github.com/rap4all/housing/",
        commit = "1c860959310b80e67c41f7bbdc3e84cef00df18e"
      ),
      ide = "none",
      shell_hook = "Rscript -e 'targets::tar_make()'",
      project_path = path_default_nix,
      overwrite = TRUE
    )

Now, each time you drop into the Nix shell for that project using `nix-shell`, the pipeline gets automatically executed. `{rix}` also features a function called `tar_nix_ga()` that adds a GitHub Actions workflow file to make the pipeline run automatically on GitHub Actions. The GitHub repository linked above has such a file, so each time changes get pushed, the pipeline runs on GitHub Actions and the results are automatically pushed to a branch called `targets-runs`. See the workflow file here. This feature is very heavily inspired and adapted from the `targets::github_actions()` function.