Program Evaluation for Public Service

PMAP 8521 • Spring 2023
Andrew Heiss • Andrew Young School of Policy Studies • Georgia State University

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Quarto + {targets} + {renv} + {xaringan} = magic! 🪄

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How to build the site

1. Install RStudio version 2022.07.1 or later since it has a Quarto installation embedded in it. Otherwise, download and install Quarto separately.
2. Open evalsp23.Rproj to open an RStudio Project.
3. If it’s not installed already, R should try to install the {renv} package when you open the RStudio Project for the first time. If you don’t see a message about package installation, install it yourself by running install.packages("renv") in the R console.
4. Run renv::restore() in the R console to install all the required packages for this project.
5. Run targets::tar_make() in the R console to build everything.
6. 🎉 All done! 🎉 The complete website will be in a folder named _site/.

{targets} pipeline

I use the {targets} package to build this site and all its supporting files. The complete pipeline is defined in _targets.R and can be run in the R console with:

targets::tar_make()

The pipeline does several major tasks:

• Create supporting data files: The problem sets and examples I use throughout the course use many different datasets that come prepackaged in R packages, I downloaded from sources online, or that I generated myself. To make sure I and my students are using the latest, most correct datasets, the functions in R/tar_data.R save and/or generate these datasets prior to building the website.

• Compress project folders: To make it easier to distribute problem sets and in-class activities to students, I compress all the folders in the /projects/ folder so that students can download and unzip a self-contained RStudio Project as a .zip file. These targets are dynamically generated so that any new folder that is added to /projects/ will automatically be zipped up when running the pipeline.

• Render xaringan slides to HTML and PDF: Quarto supports HTML-based slideshows through reveal.js. However, I created all my slides using {xaringan}, which is based on remark.js and doesn’t work with Quarto. Since (1) I recorded all the class videos using my {xaringan} slides with a fancy template I made, and (2) I don’t want to recreate my fancy template in reveal.js yet, I want to keep using {xaringan}.

  The pipeline dynamically generates targets for all the .Rmd files in /slides/ and renders them using R Markdown rather than Quarto.

  The pipeline then uses {renderthis} to convert each set of HTML slides into PDFs.

• Build Quarto website: This project is a Quarto website, which compiles and stitches together all the .qmd files in this project based on the settings in _quarto.yml. See the Quarto website documentation for more details.

• Upload resulting _site/ folder to my remote server: Quarto places the compiled website in a folder named /_site/. The pipeline uses rsync to upload this folder to my personal remote server. This target will only run if the UPLOAD_WEBSITES environment variable is set to TRUE, and it will only work if you have an SSH key set up on my personal server, which only I do.

The complete pipeline looks like this:

(This uses mermaid.js syntax and should display as a graph on GitHub. You can also view it by pasting the code into https://mermaid.live.)

graph LR
  subgraph Graph
    direction LR
    x7ece18ea4dfd37ad(["data_barrels_rct"]):::queued --> x04215792a9a4d36b(["copy_barrels_rct"]):::queued
    x1a70645cdb0e8eb9(["gen_barrels"]):::built --> x7ece18ea4dfd37ad(["data_barrels_rct"]):::queued
    x676cecdcd5eb7813(["data_plot_barrel_dag_obs"]):::queued --> xa7f6f0c1b16f542a(["copy_plot_barrel_dag_obs"]):::queued
    xdf832f8e1f99baf2(["schedule_file"]):::built --> x35552a73efe9c59f(["schedule_ical_data"]):::queued
    x9061f97ff2027ff8(["data_attendance"]):::queued --> x7b056887098d4c56(["copy_attendance"]):::queued
    x9c20b8c56debbe9a(["deploy_script"]):::built --> x78f3e0b711425f1c(["deploy_site"]):::queued
    x7aa56383a054e8ba(["site"]):::queued --> x78f3e0b711425f1c(["deploy_site"]):::queued
    x7b056887098d4c56(["copy_attendance"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    x3b13eed8c2f4209e(["copy_barrels_obs"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    x04215792a9a4d36b(["copy_barrels_rct"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    xbbb6d7ed9a6f640a(["copy_eitc"]):::skipped --> x41092a7251862a9e(["copy_data"]):::queued
    xf17ad1e9c3822d18(["copy_evaluation"]):::skipped --> x41092a7251862a9e(["copy_data"]):::queued
    xf812cd9b8b5444a5(["copy_food_health_politics"]):::built --> x41092a7251862a9e(["copy_data"]):::queued
    xd2260b533f1829cb(["copy_monthly_panel"]):::built --> x41092a7251862a9e(["copy_data"]):::queued
    x2a5bb41380dcc5b0(["copy_penguins"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    xa7f6f0c1b16f542a(["copy_plot_barrel_dag_obs"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    x6271c0b6a170e94e(["copy_plot_barrel_dag_rct"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    x9c50e551b1b09085(["copy_public_housing"]):::skipped --> x41092a7251862a9e(["copy_data"]):::queued
    x0897796b858a5b3d(["copy_wage"]):::queued --> x41092a7251862a9e(["copy_data"]):::queued
    xb4844be3dca7f02b(["project_paths"]):::queued --> x7a8b235bff1bfb75["project_files"]:::queued
    x1917c787a0a4a0fd["project_zips"]:::queued --> x7aa56383a054e8ba(["site"]):::queued
    x4d31f5a49d5ae49f(["schedule_ical_file"]):::queued --> x7aa56383a054e8ba(["site"]):::queued
    x063edd335cc1b36f(["schedule_page_data"]):::queued --> x7aa56383a054e8ba(["site"]):::queued
    xccbb2c85646c611a["xaringan_pdfs"]:::queued --> x7aa56383a054e8ba(["site"]):::queued
    x60c212b45249134a["xaringan_slides"]:::queued --> x7aa56383a054e8ba(["site"]):::queued
    xdf832f8e1f99baf2(["schedule_file"]):::built --> x063edd335cc1b36f(["schedule_page_data"]):::queued
    xccb29afdb6aede8f(["gen_nets"]):::queued --> xbe28472fe2bce29e(["data_nets"]):::queued
    xa48826fcb4dc2e34(["project_paths_change"]):::queued --> xb4844be3dca7f02b(["project_paths"]):::queued
    x20b85e3488818f5e(["gen_data_tutoring"]):::queued --> x5cef82ddbf74dbd2(["gen_data_tutoring_sharp"]):::queued
    x9061f97ff2027ff8(["data_attendance"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    xcd68d1a7c07ebab6(["data_barrels_obs"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x7ece18ea4dfd37ad(["data_barrels_rct"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    xcd2bd51d3f2880dc(["data_bed_nets_real"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x10e4e9d82e7b691d(["data_bed_nets_time_machine"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    xdba7a42d19fbbe49(["data_card"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x068350206b5f4fee(["data_father_educ"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x8288901d8e9e8d55(["data_gapminder"]):::built --> xb453b5ae08dcaee7(["build_data"]):::queued
    x81182810f96b04c1(["data_injury"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x182180f03bcfc8dc(["data_mpg"]):::built --> xb453b5ae08dcaee7(["build_data"]):::queued
    xbe28472fe2bce29e(["data_nets"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    xa3d8306cecf136f4(["data_penguins"]):::skipped --> xb453b5ae08dcaee7(["build_data"]):::queued
    x676cecdcd5eb7813(["data_plot_barrel_dag_obs"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    xc72ce427df7cb6d6(["data_plot_barrel_dag_rct"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x313ad24da404b651(["data_tutoring_fuzzy"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x6182dfd3a1ca6e02(["data_tutoring_sharp"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x7ba0dec890393ab6(["data_village_obs"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x4df77a4d5c017917(["data_village_rct"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x9a78ab75449e880d(["data_wage"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    xb9fb625c05443344(["data_wage2"]):::queued --> xb453b5ae08dcaee7(["build_data"]):::queued
    x1a70645cdb0e8eb9(["gen_barrels"]):::built --> xcd68d1a7c07ebab6(["data_barrels_obs"]):::queued
    xc5cdd24fb6bd9f0e(["gen_village"]):::queued --> x4df77a4d5c017917(["data_village_rct"]):::queued
    x4a210bdf90796bca(["xaringan_files_files"]):::built --> xf4774655f169db90["xaringan_files"]:::queued
    x9d65856d614f77f4(["gen_data_bed_nets_real"]):::queued --> xcd2bd51d3f2880dc(["data_bed_nets_real"]):::queued
    x7a0d40becb063bda(["xaringan_html_files_files"]):::queued --> x0751853b619def05["xaringan_html_files"]:::queued
    xf4774655f169db90["xaringan_files"]:::queued --> x60c212b45249134a["xaringan_slides"]:::queued
    x6deca4ab95db78c5(["gen_data_bed_nets"]):::queued --> x9d65856d614f77f4(["gen_data_bed_nets_real"]):::queued
    x9a78ab75449e880d(["data_wage"]):::queued --> x0897796b858a5b3d(["copy_wage"]):::queued
    xb453b5ae08dcaee7(["build_data"]):::queued --> x1917c787a0a4a0fd["project_zips"]:::queued
    x41092a7251862a9e(["copy_data"]):::queued --> x1917c787a0a4a0fd["project_zips"]:::queued
    x7a8b235bff1bfb75["project_files"]:::queued --> x1917c787a0a4a0fd["project_zips"]:::queued
    x20b85e3488818f5e(["gen_data_tutoring"]):::queued --> x5c240766086c102f(["gen_data_tutoring_fuzzy"]):::queued
    x5c240766086c102f(["gen_data_tutoring_fuzzy"]):::queued --> x313ad24da404b651(["data_tutoring_fuzzy"]):::queued
    x1b5d71f80f0ded23(["gen_data_father_educ"]):::skipped --> x068350206b5f4fee(["data_father_educ"]):::queued
    x60c212b45249134a["xaringan_slides"]:::queued --> x7a0d40becb063bda(["xaringan_html_files_files"]):::queued
    x07bd1301298fd82f(["gen_barrel_dags"]):::queued --> xc72ce427df7cb6d6(["data_plot_barrel_dag_rct"]):::queued
    x5cef82ddbf74dbd2(["gen_data_tutoring_sharp"]):::queued --> x6182dfd3a1ca6e02(["data_tutoring_sharp"]):::queued
    xb91d56300ed67e72(["gen_attendance"]):::built --> x9061f97ff2027ff8(["data_attendance"]):::queued
    xf38d3f5e6365ad72(["workflow_graph"]):::started --> x6e52cb0f1668cc22(["readme"]):::queued
    x0751853b619def05["xaringan_html_files"]:::queued --> xccbb2c85646c611a["xaringan_pdfs"]:::queued
    x07bd1301298fd82f(["gen_barrel_dags"]):::queued --> x676cecdcd5eb7813(["data_plot_barrel_dag_obs"]):::queued
    xcd68d1a7c07ebab6(["data_barrels_obs"]):::queued --> x3b13eed8c2f4209e(["copy_barrels_obs"]):::queued
    xc5cdd24fb6bd9f0e(["gen_village"]):::queued --> x7ba0dec890393ab6(["data_village_obs"]):::queued
    xc72ce427df7cb6d6(["data_plot_barrel_dag_rct"]):::queued --> x6271c0b6a170e94e(["copy_plot_barrel_dag_rct"]):::queued
    x35552a73efe9c59f(["schedule_ical_data"]):::queued --> x4d31f5a49d5ae49f(["schedule_ical_file"]):::queued
    x6deca4ab95db78c5(["gen_data_bed_nets"]):::queued --> x10e4e9d82e7b691d(["data_bed_nets_time_machine"]):::queued
    xa3d8306cecf136f4(["data_penguins"]):::skipped --> x2a5bb41380dcc5b0(["copy_penguins"]):::queued
  end

Fonts and colors

The fonts used throughout the site are Fira Sans Condensed (for headings and titles) and Barlow (for everything else).

The colors for the site and hex logo come from a palette of 8 colors generated from the viridis inferno color map:

viridisLite::viridis(8, option = "inferno", begin = 0.1, end = 0.9)

Licenses

Text and figures: All prose and images are licensed under Creative Commons (CC-BY-NC 4.0)

Code: All code is licensed under the MIT License.