Big merge from my fork

.github/workflows/sandpaper-main.yaml

@@ -5,8 +5,6 @@ on:
     branches:
       - main
       - master
-  schedule:
-    - cron: '0 0 * * 2'
   workflow_dispatch:
     inputs:
       name:

.github/workflows/sandpaper-version.txt

@@ -1 +1 @@
-0.16.10
+0.16.11

.gitignore

@@ -18,6 +18,7 @@ site/*
 /*.Rcheck/
 # RStudio files
 .Rproj.user/
+*.Rproj
 # produced vignettes
 vignettes/*.html
 vignettes/*.pdf

MAINTENANCE.md

@@ -1,4 +1,6 @@
-# Site Structure and Maintenance
+---
+title: "Site Structure and Maintenance"
+---
 
 This site depends strongly on GitHub infrastructure, and a number of
 operational decisions have been made during the development process

README.md

@@ -7,11 +7,12 @@ This lesson teaches the basics of interacting with high-performance computing
 
 ## Using this material
 
-NOTE: This is *not* Carpentries boilerplate! Please read carefully.
+NOTE: This lesson is being transitioned to Carpentries Workbench but is still *not* Carpentries boilerplate! 
+Instructions below still need to be edited to reflect the transition. Proceed with caution.
 
-1. Follow the instructions found in The Carpentries' [example lesson][ex-lesson]
+1. ~~Follow the instructions found in The Carpentries' [example lesson][ex-lesson]
   to create a repository for your lesson. Install Ruby, Make, and Jekyll
-  following the instructions [here][setup].
+  following the instructions [here][setup].~~
 
 2. For easier portability, we use snippets of text and code to capture inputs
   and outputs that are host- or site-specific and cannot be scripted. These
@@ -37,17 +38,17 @@ NOTE: This is *not* Carpentries boilerplate! Please read carefully.
   or omit episodes, by editing the configuration block under `episode_names`
   in this file.
 
-4. Set the environment variable `HPC_JEKYLL_CONFIG` to the relative path of the
-  configuration file in your snippets folder:
+4. ~~Set the environment variable `HPC_JEKYLL_CONFIG` to the relative path of the
+  configuration file in your snippets folder:~~
 
   ```bash
   export HPC_JEKYLL_CONFIG=_includes/snippets_library/.../_config_options.yml
   ```
 
-5. Preview the lesson locally, by running `make serve`. You can then view the
+5. ~~Preview the lesson locally, by running `make serve`. You can then view the
   website in your browser, following the links in the output (usually,
   <https://localhost:4000>). Pages will be automatically regenerated every
-  time you write to them.
+  time you write to them.~~
 
 6. If there are discrepancies in the output, edit the snippet file containing
   it, or create a new one and customize.
@@ -67,6 +68,7 @@ NOTE: This is *not* Carpentries boilerplate! Please read carefully.
   future will probably not be accepted.
 
 ## Deploying a Customized Lesson
+**While this lesson is in transition, we do not recommend customizing**
 
 The steps above will help you port the default HPC Intro lesson to your
 specific cluster, but the changes will only be visible on your local machine.

config.yaml

@@ -20,7 +20,7 @@ carpentry: 'cp'
 title: 'Introduction to High-Performance Computing'
 
 # Date the lesson was created (YYYY-MM-DD, this is empty by default)
-created: 2017-03-24 
+created: 2017-03-24
 
 # Comma-separated list of keywords for the lesson
 keywords: 'software, data, lesson, The Carpentries'
@@ -33,7 +33,7 @@ life_cycle: 'alpha'
 license: 'CC-BY 4.0'
 
 # Link to the source repository for this lesson
-source: 'https://github.com/tobyhodges/probable-pancake'
+source: 'https://github.com/ocaisa/probable-pancake'
 
 # Default branch of your lesson
 branch: 'main'
@@ -64,26 +64,29 @@ contact: 'team@carpentries.org'
 # - another-learner.md
 
 # Order of episodes in your lesson
-episodes: 
-- 10-hpc-intro.md
-- 11-connecting.md
-- 12-cluster.md
-- 13-scheduler.md
-- 14-environment-variables.md
-- 15-modules.md
-- 16-transferring-files.md
-- 17-parallel.md
-- 18-resources.md
-- 19-responsibility.md
+episodes:
+  - 10-hpc-intro.Rmd
+  - 11-connecting.Rmd
+  - 12-cluster.Rmd
+  - 13-scheduler.Rmd
+  - 14-environment-variables.Rmd
+  - 15-modules.Rmd
+  - 16-transferring-files.Rmd
+  - 17-parallel.Rmd
+  - 18-resources.Rmd
+  - 19-responsibility.Rmd
 
 # Information for Learners
-learners: 
+learners:
+  - setup.md
 
 # Information for Instructors
-instructors: 
+instructors:
+  - instructor-notes.Rmd
 
 # Learner Profiles
-profiles: 
+profiles:
+  - learner-profiles.md
 
 # Customisation ---------------------------------------------
 #
@@ -92,6 +95,6 @@ profiles:
 
 
 carpentry_description: Lesson Description
-url: 'https://tkphd.github.io/hpc-intro-online'
+url: 'https://ocaisa.github.io/probable_pancake'
 analytics: carpentries
 lang: en

episodes/10-hpc-intro.md → episodes/10-hpc-intro.Rmd

@@ -4,6 +4,11 @@ teaching: 15
 exercises: 5
 ---
 
+```{r, echo=FALSE}
+# Source the external configuration script
+source("load_config.R")
+```
+
 ::::::::::::::::::::::::::::::::::::::: objectives
 
 - Describe what an HPC system is
@@ -22,15 +27,15 @@ Frequently, research problems that use computing can outgrow the capabilities
 of the desktop or laptop computer where they started:
 
 - A statistics student wants to cross-validate a model. This involves running
-  the model 1000 times -- but each run takes an hour. Running the model on
+  the model 1000 times — but each run takes an hour. Running the model on
   a laptop will take over a month! In this research problem, final results are
   calculated after all 1000 models have run, but typically only one model is
   run at a time (in **serial**) on the laptop. Since each of the 1000 runs is
   independent of all others, and given enough computers, it's theoretically
   possible to run them all at once (in **parallel**).
 - A genomics researcher has been using small datasets of sequence data, but
   soon will be receiving a new type of sequencing data that is 10 times as
-  large. It's already challenging to open the datasets on a computer --
+  large. It's already challenging to open the datasets on a computer —
   analyzing these larger datasets will probably crash it. In this research
   problem, the calculations required might be impossible to parallelize, but a
   computer with **more memory** would be required to analyze the much larger
@@ -54,7 +59,7 @@ problems in parallel**.
 
 ## Jargon Busting Presentation
 
-Open the [HPC Jargon Buster]({{ site.url }}files/jargon#p1)
+Open the [HPC Jargon Buster](files/jargon.html#p1)
 in a new tab. To present the content, press `C` to open a **c**lone in a
 separate window, then press `P` to toggle **p**resentation mode.
 
@@ -71,48 +76,44 @@ results.
 ## Some Ideas
 
 - Checking email: your computer (possibly in your pocket) contacts a remote
-  machine, authenticates, and downloads a list of new messages; it also
-  uploads changes to message status, such as whether you read, marked as
-  junk, or deleted the message. Since yours is not the only account, the
-  mail server is probably one of many in a data center.
-- Searching for a phrase online involves comparing your search term against
-  a massive database of all known sites, looking for matches. This "query"
+  machine, authenticates, and downloads a list of new messages; it also uploads
+  changes to message status, such as whether you read, marked as junk, or
+  deleted the message. Since yours is not the only account, the mail server is
+  probably one of many in a data center.
+- Searching for a phrase online involves comparing your search term against a
+  massive database of all known sites, looking for matches. This "query"
   operation can be straightforward, but building that database is a
   [monumental task][mapreduce]! Servers are involved at every step.
-- Searching for directions on a mapping website involves connecting your
-  (A) starting and (B) end points by [traversing a graph][dijkstra] in
-  search of the "shortest" path by distance, time, expense, or another
-  metric. Converting a map into the right form is relatively simple, but
-  calculating all the possible routes between A and B is expensive.
+- Searching for directions on a mapping website involves connecting your (A)
+  starting and (B) end points by [traversing a graph][dijkstra] in search of
+  the "shortest" path by distance, time, expense, or another metric. Converting
+  a map into the right form is relatively simple, but calculating all the
+  possible routes between A and B is expensive.
 
 Checking email could be serial: your machine connects to one server and
 exchanges data. Searching by querying the database for your search term (or
-endpoints) could also be serial, in that one machine receives your query
-and returns the result. However, assembling and storing the full database
-is far beyond the capability of any one machine. Therefore, these functions
-are served in parallel by a large, ["hyperscale"][hyperscale] collection of
-servers working together.
-
-
+endpoints) could also be serial, in that one machine receives your query and
+returns the result. However, assembling and storing the full database is far
+beyond the capability of any one machine. Therefore, these functions are served
+in parallel by a large, ["hyperscale"][hyperscale] collection of servers
+working together.
 
 :::::::::::::::::::::::::
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::
 
-
-
 [mapreduce]: https://en.wikipedia.org/wiki/MapReduce
 [dijkstra]: https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
 [hyperscale]: https://en.wikipedia.org/wiki/Hyperscale_computing
 
-
 :::::::::::::::::::::::::::::::::::::::: keypoints
 
-- High Performance Computing (HPC) typically involves connecting to very large computing systems elsewhere in the world.
-- These other systems can be used to do work that would either be impossible or much slower on smaller systems.
+- High Performance Computing (HPC) typically involves connecting to very large
+  computing systems elsewhere in the world.
+- These other systems can be used to do work that would either be impossible or
+  much slower on smaller systems.
 - HPC resources are shared by multiple users.
-- The standard method of interacting with such systems is via a command line interface.
+- The standard method of interacting with such systems is via a command line
+  interface.
 
 ::::::::::::::::::::::::::::::::::::::::::::::::::
-
-