Updates to the presentation

presentation/00-index-mod.md

@@ -0,0 +1,25 @@
+
+# Introduction
+
+This document describes a few **possible** steps to self-check replication packages before submitting them to a journal. It is not meant to be exhaustive, and it is not meant to be prescriptive. There are **many ways to construc**t a replication package, and many more to check that it works.
+
+## Computational Empathy
+The key ingredient is what I call "**computational empathy**" - thinking about what an unknown person attempting to reproduce the results in your paper might face, **what they might know and assume**, and more importantly, **what they might not know** or know to assume. While the replication package might very well run on your computer, that is by no means evidence that it will run on someone else's computer. 
+
+## Prerequisites {.smaller}
+
+In what follows, we will assume that the replicator satisfies the following conditions:
+
+::: {.incremental}
+
+- they are familiar with their own **operating system** (not yours!)
+- they are somewhat familiar with **how to run code** in the "dominant" programming language in your field (but...)
+- they are **probably not  familiar** with cutting edge methods of running software that you might be using (but want to learn!)
+- they likely have some experience with **how social scientists write code** and prepare data, but may not have your years of experience
+
+:::
+
+## TL;DR
+
+Techy lingo for "**too long, didn't read**". A summary of the most important takeaways will be at the top of each section.
+

presentation/01-run_it_again.md

@@ -35,9 +35,9 @@ Furthermore, it may suggest that you haven't been able to re-run your own code v
 ::: {.incremental}
 
 - ✅ your code runs without problem, after all the debugging.
-- ❓your code runs without manual intervention, and with low effort
-- ❓it actually produces all the outputs
-- ❓your code generates a log file that you can inspect, and that you could share with others.
-- ❓it will run on somebody else's computer
+- [ ] your code runs without manual intervention, and with low effort
+- [ ] it actually produces all the outputs
+- [ ]your code generates a log file that you can inspect, and that you could share with others.
+- [ ] it will run on somebody else's computer
 
 :::

presentation/02-hands_off_running.md

@@ -215,8 +215,8 @@ For examples for **Julia, Python, MATLAB,** and **multi-software scripts**, see
 
 - ✅ your code runs without problem, after all the debugging.
 - ✅your code runs without manual intervention, and with low effort
-- ❓it actually produces all the outputs
-- ❓your code generates a log file that you can inspect, and that you could share with others.
-- ❓it will run on somebody else's computer
+- [ ] it actually produces all the outputs
+- [ ] your code generates a log file that you can inspect, and that you could share with others.
+- [ ] it will run on somebody else's computer
 
 

presentation/03-automatically_saving_figures.md

@@ -87,7 +87,7 @@ Learn how to save tables in robust, reproducible ways. Do not try to copy-paste
 - ✅ your code runs without problem, after all the debugging.
 - ✅your code runs without manual intervention, and with low effort
 - ✅it actually produces all the outputs
-- ❓your code generates a log file that you can inspect, and that you could share with others.
-- ❓it will run on somebody else's computer
+- [ ] your code generates a log file that you can inspect, and that you could share with others.
+- [ ] it will run on somebody else's computer
 
 :::

presentation/04-creating_log_files.md

@@ -200,12 +200,8 @@ which will create a log file with everything that would normally appear on the c
 ## Takeaways
 
 
-::: {.incremental}
-
 - ✅ your code runs without problem, after all the debugging.
 - ✅your code runs without manual intervention, and with low effort
 - ✅it actually produces all the outputs
 - ✅your code generates a log file that you can inspect, and that you could share with others.
-- ❓it will run on somebody else's computer
-
-:::
+- [ ] it will run on somebody else's computer

presentation/05-00-intermezzo.md

@@ -0,0 +1,117 @@
+# Environments 
+
+
+## TL;DR
+
+- Search paths and environments are key concepts to create **portable**, **reproducible** code, by **isolating** each project from others.
+- Methods exist in all (statistical) programming languages
+
+## What is an environment?
+
+From the [renv](https://rstudio.github.io/renv/) documentation:
+
+-   **Isolated**: Installing a new or updated package for one project won't break your other projects, and vice versa. 
+-   **Portable**: Easily transport your projects from one computer to another, *even across different platforms*. 
+-   **Reproducible**: Records the exact package versions you depend on, and ensures those exact versions are the ones that get installed wherever you go.
+
+## What software supports environments?
+
+- R: `renv` package
+- Python: `venv` or `virtualenv` module
+- Julia: `Pkg` module
+
+## "But I use Stata!"
+
+## Hold on...
+
+## Understanding search paths
+
+Generically, all "environments" simply modify where the specific **software searches** (the "search path") for its components, and in particular any supplementary components (packages, libraries, etc.).[^searchpaths]
+
+[^searchpaths]: Formally, this is true for operating systems as well, and in some cases, the operating system and the programming language interact (for instance, in Python).
+
+## Search paths {auto-animate=true}
+
+
+:::: {.columns}
+
+::: {.column width=30%}
+
+- R: `.libPaths()`
+
+:::
+
+::: {.column width=70%}
+
+```{.r code-line-numbers="2-3"}
+> .libPaths()
+[1] "C:/Users/lv39/AppData/Local/R/win-library/4.3"         
+[2] "C:/Users/lv39/AppData/Local/Programs/R/R-4.3.2/library"
+
+```
+
+:::
+
+::::
+
+## Search paths {auto-animate=true}
+
+:::: {.columns}
+
+::: {.column width=30%}
+
+- R: `.libPaths()`
+- Python: `sys.path`
+
+:::
+
+::: {.column width=70%}
+
+```{.python code-line-numbers="4-9"}
+>>> import sys
+>>> from pprint import pprint
+>>> pprint(sys.path)
+['',
+ 'C:\\Users\\lv39\\AppData\\Local\\Programs\\Python\\Python312\\python312.zip',
+ 'C:\\Users\\lv39\\AppData\\Local\\Programs\\Python\\Python312\\DLLs',
+ 'C:\\Users\\lv39\\AppData\\Local\\Programs\\Python\\Python312\\Lib',
+ 'C:\\Users\\lv39\\AppData\\Local\\Programs\\Python\\Python312',
+ 'C:\\Users\\lv39\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages']
+
+```
+
+:::
+
+::::
+
+## Search paths {auto-animate=true}
+
+:::: {.columns}
+
+::: {.column width=30% .smaller}
+
+- R: `.libPaths()`
+- Python: `sys.path`
+- Julia: `DEPOT_PATH` ([Julia docs](https://docs.julialang.org/en/v1/manual/code-loading/))
+
+:::
+
+::: {.column width=70%}
+
+```{.julia code-line-numbers="3-5" .smaller}
+julia> DEPOT_PATH
+3-element Vector{String}:
+ "C:\\Users\\lv39\\.julia"
+ "C:\\Users\\lv39\\.julia\\juliaup\\julia-1.10.0+0.x64.w64.mingw32\\local\\share\\julia"
+ "C:\\Users\\lv39\\.julia\\juliaup\\julia-1.10.0+0.x64.w64.mingw32\\share\\julia"
+
+```
+
+:::
+
+::::
+
+
+## "Yes, but what about Stata?"
+
+> We now have the **ingredients** to understand (project) environments in Stata.