From 4cd09fbd46c44019cb4970b74e207516cbfbb441 Mon Sep 17 00:00:00 2001
From: Marty Oehme <contact@martyoeh.me>
Date: Sat, 11 Oct 2025 08:36:29 +0200
Subject: [PATCH] Add labels to popcorn qmd computations

---
 popcorn.qmd | 15 +++++++++++++--
 1 file changed, 13 insertions(+), 2 deletions(-)

diff --git a/popcorn.qmd b/popcorn.qmd
index a107d9e..7c1171f 100644
--- a/popcorn.qmd
+++ b/popcorn.qmd
@@ -25,7 +25,8 @@ enable its service to run in the background with `ln -s /etc/sv/popcorn
 /var/service`.
 
 ```{python}
-# | echo: false
+#| label: setup
+
 import os
 from typing import Any, Awaitable, Mapping
 
@@ -88,7 +89,7 @@ glance a more 'user-choice'-aligned view of how many aisles the buffet offers,
 and how many of those the users are eating from.
 
 ```{python}
-# | echo: true
+#| label: fig-filesize
 from notebooks.popcorn import plt_filesize
 pplot(plt_filesize)
 ```
@@ -136,6 +137,7 @@ and the number of unique installs (i.e. how many people provide their
 statistics). We will look at both of these in turn.
 
 ```{python}
+#| label: fig-weekly-packages
 from notebooks.popcorn import plt_weekly_packages
 pplot(plt_weekly_packages)
 ```
@@ -155,6 +157,7 @@ unique uploads, in we can see a similar pattern, though even more strongly
 pronounced.
 
 ```{python}
+#| label: fig-unique-installs
 from notebooks.popcorn import plt_unique_installs
 pplot(plt_unique_installs)
 ```
@@ -198,6 +201,7 @@ Next, let's verify that hunch by actually looking at the installed packages
 _per user_ for each day.
 
 ```{python}
+#| label: fig-packages-relative
 from notebooks.popcorn import plt_pkg_relative
 pplot(plt_pkg_relative)
 ```
@@ -257,6 +261,7 @@ packages which take the top-installed spots on users' systems.
 <!-- TODO: perhaps the pre-made ISOs play a role, especially Feb2024? no hang on feb 2025 -->
 
 ```{python}
+#| label: fig-top-packages
 from notebooks.popcorn import plt_top_packages
 pplot(plt_top_packages)
 ```
@@ -309,6 +314,7 @@ available.
 Let's turn to the 'distribution' of package installations.
 
 ```{python}
+#| label: fig-package-distribution
 from notebooks.popcorn import plt_package_distribution
 pplot(plt_package_distribution)
 ```
@@ -383,6 +389,7 @@ themselves.
 Let's start by looking at the prevalence of the different major versions.
 
 ```{python}
+#| label: fig-kernel-versions
 from notebooks.popcorn import plt_kernel_versions
 pplot(plt_kernel_versions)
 ```
@@ -436,6 +443,7 @@ major version as 99. The strange version starts appearing on
 Let's turn to the actual adoption of kernels over time in the next visualization.
 
 ```{python}
+#| label: fig-kernel-timeline
 from notebooks.popcorn import plt_kernel_timeline
 pplot(plt_kernel_timeline)
 ```
@@ -565,6 +573,7 @@ instead: here we just add up all the files reported so far for each day, and
 show the resulting growth line.
 
 ```{python}
+#| label: fig-filesize-cumulative
 from notebooks.popcorn import plt_filesize_cumulative
 outp, _ = plt_filesize_cumulative.run() # pyright: ignore
 outp
@@ -581,6 +590,7 @@ Let's also look at the packages installed on systems for different time slices.
 We'll start with a look at the packages per weekday.
 
 ```{python}
+#| label: fig-weekday-packages
 from notebooks.popcorn import plt_weekday_packages
 pplot(plt_weekday_packages)
 ```
@@ -600,6 +610,7 @@ Tuesdays and Wastebin Wednesdays if you will.
 Alright, but let's also take a look at the package numbers per month instead.
 
 ```{python}
+#| label: fig-month-packages
 from notebooks.popcorn import plt_month_packages
 pplot(plt_month_packages)
 ```