ENH: Update Build Software (jb==1.04) and anaconda=2025.05

[mmcky]

This PR

• update to use the latest jupyter-book=1.04post1 build, which should be the latest build before jb2
• updates to anaconda==2025.06 which uses python=3.13

the software fixes in quantecon-book-theme enables us to use the latest version of sphinx with jb1 to give us two pathways for upgrading to the latest anaconda.

We will switch to jb2 once all features we require are supported.

This comes packaged with some nice upgrades to the pdf around exercises.

• update quantecon.manual with restrictions around use of figures nested inside other directives like solution and exercise nodes for pdf generation. We need to use image instead as figure cause latex to fail in the new mini-page environment used for exercises (c526af5)
• run a full test build (remove execution cache)
• update sphinx-tojupyter==0.3.1

[github-actions]

🚀 Deployed on https://688c1323756f325987a50e83--epic-agnesi-957267.netlify.app

[mmcky]

@kp992 would you have time to double check this build looks good on your end? There are a lot of software changes going on here with the various updates. It is looking good to me, but if you spot any regressions that would be useful to know.

https://6881a00889e1d06b90fae1ac--epic-agnesi-957267.netlify.app/

[kp992]

This looks great. Thanks @mmcky. I verified the 3 lecture updates and looks fine to me.

[mmcky]

@HumphreyYang @kp992 @bishmaybarik @nisha617 @longye-tian @shlff

This lecture build

https://6886e2a31960c154a8e4d1d0--epic-agnesi-957267.netlify.app/

has updated the entire software stack including the latest anaconda=2025.06 and python=3.13 as you can see from

https://6886e2a31960c154a8e4d1d0--epic-agnesi-957267.netlify.app/status.html

If you had any time -- would you mind looking at a random lecture and comparing it to the current live lecture equivalent.

I have had a good look across the series, but some additional random checks would be really helpful given the extent of the software changes taking place.

If you are able, please just post which lecture(s) you took a look at, or let me know if you spot any issues. Thanks.

[mmcky]

Final Task:

• re-enable the build cache
• ensure all workflows are tied to python=3.13

[shlff]

Hi @mmcky I randomly reviewed lecture 3. An Introductory Example and noticed the following difference (left: preview; right: online lecture equivalence):

The output also prints the datatype of the values in the preview versions. Not sure if that's a feature we want.

[nisha617]

Hi @mmcky! Lectures 4 and 7 look good to me.

[bishmaybarik]

Hi @mmcky , I checked Lectures 8 and 9. Lecture 8 looks fine to me, however, I think there might be some issues with Lecture 9. I am sharing a screenshot for your reference.

[mmcky]

@shlff @nisha617 @bishmaybarik -- thank you. Rockstars! Appreciate the help.

[kp992]

The output also prints the datatype of the values in the preview versions. Not sure if that's a feature we want.

+1 to this. I think this is the new update with latest numpy version. Probably, we should update it to output the scalar as it was before.

also nice catch @bishmaybarik on testing it on colab. @mmcky it reminds me of colab CI that we had probably on some lecture series. Should we add the colab CI across all the series and test it every month or week?

[mmcky]

Thanks @kp992

Probably, we should update it to output the scalar as it was before.

re: re: NumPy Floats I think we should output what numpy outputs as a default.

[kp992]

agreed. It will keep the users updated with the latest changes.

[mmcky]

thanks @bishmaybarik fixed workspace.md in c0957e2