FracturedJson is a fam­ily of util­i­ties that for­mat JSON data in a way that’s easy for hu­mans to read, but fairly com­pact. Arrays and ob­jects are writ­ten on sin­gle lines, as long as they’re nei­ther too long nor too com­plex. When sev­eral such lines are sim­i­lar in struc­ture, they’re writ­ten with fields aligned like a table. Long ar­rays are writ­ten with mul­ti­ple items per line across mul­ti­ple lines.

There are lots of set­tings avail­able to con­trol the out­put, but usu­ally you can ig­nore most of them. FracturedJson pro­duces nice-look­ing out­put from any set of JSON data au­to­mat­i­cally.

You can try it out with the browser for­mat­ter page. It’s also avail­able as a .NET li­brary, a JavaScript/Typescript pack­age, and a Visual Studio Code ex­ten­sion. See here for Python op­tions.

Here’s a sam­ple of out­put us­ing de­fault set­tings. See the Options page for ex­am­ples of what you dif­fer­ent set­tings do.

“BasicObject”  : {

“ModuleId”  : “armor”,

“Name”  : “”,

“Locations”  : [

[11, 2], [11, 3], [11, 4], [11, 5], [11, 6], [11, 7], [11, 8], [11, 9],

[11, 10], [11, 11], [11, 12], [11, 13], [11, 14], [ 1, 14], [ 1, 13], [ 1, 12],

[ 1, 11], [ 1, 10], [ 1, 9], [ 1, 8], [ 1, 7], [ 1, 6], [ 1, 5], [ 1, 4],

[ 1, 3], [ 1, 2], [ 4, 2], [ 5, 2], [ 6, 2], [ 7, 2], [ 8, 2], [ 8, 3],

[ 7, 3], [ 6, 3], [ 5, 3], [ 4, 3], [ 0, 4], [ 0, 5], [ 0, 6], [ 0, 7],

[ 0, 8], [12, 8], [12, 7], [12, 6], [12, 5], [12, 4]

“Orientation”: “Fore”,

“Seed”  : 272691529

“SimilarArrays” : {

“Katherine”: [“blue”, “lightblue”, “black” ],

“Logan”  : [“yellow”, “blue”, “black”, “red”],

“Erik”  : [“red”, “purple” ],

“Jean”  : [“lightgreen”, “yellow”, “black” ]

“SimilarObjects”: [

{ “type”: “turret”, “hp”: 400, “loc”: {“x”: 47, “y”: -4}, “flags”: “S” },

{ “type”: “assassin”, “hp”: 80, “loc”: {“x”: 12, “y”: 6}, “flags”: “Q” },

{ “type”: “berserker”, “hp”: 150, “loc”: {“x”: 0, “y”: 0} },

{ “type”: “pittrap”, “loc”: {“x”: 10, “y”: -14}, “flags”: “S,I” }

Optionally, com­ments can be pre­served. Comments aren’t al­lowed by the of­fi­cial JSON stan­dard, but they’re ubiq­ui­tous, so it’s nice to have the op­tion. FracturedJson tries to keep the com­ments to­gether with what­ever el­e­ments they seem to re­late to.

* Multi-line com­ments

* are fun!

“NumbersWithHex”: [

254 /*00FE*/, 1450 /*5AA*/ , 0 /*0000*/, 36000 /*8CA0*/, 10 /*000A*/,

199 /*00C7*/, 15001 /*3A99*/, 6540 /*198C*/

/* Elements are keen */

“Elements”  : [

{ /*Carbon*/ “Symbol”: “C”, “Number”: 6, “Isotopes”: [11, 12, 13, 14] },

{ /*Oxygen*/ “Symbol”: “O”, “Number”: 8, “Isotopes”: [16, 18, 17 ] },

{ /*Hydrogen*/ “Symbol”: “H”, “Number”: 1, “Isotopes”: [ 1, 2, 3 ] },

{ /*Iron*/ “Symbol”: “Fe”, “Number”: 26, “Isotopes”: [56, 54, 57, 58] }

// Not a com­plete list…

“Beatles Songs” : [

“Taxman”, // George

“Hey Jude”, // Paul

“Act Naturally”, // Ringo

“Ticket To Ride” // John

Most JSON li­braries give you a choice be­tween two for­mat­ting op­tions. Minified JSON is very ef­fi­cient, but dif­fi­cult for a per­son to read.

{“AttackPlans”:[{“TeamId”:1,“Spawns”:[{“Time”:0.0,“UnitType”:“Grunt”,“SpawnPointIndex”:0},{“Time”:0.0,“UnitType”:“Grunt”,“SpawnPointIndex”:0},{“Time”:0.0,“UnitType”:“Grunt”,“SpawnPointIndex”:0}]}],“DefensePlans”:[{“TeamId”:2,“Placements”:[{“UnitType”:“Archer”,“Position”:[41,7]},{“UnitType”:“Pikeman”,“Position”:[40,7]},{“UnitType”:“Barricade”,“Position”:[39,7]}]}]}

Most beau­ti­fied/​in­dented JSON, on the other hand, is too spread out, of­ten mak­ing it dif­fi­cult to take in quickly or to scan for spe­cific in­for­ma­tion.

“AttackPlans”: [

“TeamId”: 1,

“Spawns”: [

“Time”: 0,

“UnitType”: “Grunt”,

“SpawnPointIndex”: 0

“Time”: 0,

“UnitType”: “Grunt”,

“SpawnPointIndex”: 0

“Time”: 0,

“UnitType”: “Grunt”,

“SpawnPointIndex”: 0

“DefensePlans”: [

“TeamId”: 2,

“Placements”: [

“UnitType”: “Archer”,

“Position”: [

41,

7

“UnitType”: “Pikeman”,

“Position”: [

40,

7

“UnitType”: “Barricade”,

“Position”: [

39,

7

FracturedJson tries to for­mat data like a per­son would. Containers are kept to sin­gle lines as long as they’re not too com­plex and not too long. If sev­eral suc­ces­sive in­line ar­rays or ob­jects are sim­i­lar enough, they will be for­mat­ted as a table.

“AttackPlans” : [

“TeamId”: 1,

“Spawns”: [

{“Time”: 0, “UnitType”: “Grunt”, “SpawnPointIndex”: 0},

{“Time”: 0, “UnitType”: “Grunt”, “SpawnPointIndex”: 0},

{“Time”: 0, “UnitType”: “Grunt”, “SpawnPointIndex”: 0}

“DefensePlans”: [

“TeamId”  : 2,

“Placements”: [

{ “UnitType”: “Archer”, “Position”: [41, 7] },

{ “UnitType”: “Pikeman”, “Position”: [40, 7] },

{ “UnitType”: “Barricade”, “Position”: [39, 7] }

FracturedJson uses four types of for­mat­ting: in­lined, com­pact mul­ti­line ar­ray, table and ex­panded.

When pos­si­ble, sec­tions of the doc­u­ment are writ­ten in­lined, as long as that does­n’t make them too long or too com­plex (as de­ter­mined by the set­tings). “Complexity” refers to how deeply nested an ar­ray or ob­jec­t’s con­tents are.

{ “UnitType”: “Archer”, “Position”: [41, 7] }

Use the set­ting MaxInlineComplexity to con­trol how much nest­ing is al­lowed on one line.

The next op­tion, for ar­rays, is to write them with mul­ti­ple items per line, across mul­ti­ple lines.

[19, 2], [ 3, 8], [14, 0], [ 9, 9], [ 9, 9], [ 0, 3], [10, 1],

[ 9, 1], [ 9, 2], [ 6, 13], [18, 5], [ 4, 11], [12, 2]

Use the set­ting MaxCompactArrayComplexity to con­trol how deeply nested items can be when arranged this way, or use -1 to dis­able this fea­ture.

If an ar­ray or ob­ject con­tains in­lin­e­able items of the same type, they can be for­mat­ted in a tab­u­lar for­mat. With enough room, all fields at any depth are lined up (and re­ordered if nec­es­sary).

“Rect” : { “position”: {“x”: -44, “y”: 3.4 }, “color”: [0, 255, 255] },

“Point”: { “position”: { “y”: 22  , “z”: 3} },

“Oval” : { “position”: {“x”: 140, “y”: 0.04 }, “color”: “#7f3e96″ },

“Plane”: { “position”: null, “color”: [0, 64, 64] }

Danish women vac­ci­nated with the 4-valent hu­man pa­pil­lo­mavirus (HPV) vac­cine (HPV types: 6/11/16/18) at age 14 in 2008 reached screen­ing age in 2017, al­low­ing as­sess­ment of long-term ef­fects on preva­lence, per­sis­tence and in­ci­dence of HPV in­fec­tions.

To ex­am­ine the HPV sta­tus of cer­vi­cal sam­ples over time among women vac­ci­nated as girls.

Between February 2017 and February 2024, resid­ual ma­te­r­ial from cy­tol­ogy-analysed sam­ples col­lected through the ‘Trial23’ study, part of the na­tional screen­ing pro­gramme, was tested for HPV16/18 and non-vac­cine high-risk (HR) HPV types. Prevalence in first, sec­ond and third sam­ples, and per­sis­tence and in­ci­dence be­tween sam­ples were cal­cu­lated.

Over 7 years, 8,659 women pro­vided at least one sam­ple, 5,835 at least two and 2,461 at least three. In 7,800 vac­ci­nated women, HPV16/18 preva­lence was 0.4% (95% con­fi­dence in­ter­val (CI): 0.2–0.5), 0.3% (95% CI: 0.1–0.4) and 0.2% (95% CI: 0.0–0.4) in three con­sec­u­tive sam­ples. Prevalence of non-vac­cine HR HPV was 32% (95% CI: 31–33), 28% (95% CI: 27–29) and 31% (95% CI: 29–33). Persistence of HPV16/18 and non-vac­cine HPV among vac­ci­nated women was 40% and 53%. In ad­justed analy­ses com­par­ing vac­ci­nated vs un­vac­ci­nated women, in­ci­dence was sig­nif­i­cantly lower for HPV16/18 (adjusted rel­a­tive risk (aRR)

Our study pro­vides real-world ev­i­dence of sta­ble pro­tec­tion against HPV16/18 in­fec­tions in women vac­ci­nated as girls. Less in­ten­sive screen­ing seems rea­son­able un­til women vac­ci­nated with the 9-valent vac­cine reach screen­ing age, when screen­ing should be re­con­sid­ered.

January 2026 will mark 10 years since I started stor­ing my per­sonal fi­nances in plain text files us­ing Beancount. Since January 2016, I’ve taken out about 30-45 min­utes every sin­gle month to down­load my monthly bank state­ments and im­port them into my Beancount ledger.

There’s a lot to talk about here, but let’s start with some fun num­bers!

10 years of fi­nan­cial trans­ac­tions is a lot of data! All in all, my ledger con­tains over 45,000 lines of Beancount en­tries spread across 16 plain text files. All of it is stored in a fi­nances di­rec­tory (version con­trolled) on my lap­top. Here’s a snap­shot:

❯ find . -name “*.beancount” | xargs wc -l

4037 ./includes/2020.beancount

3887 ./includes/2018.beancount

27 ./includes/cash.beancount

4398 ./includes/2021.beancount

5531 ./includes/2019.beancount

5267 ./includes/2022.beancount

3287 ./includes/2017.beancount

5506 ./includes/2024.beancount

5606 ./includes/2023.beancount

1454 ./includes/2016.beancount

1089 ./includes/open/04-expenses.beancount

66 ./includes/open/03-income.beancount

11 ./includes/open/05-liabilities.beancount

37 ./includes/open/02-assets.beancount

1 ./includes/open/01-equity.beancount

4807 ./main.beancount

45011 to­tal

Running bean-query on main.bean­count tells me I have about 10,000 trans­ac­tions in to­tal, that in turn con­tain about 20,000 post­ings (in dou­ble-en­try book­keep­ing, one trans­ac­tion may have mul­ti­ple post­ings).

❯ uv run bean-query main.bean­count

Input file: “Goel”

Ready with 12466 di­rec­tives (19743 post­ings in 9895 trans­ac­tions).

bean­query>

There are 1086 ac­counts in to­tal.

bean­query> se­lect count(*) from (select dis­tinct(ac­count));

coun

1086

… which does not mean that there are 1086 bank ac­counts. Accounts in Beancount are vir­tual, and you can cre­ate as many as you like. Imagine one ac­count for cat­e­go­riz­ing su­per­mar­ket spend­ing, one for track­ing your in­come, one for your Netflix sub­scrip­tion, and so on.

Next, there are about 500 doc­u­ments in the repos­i­tory.

❯ find doc­u­ments/ -name “*.pdf” | wc -l

507

Beancount lets you at­tach doc­u­ments (e.g. re­ceipts or in­voices) to trans­ac­tions, that makes book­keep­ing very ef­fi­cient. I love the fact that when­ever I need to do my tax re­turns, I can just take a look at my Beancount ledger and find all the in­voices right there next to the rel­e­vant trans­ac­tion.

Lastly, in terms of post­ings, I started out with 715 in the year 2016, and the year 2023 was the busiest so far in terms of just the to­tal post­ings count.

bean­query> se­lect year(date), count(*) where year(date) < 2025 group by year(date);

year coun

2016 715

2017 1422

2018 1605

2019 2437

2020 1582

2021 2022

2022 2435

2023 2651

2024 2602

I wrote ear­lier that every month I take about 30-45 min­utes to im­port my fi­nan­cial trans­ac­tions into Beancount. What does that work­flow look like? I wrote an­other, much more de­tailed blog post about it a few years ago, but here’s a gist.

It starts with me log­ging in to my bank ac­count(s) to down­load my monthly state­ment(s) in CSV (CSV be­cause it’s much more pre­dictable to parse com­pared to PDF). I then run these CSV files through what’s called an “importer”, that con­verts this CSV data into data struc­tures that Beancount un­der­stands. I then ap­pend all those ex­tracted en­tries into my cur­rent .beancount file (which is the main file con­tain­ing all my fi­nan­cial trans­ac­tions in plain text). I then go through each en­try one by one and make sure it’s bal­anced (in dou­ble-en­try book­keep­ing, all the post­ings in a trans­ac­tion must sum to zero, and not all post­ings/​trans­ac­tions that an im­porter out­puts are bal­anced). Some of that bal­anc­ing is man­ual and some of it is au­to­mated (e.g. the im­porter code can look at the trans­ac­tion’s de­scrip­tion and de­cide which ac­count it should go into, and bal­ance au­to­mat­i­cally). This last part (balancing) is where most of those 30-45 min­utes go.

Whenever a new year starts, I move all the trans­ac­tions from the past year into a

file and add an in­clude in the ac­tive

main.bean­count­file, mostly to avoid the main file from be­com­ing too long. Not that it would be an is­sue for Beancount, but just for the sake of read­abil­ity.

With such a work­flow, all my fi­nan­cial trans­ac­tions from the be­gin­ning of time are con­tained in a few plain text files in one di­rec­tory on my lap­top.

Beancount only pro­vides the foun­da­tions for work­ing with money, but it has no knowl­edge of what your bank state­ments look like. This is where the con­cept of an im­porter comes in. An im­porter is a (Python) class that takes in a bank state­ment of sorts (e.g. a CSV ex­port of your trans­ac­tions) and con­verts them into some­thing that Beancount can work with.

I live in Germany and my bank ac­counts are with German banks, so I had to write a few im­porters for a few dif­fer­ent banks, specif­i­cally bean­count-dkb, bean­count-ing,

bean­count-n26, and bean­count-com­merzbank. I closed out my Commerzbank ac­count a while ago, so I don’t main­tain that in­te­gra­tion any­more, but the first three li­braries are ac­tively main­tained (and used)!

My start with Beancount was a bit bumpy. The doc­u­men­ta­tion is very com­pre­hen­sive but as a new­comer, I found it tricky to get a grasp on the over­all work­flow. It took me some trial and er­ror to fig­ure things out and have that “aha” mo­ment.

I fig­ured that if I found it tricky, maybe it’s tricky for oth­ers as well. So I wrote a short book to help new­com­ers get up and run­ning with Beancount eas­ily. If you’re in­ter­ested, here’s a link: https://​per­son­al­fi­nance­spython.com.

The feed­back on the book has been su­per pos­i­tive. It got men­tioned on Beancount’s

ex­ter­nal con­tri­bu­tions page, and the reader re­views have all been very en­cour­ag­ing!

Having all my fi­nances in a bunch of plain text files tracked in a git repos­i­tory feels in­valu­able to me. And hit­ting the 10 years mark on that al­most feels like a mile­stone.

Perhaps the nicest bit about all this is that this data is sit­ting on my own

ma­chine, not in some data cen­ter some­where else. All of it is in plain text files that I can open up in my ed­i­tor, and an­a­lyze us­ing the tools that the Beancount ecosys­tem gives me. All of it will out­live any app or ser­vice, and that, I feel, is why plain­text ac­count­ing is so pow­er­ful.

The 39th Chaos Communication Congress (39C3) takes place in Hamburg on 27-30 Dec 2025, and is the 2025 edi­tion of the an­nual four-day con­fer­ence on tech­nol­ogy, so­ci­ety and utopia or­ga­nized by the Chaos Computer Club (CCC) and vol­un­teers. Congress of­fers lec­tures and work­shops and var­i­ous events on a mul­ti­tude of top­ics in­clud­ing (but not lim­ited to) in­for­ma­tion tech­nol­ogy and gen­er­ally a crit­i­cal-cre­ative at­ti­tude to­wards tech­nol­ogy and the dis­cus­sion about the ef­fects of tech­no­log­i­cal ad­vances on so­ci­ety.

A few days ago, I found that a grown man had been tex­ting my twelve-year-old son on his “kid-safe” Gabb phone. The man got my son’s num­ber through a chil­dren’s book chat on an app called GroupMe. Thankfully my wife and I dis­cov­ered the sit­u­a­tion and in­ter­vened be­fore any­thing bad hap­pened; but still it was sick­en­ing to dis­cover that on Christmas morn­ing, while our fam­ily was un­wrap­ping pre­sents next to the tree, some creep had been tex­ting my son: “What did you get? Send pic­tures.”

How could we have let this hap­pen? How could we be such care­less par­ents?

But wait . . . had­n’t we done what we were sup­posed to do? We bought the “kid-safe” phone. And we con­firmed GroupMe was on the Gabb “approved apps” list, which, as I un­der­stand it, of­fers “no so­cial me­dia or high-risk op­tions.” We did the safe things, right?

Maybe not. Turns out Gabb’s own blog ap­pears to in­clude GroupMe on a list of seven apps with

dan­ger­ous chat fea­tures, de­scrib­ing it as an app that “opens the door to po­ten­tial dan­gers.” We were ap­par­ently sup­posed to find that warn­ing our­selves, some­where among Gabb’s 572 blog posts:

$ curl -s \

https://​gabb.com/​post-sitemap.xml \

| grep -oE ’https://​gabb\.com/​blog/[^

But if GroupMe “opens the door” to dan­ger, why did Gabb put it on their “approved apps” list? When I re­vis­ited the site, I no­ticed a small mes­sage be­neath GroupMe men­tion­ing Communication with Strangers. I hov­ered over it with my mouse pointer, and a tooltip ap­peared: “Allows con­tact and com­mu­ni­ca­tion with peo­ple the child may not know.”

So it al­lows com­mu­ni­ca­tion with strangers, but it’s not “high-risk?” The ap­proved list is­n’t look­ing so safe. The ap­proved list is ap­par­ently a cat­a­log of risks I’m sup­posed to de­ci­pher by fil­ter­ing through 838 apps and hov­er­ing my mouse pointer around to see tooltips:

$ for cat in \

ex­ist­ing_apps \

un­ap­proved_apps \

un­met_cri­te­ri­a_apps \

mu­sic_apps; do

count=$(curl -s “https://​gabb.com/​app-guide/” \

| grep -o “${cat} = \[.*\]” \

| head -1 \

| sed “s/${cat} = \[//” \

| sed “s/\]//” \

| tr ‘,’ ‘\n’ \

| sed “s/’//g” \

| sed ‘s/^ *//’ \

| sort -u \

| wc -l \

| tr -d ′ ’)

echo “$count $cat”

done && echo ”…as of $(date ‘+%B %d, %Y’)”

586 ex­ist­ing_apps

60 un­ap­proved_apps

170 un­met_cri­te­ri­a_apps

22 mu­sic_apps

…as of January 02, 2026

Whatever the rea­son for this com­plex­ity, I don’t feel in con­trol.

And Gabb is­n’t alone in mak­ing me feel like this. It seems like many com­pa­nies sell­ing tech to fam­i­lies op­er­ate in the same way: mar­ket safety, de­liver com­plex­ity, and leave par­ents to fig­ure it out.

Take the Nintendo Switch my son un­wrapped be­tween those creepy texts. To set it up, I had to:

Connect the con­sole to the in­ter­net

Download the Nintendo Switch Parental Controls app to my phone

Link my credit card and be charged $0.50 to ver­ify parental con­sent

Set up parental con­trols from the app on my phone

Sync the parental con­trols app to the Nintendo Switch

Set up a se­cu­rity PIN on the Nintendo Switch

Sync my son’s Nintendo Account to the Nintendo Switch

Discover that half the con­trols live in the phone app and the other

half live on Nintendo’s web­site, be­cause of course they do

Log into Nintendo’s web­site to fin­ish the job . . .

Only to dis­cover that there’s no clear op­tion to block in­ter­net ac­cess, no clear way to dis­able down­loads from the Nintendo eS­hop, and no easy way to make this thing func­tion like an old-school Game Boy and just let a kid have fun with a game car­tridge. But that’s just nos­tal­gia talk­ing. Nobody wants that any­more. Apparently.

Because next comes Minecraft. Ah, Minecraft. The game every mid­dle-schooler on earth ap­par­ently needs to sur­vive. To let my son play with his friends:

Create an email ad­dress for my son

Set up a gamertag for my son on ac­count.xbox.com

Now, I did my best to con­fig­ure these set­tings. I re­ally did. But xbox.com alone in­cludes twenty-nine con­fus­ingly over­lap­ping set­tings re­lated to chat, friends, and com­mu­ni­ca­tion. Twenty-nine.

And when I fi­nally—fi­nally—tried to test on­line play, Minecraft told me I would need to loosen the parental con­trols (it did not say which) and cre­ate a Nintendo Switch Online ac­count for my son.

Nintendo Switch Online (not re­ally an­other ac­count, mind you, but a mem­ber­ship) in­volves a re­cur­ring fee. It also un­locks ac­cess to the Nintendo eS­hop, which I can­not dis­able. I can set his eS­hop spend­ing limit to zero, sure. But I can’t block free down­loads. So to let my son play on­line Minecraft with his friends, I have to open him up to an un­re­lated store full of con­tent I can’t pos­si­bly eval­u­ate. That’s the deal. Take it or leave it.

I as­sume some mar­ket­ing per­son at Nintendo, prob­a­bly sit­ting in a con­fer­ence room in Kyoto, sur­rounded by white­boards cov­ered in ar­rows and car­toon stick fig­ures, has this en­tire process mapped out as a “customer jour­ney.” And by Step 17, the jour­ney is sup­posed to be over. You’re sup­posed to be so beaten down, so ut­terly de­pleted of will, that you just cave. You sign up for Nintendo Online. You dis­able a bunch of parental con­trols you don’t re­ally un­der­stand. You let your kid play his damn game. You be­come the ideal cus­tomer.

But I did­n’t cave. Instead, some­where on the thresh­old of Customer Journey Step 18, I found my­self grip­ping the Switch with both hands and imag­in­ing, quite vividly, what it would feel like to lift the Switch up, and bring it down over my knee. I could al­most hear the crack. Could al­most see that OLED dis­play splin­ter­ing into a thou­sand pieces. The lit­tle Joy-Cons skit­ter­ing across the floor. My son’s face. My wife’s face. The stunned si­lence.

I did not break the Switch.

What I did was an­nounce, in a voice louder than nec­es­sary, that no­body was to ask me about any­thing Minecraft-related on the Nintendo Switch for a min­i­mum of two weeks. My son could play Zelda: Breath of the Wild in­stead, which, thank you, de­vel­op­ers, thank you from the bot­tom of my heart, does­n’t ap­pear to in­volve any manda­tory on­line any­thing what­so­ever.

Here’s what I want: an off switch. A sin­gle set­ting that says “this child can­not go on­line, com­mu­ni­cate with strangers, spend money, or down­load any­thing with­out my ex­plicit per­mis­sion.” Instead I get a maze, com­plex enough that when some­thing goes wrong, I’m at fault for a tooltip I did­n’t hover over, a blog post I did­n’t read, a sub­menu I did­n’t find. Maybe that’s by de­sign. Maybe it’s ne­glect. I don’t know.

What I know is this. My son just wants to play video games and talk to his friends. I just want to keep him safe. Somewhere be­tween those two things, I’m sup­posed to be­come an ex­pert in the con­vo­luted parental con­trol schemes of Gabb, Nintendo, Microsoft, and Xbox, while a stranger’s Christmas morn­ing texts sit in my son’s phone his­tory.

Around the world, peo­ple cel­e­brate Public Domain Day on January 1, the day in which copy­right ex­pires on some older works and they en­ter the pub­lic do­main in many dif­fer­ent coun­tries.

In the U. S. Constitution, copy­right terms were meant to be very lim­ited in or­der to “promote the Progress of Science and use­ful Arts.” The first copy­right act, writ­ten in 1790 by the found­ing fa­thers them­selves, set the term to be up to twenty-eight years.

But since then, pow­er­ful cor­po­ra­tions have re­peat­edly ex­tended the length of copy­right to pro­mote not the progress of so­ci­ety, but their profit. The re­sult is that to­day in the U. S., work only en­ters the pub­lic do­main ninety-five years af­ter pub­li­ca­tion—lock­ing our cul­ture away for nearly a cen­tury.

2019 was the year in which new works were fi­nally sched­uled to en­ter the pub­lic do­main, end­ing this long, cor­po­rate-dic­tated cul­tural win­ter. And as that year drew closer, it be­came clear that these cor­po­ra­tions would­n’t try to ex­tend copy­right yet again—mak­ing it the first year in al­most a hun­dred years in which a sig­nif­i­cant amount of art and lit­er­a­ture once again en­tered the U. S. pub­lic do­main, free for any­one in the U.S. to read, use, share, remix, build upon, and en­joy.

Ever since then, January 1 has been cel­e­brated as Public Domain Day, the day in which the next year’s crop of books, movies, mu­sic, and art­work grad­u­ates into the pub­lic do­main. At Standard Ebooks, we’ve pre­pared some of the year’s biggest lit­er­ary hits for you to read this January 1.

On January 1, 2026, books pub­lished in 1930 en­ter the U. S. pub­lic do­main.

This in­cludes leg­endary books by William Faulkner, Franz Kafka, Agatha Christie, and Langston Hughes. In ad­di­tion, The Maltese Falcon, per­haps the best-known noir book—and film—of all time, and books by Evelyn Waugh, Dorothy L. Sayers, and more, en­ter the U. S. pub­lic do­main, be­com­ing free for any­one in the U.S. to read, use, and re-use.

Our friends at the Public Domain Review have writ­ten about some other things that en­ter the pub­lic do­main this year, too.

These past few months at Standard Ebooks, our vol­un­teers have been work­ing hard to pre­pare a se­lec­tion of the books pub­lished in 1930 in ad­vance of Public Domain Day. We’re ex­cited to fi­nally be able to share these 20 new free ebooks with you!

Around the world, peo­ple cel­e­brate Public Domain Day on January 1, the day in which copy­right ex­pires on some older works and they en­ter the pub­lic do­main in many dif­fer­ent coun­tries.

In the U. S. Constitution, copy­right terms were meant to be very lim­ited in or­der to “promote the Progress of Science and use­ful Arts.” The first copy­right act, writ­ten in 1790 by the found­ing fa­thers them­selves, set the term to be up to twenty-eight years.

But since then, pow­er­ful cor­po­ra­tions have re­peat­edly ex­tended the length of copy­right to pro­mote not the progress of so­ci­ety, but their profit. The re­sult is that to­day in the U. S., work only en­ters the pub­lic do­main ninety-five years af­ter pub­li­ca­tion—lock­ing our cul­ture away for nearly a cen­tury.

2019 was the year in which new works were fi­nally sched­uled to en­ter the pub­lic do­main, end­ing this long, cor­po­rate-dic­tated cul­tural win­ter. And as that year drew closer, it be­came clear that these cor­po­ra­tions would­n’t try to ex­tend copy­right yet again—mak­ing it the first year in al­most a hun­dred years in which a sig­nif­i­cant amount of art and lit­er­a­ture once again en­tered the U. S. pub­lic do­main, free for any­one in the U.S. to read, use, share, remix, build upon, and en­joy.

Ever since then, January 1 has been cel­e­brated as Public Domain Day, the day in which the next year’s crop of books, movies, mu­sic, and art­work grad­u­ates into the pub­lic do­main. At Standard Ebooks, we’ve pre­pared some of the year’s biggest lit­er­ary hits for you to read this January 1.

On January 1, 2026, books pub­lished in 1930 en­ter the U. S. pub­lic do­main.

This in­cludes leg­endary books by William Faulkner, Franz Kafka, Agatha Christie, and Langston Hughes. In ad­di­tion, The Maltese Falcon, per­haps the best-known noir book—and film—of all time, and books by Evelyn Waugh, Dorothy L. Sayers, and more, en­ter the U. S. pub­lic do­main, be­com­ing free for any­one in the U.S. to read, use, and re-use.

Our friends at the Public Domain Review have writ­ten about some other things that en­ter the pub­lic do­main this year, too.

These past few months at Standard Ebooks, our vol­un­teers have been work­ing hard to pre­pare a se­lec­tion of the books pub­lished in 1930 in ad­vance of Public Domain Day. We’re ex­cited to fi­nally be able to share these 20 new free ebooks with you!

A land sur­veyor known only as K. is sum­moned to a re­mote vil­lage to per­form some work for au­thor­i­ties in a nearby cas­tle. When the lo­cals in­form him that there has been a mis­take, K. con­tin­ues to try to make con­tact with the of­fi­cials in the cas­tle to com­plete his work, in the face of an in­creas­ingly-sur­real bu­reau­cratic night­mare. The Castle was in­com­plete at the time of Kafka’s death, and was pub­lished posthu­mously by his lit­er­ary ex­ecu­tor Max Brod. This 1930 trans­la­tion was the book that kick­started the English-speaking world’s in­ter­est Kafka’s uniquely op­pres­sive and mod­ernist style.

When an unloved lo­cal is mur­dered in the small rural town of St. Mary Mead, the lo­cal vicar takes up the case. But he soon finds him­self re­ly­ing on the help of his gos­sipy neigh­bor—an old spin­ster named Miss Marple. While this novel tech­ni­cally is­n’t Miss Marple’s first ap­pear­ance—she was fea­tured in a short story some years ear­lier—it is the first full-length story fea­tur­ing the homely sleuth who would go on to be­come one of Christie’s most beloved char­ac­ters.

Evelyn Waugh re­turns in this, his sec­ond novel, to de­liver an­other scathing, comic satire of high so­ci­ety. This time his tar­gets are the “bright young things” of post-World-War-I England. Waugh deftly skew­ers their raunchy, rau­cus, Jazz-age lifestyle, as well as the mid­dle class pub­lic, who can’t seem to get enough of their gos­sip. As a tes­ta­ment to the nov­el’s stay­ing power, David Bowie used Vile Bodies as the pri­mary in­spi­ra­tion for his song “Aladdin Sane.”

№ 13 in the Pulitzer Prize for Fiction Winners

se­ries.

Years of Grace fol­lows the life of Jane Ward, a rather un­so­phis­ti­cated young girl who comes of age in 1890s Chicago. Her fam­ily is up­per mid­dle class, and Jane finds her tra­di­tional, home­body na­ture be­ing pulled by the var­i­ous forces of am­bi­tion, cul­ture, and progress that swirl around her dur­ing the ef­fer­ves­cent decades at the turn of the cen­tury. We see her into late mid­dle age, where the world has been ripped apart by war, and with change ac­cel­er­at­ing faster and faster as an­other war looms on the hori­zon.

Miss Mole is a mid­dle-age house­keeper who has re­cently left the em­ploy of a wealthy ma­tron to work for the young fam­ily of a min­is­ter. The mother has re­cently passed, leav­ing the fam­ily strug­gling to man­age the house­hold—but luck­ily for them, Miss Mole is ex­actly the kind of ca­pa­ble, witty, and as­sertive leader they need. As they work on or­der­ing the house­hold, a shad­owy fig­ure from Miss Mole’s past weaves in and out of the nar­ra­tive. But what­ever hap­pened in Miss Mole’s his­tory can’t seem to put a damper on her bright, clever, and funny out­look.

The Faraway Bride con­cerns the Malinin fam­ily, shopown­ers in 1920s Manchuria who are struck by mis­for­tune when their store is raided by Red Army thugs. Their fa­ther re­calls that a friend owes him a debt of money that could save the fam­i­ly’s fi­nances—but the friend lives in Seoul, which lies at a gru­el­ing three week’s walk across the Korean moun­tains. The dif­fi­culty of the jour­ney does­n’t faze the two Malinin chil­dren, who ex­cit­edly em­bark on a quest to save the fam­ily. The novel is based on the story of Tobit from the Apocrypha, but its set­ting, and the re­sult­ing mish-mash of lan­guages and cul­tures, make for a de­cid­edly unique read.

How will hu­mankind, and the world, end? Geoffrey Dennis aims to an­swer that ques­tion in this sin­gu­lar work of semi-fic­tion. He ex­plores how prophe­cies and pre­dic­tions can twist the fate of hu­mankind, and how the progress of sci­ence and tech­nol­ogy can si­mul­ta­ne­ously lift hu­mans up, while mak­ing them sus­cep­ti­ble to con­trol by so­ci­etal and po­lit­i­cal in­ter­ests. Dennis’s con­clu­sions blend re­li­gion, sci­ence, and his­tory to cre­ate a unique book that strad­dles the line be­tween fact and fic­tion.

№ 1 in the Swallows and Amazons

se­ries.

Arthur Ransome, a jour­nal­ist in Manchester, was in­spired to write this chil­dren’s story of gen­tle ad­ven­ture while spend­ing a sum­mer teach­ing a friend’s chil­dren to sail in the Lake District. In it, the chil­dren of two fam­i­lies on rural va­ca­tions meet in the wilder­ness; one side sails the dinghy named the Swallow, and the other the dinghy Amazon. They soon join forces against the das­tardly “Captain Flint,” who in re­al­ity is just a cranky old man try­ing to qui­etly write his mem­oirs in his house­boat. Their ad­ven­tures are a charm­ing tale that, by stay­ing firmly grounded in re­al­ity, com­pletely es­chews the tropes typ­i­cal of to­day’s chil­dren’s books.

Daphne du Maurier had a long and il­lus­tri­ous ca­reer writ­ing short fic­tion. This year, four of her short sto­ries en­ter the U. S. pub­lic do­main: “The Lover,” “The Supreme Artist,” “Frustration,” and “Indiscretion.” In her time, Du Maurier was of­ten cat­e­go­rized as a ro­man­tic nov­el­ist, a la­bel that frus­trated her to no end, be­cause her sto­ries have more in com­mon with the works of writ­ers like Wilkie Collins in that they ex­plore dark and sin­is­ter themes, of­ten tinged with a para­nor­mal fla­vor. Many of her works have since been adapted to film.

Cimarron was the best-sell­ing novel of 1930. Set in the lands of Oklahoma dur­ing the land rushes of 1889 and 1893, it fol­lows a young fam­ily try­ing to make a life for them­selves in a land be­set by scrab­bling set­tlers and out­raged na­tives. The fam­i­ly’s tra­jec­tory rises as the charis­matic pa­tri­arch founds a news­pa­per and set­tles lo­cal dis­putes, while the ma­tri­arch trans­forms from a faint-hearted Southern belle into a hard-eyed fron­tier­swoman and politi­cian. Though later seen as a paean to fem­i­nism, Ferber orig­i­nally in­tended the story to be a satire of American wom­an­hood. Its pop­u­lar­ity led it to be­ing pub­lished as an Armed Services Edition and sent to sol­diers on the front—the same for­tu­itous fate that graced The Great Gatsby—cementing its fame in the minds of a gen­er­a­tion.

Giant’s Bread is the first novel Agatha Christie wrote un­der a pen name, be­cause it dif­fered so much from her usual mys­tery fare that she wanted it to stand up to pub­lic scrutiny un­der its own mer­its and not on her rep­u­ta­tion. And stand up it did, as re­view­ers re­ceived it with glow­ing praise. The book fol­lows Vernon Deyre, a young Englishman and bril­liant mu­si­cian, from in­fancy to adult­hood be­fore and dur­ing the Great War. It ex­plores themes of love, sac­ri­fice, art, and ul­ti­mately, re­demp­tion.

Nancy Drew, young de­tec­tive, is on the case again when her friend’s in­her­i­tance of di­a­monds, worth forty thou­sand dol­lars, is stolen dur­ing a lunch. Her friend’s guardian is the prime sus­pect. Can Nancy un­cover the true crim­i­nal be­fore an in­no­cent per­son is locked away?Like many other Nancy Drew nov­els, this one was rewrit­ten in 1961 by a dif­fer­ent au­thor. This Standard Ebooks edi­tion fol­lows the 1930 text, writ­ten by Mildred Wirt Benson un­der the Carolyn Keene pen name.

TL;DR: 2026 is go­ing to be The Year of The Linux Desktop for me. I haven’t booted into Windows in over 3 months on my tower and I’m start­ing to re­al­ize that it’s not worth wast­ing the space for. I plan to unify my three SSDs and turn them all into btrfs dri­ves on Fedora.

I’ve been merely tol­er­at­ing Windows 11 for a while but re­cently it’s got­ten to the point where it’s just ab­solutely in­tol­er­a­ble. Somehow Linux on the desk­top has got­ten so much bet­ter by not even do­ing any­thing dif­fer­ently. Microsoft has man­aged to ac­tively sab­o­tage the desk­top ex­pe­ri­ence through years of ac­tive dis­re­gard and spite against their users. They’ve man­aged to take some of their most rev­o­lu­tion­ary tech­no­log­i­cal in­no­va­tions (the NT ker­nel’s hy­brid de­sign al­low­ing it to restart dri­vers, NTFS, ReFS, WSL, Hyper-V, etc.) then just shat all over them with start menus made with React Native, con­trol-alt-delete menus that are ac­tu­ally just we­b­views, and forc­ing Copilot down every­one’s throats to the point that I’ve ac­ci­den­tally got­ten stuck in Copilot in a hand­held gam­ing PC and had to hard re­boot the de­vice to get out of it. It’s as if the in­ter­nal teams at Microsoft have had decades of lead time in shoot­ing each other in the head with pre­dictable re­sults.

To be hon­est, I’ve had enough. I’m go­ing to go with Fedora on my tower and Bazzite (or SteamOS) on my hand­helds.

I think that Linux on the desk­top is ready for the masses now, not be­cause it’s ad­vanced in a huge leap/​bound. It’s ready for the masses to use be­cause Windows has got­ten so much ac­tively worse that con­tin­u­ing to use it is an ac­tive detri­ment to user ex­pe­ri­ence and sta­bil­ity. Not to men­tion with the price of ram lately, you need every gi­ga­byte you can get and desk­top Linux lets you waste less of it on su­per­flu­ous bull­shit that very few peo­ple ac­tu­ally want.

At the very least, when some­thing goes wrong on Linux you have log mes­sages that can let you know what went wrong so you can search for it.

Facts and cir­cum­stances may have changed since pub­li­ca­tion. Please con­tact me be­fore jump­ing to con­clu­sions if some­thing seems wrong or un­clear.

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Google “harder bet­ter faster stronger bpm” and Google’s “AI Overview” will tell you:

Daft Punk’s “Harder, Better, Faster, Stronger” gen­er­ally sits around 123 BPM (Beats Per Minute), though some analy­ses find it slightly higher (like 123.48 BPM) or list dif­fer­ent BPMs in remixes/​work­outs, with ex­act fig­ures vary­ing slightly by source and ver­sion.

Spotify’s meta­data data­base, SongBPM, and most other on­line BPM data­bases list it at ex­actly 123.

But I think our hel­met-clad ro­bot friends might have been mak­ing a lit­tle joke that we’ve ap­par­ently all missed. The BPM of Harder, Better, Faster, Stronger is ac­tu­ally 123.45.

How do I know this? It so hap­pens that for over 10 years I’ve writ­ten an app called Tempi that shows the mu­sic BPM in real time, so I know a lit­tle bit about the sci­ence and al­go­rithms be­hind mu­sic tempo de­tec­tion.

Most tempo de­tec­tion soft­ware works ba­si­cally the same way:

* A spe­cial­ized al­go­rithm called the Fast Fourier Transform (FFT) col­lects over­lap­ping en­ergy lev­els at dif­fer­ent fre­quency bands.

* Those lev­els are re­fined into well-de­fined peaks that rep­re­sent rhyth­mic events in the track.

* Another al­go­rithm (autocorrelation) looks for pat­terns, or more ac­cu­rately pe­ri­od­ic­ity, in those peaks.

But these pat­terns are tricky be­cause there’s all kinds of noise, per­for­mance in­ac­cu­ra­cies, and rhyth­mic har­mon­ics throw­ing things off. All that is to say, a) it’s com­pli­cated and b) it’s not per­fectly ac­cu­rate.

When I make changes to my own sys­tem of course I need some way to know if it’s get­ting bet­ter or worse, so I have a test li­brary of hun­dreds of song snip­pets that I score it against. One of these songs is Daft Punk’s HBFS, and early on I no­ticed some­thing strange about that track.

Almost all elec­tronic mu­sic is synced to a se­quencer and so ob­vi­ously is go­ing to have a very steady tempo. But while the vast ma­jor­ity of elec­tronic mu­sic tracks I test have an “integral” tempo — mean­ing their tempo is ex­actly some round num­ber like 95, and not a frac­tion like 95.2 — my soft­ware al­ways finds the BPM of HBFS to be some­where be­tween 123 and 124, but not ex­actly ei­ther. For years I’ve chalked this up to in­con­sis­ten­cies with my sys­tem and did­n’t think much of it. But lately I’ve made im­prove­ments to the sys­tem so that it’s much more ac­cu­rate and it now tells me the BPM of HBFS is 123.4.

And that got me think­ing, “Hmm. Did these guys pick that tempo be­cause they have a sense of hu­mor? And if so, how far would they take it?”

To get to the bot­tom of this I needed to es­tab­lish what the BPM of HBFS re­ally is.

Here’s a Venn di­a­gram show­ing the over­lap be­tween hu­man and com­puter ca­pa­bil­i­ties in the dig­i­tal realm:

Computers can do al­most all “computer-y” things (i.e. things that can be en­tirely done on a com­puter) MUCH bet­ter, faster, (and stronger?) than hu­mans. But for the time be­ing there re­main a few things that hu­mans can do very eas­ily which com­put­ers find dif­fi­cult. Along with count­ing traf­fic lights and cross­walks, one of those things is find­ing the ex­act BPM of a song. Not an es­ti­mate like most soft­ware does, but the ex­act value with ex­treme pre­ci­sion across the en­tire song. Anyone with a ba­sic sense of rhythm and an au­dio app can do this.

* Open the song in an au­dio app like Logic, Audition, Ableton, Reaper, ProTools, etc.

* Zoom in on the wave­form a lit­tle bit so you can see the shape of the beats.

* Find the first ob­vi­ous beat — mean­ing it has a well-de­fined wave­form peak — and the last ob­vi­ous beat. Let’s call these “bookend” beats.

* Measure the ex­act du­ra­tion in sec­onds be­tween the book­end beats.

* Play the song and count all the beats start­ing at the first book­end beat and end­ing at the last book­end beat. (If you have an old school cal­cu­la­tor, an easy way to do this is type “1+1=” and then just keep tap­ping “=” to add 1 on each beat.)

Then to get the ex­act tempo of the track, av­er­aged through­out the en­tire thing, use this for­mula:

bpm = 60 * (number_of_beats - 1) / du­ra­tion

Computers have a rough time of this be­cause they don’t re­ally know how to “keep a beat”, and the al­go­rithms that can find the beat do a lot bet­ter when they al­ready know the es­ti­mated BPM, which is ob­vi­ously a chicken/​egg prob­lem.

For the first book­end beat in HBFS I used the first beat af­ter the “whooshing” in­tro, at around 5.58s. The last book­end beat I used the last “work” at about the 3:41.85 mark. (“Never” and “Over” aren’t good can­di­dates be­cause you can’t see their wave­form peaks.)

That gives ex­actly 446 beats or 445 in­ter­vals.

I tried this with two dif­fer­ent copies of HBFS. The Discovery CD rip I have of the song has a du­ra­tion be­tween the book­end beats of 216.276, so:

bpm = 60 * 445 / 216.276 = 123.4499403556

The “YouTube of­fi­cial au­dio” track I tested has a du­ra­tion of 216.282, so:

bpm = 60 * 445 / 216.282 = 123.4533651445

The orig­i­nal Discovery CD ver­sion has ob­vi­ously un­der­gone less pro­cess­ing over time than the YouTube ver­sion so I tend to think it’s more rep­re­sen­ta­tive, and it’s very close to 123.45 — only a 0.00005964 dif­fer­ence! But even the more mod­ern YouTube ver­sion closely rounds to 123.45.

So hope­fully I’ve put this fact to rest:

The BPM of Harder, Better, Faster, Stronger is 123.45.

The year is 1999 or 2000. Would the gear Daft Punk uses even sup­port frac­tional BPMs? And if so out to how many dec­i­mal places?

From their 2001 in­ter­view with Remix Magazine (archive.org) we know that Bangalter says:

Our se­quenc­ing is done ei­ther on an E-mu SP-1200, an Akai MPC, or a PC with Logic Audio soft­ware. We do not work on things in just one way.

And from later in­ter­views we know the Akai MPC was specif­i­cally an MPC-3000. (Oh, and that’s Emagic’s Logic, not Apple’s. Apple did­n’t ac­quire Emagic un­til 2002.)

Did the E-mu sup­port frac­tional BPMs? Yes, but only to 1 dec­i­mal place:

The Akai MPC-3000? Yep, also to 1 dec­i­mal place:

Oooh, look at that. Logic sup­ported BPMs to *4* dec­i­mal places.

But while we know those three se­quencers were used on the Discovery al­bum, I’m not sure any­one else knows which one was specif­i­cally used on HBFS. I’ve searched and searched and it seems this de­tail has just never been re­vealed.

And to con­fuse mat­ters more, in a 2013 in­ter­view with Time Magazine, Bangalter says:

So we’ve never ac­tu­ally made mu­sic with com­put­ers! [laughs] Neither Homework nor Discovery nor even Human After All were made with com­put­ers.

Was he con­tra­dict­ing him­self from 12 years be­fore? Or did he for­get? Or maybe it’s a ter­mi­nol­ogy thing?

That the CD ver­sion is so close to ex­actly 123.45 makes me think this was in­ten­tional. And if it was? Well played, ro­bots. You man­aged to leave a lit­tle Easter egg hid­ing in plain sight for 25 years.