EFF last sum­mer asked a fed­eral judge to block the fed­eral gov­ern­ment from us­ing Med­ic­aid data to iden­tify and de­port im­mi­grants.

We also warned about the dan­ger of the Trump ad­min­is­tra­tion con­sol­i­dat­ing all of the gov­ern­men­t’s in­for­ma­tion into a sin­gle search­able, AI-driven in­ter­face with help from Palantir, a com­pany that has a shaky-at-best record on pri­vacy and hu­man rights.

Now we have the first ev­i­dence that our con­cerns have be­come re­al­ity.

“Palantir is work­ing on a tool for Immigration and Customs Enforcement (ICE) that pop­u­lates a map with po­ten­tial de­por­ta­tion tar­gets, brings up a dossier on each per­son, and pro­vides a “confidence score” on the per­son’s cur­rent ad­dress,” 404 Media re­ports to­day. “ICE is us­ing it to find lo­ca­tions where lots of peo­ple it might de­tain could be based.”

The tool — dubbed Enhanced Leads Identification & Targeting for Enforcement (ELITE) — re­ceives peo­ples’ ad­dresses from the Department of Health and Human Services (which in­cludes Medicaid) and other sources, 404 Media re­ports based on court tes­ti­mony in Oregon by law en­force­ment agents, among other sources.

This rev­e­la­tion comes as ICE — which has gone on a sur­veil­lance tech­nol­ogy shop­ping spree — floods Minneapolis with agents, vi­o­lently run­ning roughshod over the civil rights of im­mi­grants and U. S. cit­i­zens alike; President Trump has threat­ened to use the Insurrection Act of 1807 to de­ploy mil­i­tary troops against pro­tes­tors there. Other lo­cal­i­ties are prepar­ing for the pos­si­bil­ity of sim­i­lar surges.

Different gov­ern­ment agen­cies nec­es­sar­ily col­lect in­for­ma­tion to pro­vide es­sen­tial ser­vices or col­lect taxes, but the dan­ger comes when the gov­ern­ment be­gins pool­ing that data and us­ing it for rea­sons un­re­lated to the pur­pose it was col­lected.

This kind of con­sol­i­da­tion of gov­ern­ment records pro­vides enor­mous gov­ern­ment power that can be abused. Different gov­ern­ment agen­cies nec­es­sar­ily col­lect in­for­ma­tion to pro­vide es­sen­tial ser­vices or col­lect taxes, but the dan­ger comes when the gov­ern­ment be­gins pool­ing that data and us­ing it for rea­sons un­re­lated to the pur­pose it was col­lected.

As EFF Executive Director Cindy Cohn wrote in a Mercury News op-ed last August, “While couched in the be­nign lan­guage of elim­i­nat­ing gov­ern­ment ‘data si­los,’ this plan runs roughshod over your pri­vacy and se­cu­rity. It’s a throw­back to the rightly mocked ‘Total Information Awareness’ plans of the early 2000s that were, at least pub­licly, stopped af­ter mas­sive out­cry from the pub­lic and from key mem­bers of Congress. It’s time to cry out again.”

In ad­di­tion to the am­i­cus brief we co-au­thored chal­leng­ing ICE’s grab for Medicaid data, EFF has suc­cess­fully sued over DOGE agents grab­bing per­sonal data from the U. S. Office of Personnel Management, filed an am­i­cus brief in a suit chal­leng­ing ICE’s grab for tax­payer data, and sued the de­part­ments of State and Homeland Security to halt a mass sur­veil­lance pro­gram to mon­i­tor con­sti­tu­tion­ally pro­tected speech by nonci­t­i­zens law­fully pre­sent in the U.S.

But lit­i­ga­tion is­n’t enough. People need to keep rais­ing con­cerns via pub­lic dis­course and Congress should act im­me­di­ately to put brakes on this run­away train that threat­ens to crush the pri­vacy and se­cu­rity of each and every per­son in America.

Play Video: Deutsche Telekom is throt­tling the in­ter­net. Let’s do some­thing about it!

Play Video: Deutsche Telekom is throt­tling the in­ter­net. Let’s do some­thing about it!

Epicenter.works, the Society for Civil Rights, the Federation of German Consumer Organizations, and Stanford Professor Barbara van Schewick are fil­ing an of­fi­cial com­plaint with the Federal Network Agency against Deutsche Telekom’s un­fair busi­ness prac­tices.

Deutsche Telekom is cre­at­ing ar­ti­fi­cial bot­tle­necks at ac­cess points to its net­work. Financially strong ser­vices that pay Telekom get through quickly and work per­fectly. Services that can­not af­ford this are slowed down and of­ten load slowly or not at all.

This means Telekom de­cides which ser­vices we can use with­out is­sues, vi­o­lat­ing net neu­tral­ity. We are fil­ing a com­plaint with the Federal Network Agency to stop this un­fair prac­tice to­gether!

A ma­cOS app that blurs your screen when you slouch.

Posturr uses your Mac’s cam­era and Apple’s Vision frame­work to mon­i­tor your pos­ture in real-time. When it de­tects that you’re slouch­ing, it pro­gres­sively blurs your screen to re­mind you to sit up straight. Maintain good pos­ture, and the blur clears in­stantly.

* Real-time pos­ture de­tec­tion - Uses Apple’s Vision frame­work for body pose and face track­ing

* Menu bar con­trols - Easy ac­cess to set­tings, cal­i­bra­tion, and sta­tus from the menu bar

* Privacy-focused - All pro­cess­ing hap­pens lo­cally on your Mac

* No ac­count re­quired - No signup, no cloud, no track­ing

brew tap tldev/​tap

brew in­stall –cask pos­turr

Download the lat­est Posturr-vX. X.X.dmg or .zip from the Releases page

Open the DMG and drag Posturr.app to your Applications folder

Launch nor­mally - no Gatekeeper warn­ings (app is signed and no­ta­rized)

Posturr re­quires cam­era ac­cess to mon­i­tor your pos­ture. When you first launch the app, ma­cOS will ask for per­mis­sion. Click “OK” to grant ac­cess.

If you ac­ci­den­tally de­nied per­mis­sion, you can grant it later:

Once launched, Posturr ap­pears in your menu bar with a per­son icon. The app con­tin­u­ously mon­i­tors your pos­ture and ap­plies screen blur when slouch­ing is de­tected.

* Recalibrate - Reset your base­line pos­ture (sit up straight, then click)

* Sensitivity - Adjust how sen­si­tive the slouch de­tec­tion is (Low, Medium, High, Very High)

* Dead Zone - Set the tol­er­ance be­fore blur kicks in (None, Small, Medium, Large)

* Compatibility Mode - Use pub­lic ma­cOS APIs for blur (try this if blur does­n’t ap­pear)

* Quit - Exit the ap­pli­ca­tion (or press Escape any­where)

* Position your cam­era at eye level when pos­si­ble

* Sit at a con­sis­tent dis­tance from your screen

* The app works best when your shoul­ders are vis­i­ble

Posture Analysis: Measures the ver­ti­cal dis­tance be­tween nose and shoul­ders

The screen blur uses ma­cOS’s pri­vate CoreGraphics API by de­fault for ef­fi­cient, sys­tem-level blur. If the blur does­n’t ap­pear on your sys­tem, en­able Compatibility Mode from the menu to use NSVisualEffectView in­stead.

git clone https://​github.com/​you­ruser­name/​pos­turr.git

cd pos­turr

./build.sh

The built app will be in build/​Pos­turr.app.

# Standard build

./build.sh

# Build with re­lease archive (.zip)

./build.sh –release

swiftc -O \

-framework AppKit \

-framework AVFoundation \

-framework Vision \

-framework CoreImage \

-o Posturr \

main.swift

* Detection ac­cu­racy: Works best with clear view of up­per body/​face

Write com­mands to /tmp/posturr-command. Responses ap­pear in /tmp/posturr-response.

Posturr processes all video data lo­cally on your Mac. No im­ages or data are ever sent to ex­ter­nal servers. The cam­era feed is used solely for pos­ture de­tec­tion and is never stored or trans­mit­ted.

Contributions are wel­come! Please feel free to sub­mit is­sues and pull re­quests.

* Uses pri­vate CoreGraphics API for blur, with NSVisualEffectView fall­back

* Inspired by the need for bet­ter pos­ture dur­ing long cod­ing ses­sions

Until re­cently, I re­sisted us­ing the F-word to de­scribe President Trump. For one thing, there were too many el­e­ments of clas­si­cal fas­cism that did­n’t seem to fit. For an­other, the term has been overused to the point of mean­ing­less­ness, es­pe­cially by left-lean­ing types who call you a fas­cist if you op­pose abor­tion or af­fir­ma­tive ac­tion. For yet an­other, the term is hazily de­fined, even by its ad­her­ents. From the be­gin­ning, fas­cism has been an in­co­her­ent doc­trine, and even to­day schol­ars can’t agree on its de­f­i­n­i­tion. Italy’s orig­i­nal ver­sion dif­fered from Germany’s, which dif­fered from Spain’s, which dif­fered from Japan’s.

I ac­cepted President Biden’s char­ac­ter­i­za­tion of the MAGA move­ment as “semi-fascist” be­cause some par­al­lels were glar­ingly ap­par­ent. Trump was def­i­nitely an au­thor­i­tar­ian, and un­ques­tion­ably a pat­ri­mo­ni­al­ist. Beyond that, though, the best de­scrip­tion seemed to be a psy­cho­log­i­cal one pro­pounded by John Bolton, Trump’s first-term na­tional se­cu­rity ad­viser: “He lis­tens to Putin, he lis­tens to Xi, he lis­tens to how they talk about gov­ern­ing un­bur­dened by un­co­op­er­a­tive leg­is­la­tures, un­con­cerned with what the ju­di­ciary may do, and he thinks to him­self, Why can’t I do that? This does­n’t amount to be­ing a fas­cist, in my view, [or] hav­ing a the­ory of how you want to gov­ern. It’s just Why can’t I have the same fun they have?”

Writing a year ago, I ar­gued that Trump’s gov­ern­ing regime is a ver­sion of pat­ri­mo­ni­al­ism, in which the state is treated as the per­sonal prop­erty and fam­ily busi­ness of the leader. That is still true. But, as I also noted then, pat­ri­mo­ni­al­ism is a style of gov­ern­ing, not a for­mal ide­ol­ogy or sys­tem. It can be lay­ered atop all kinds of or­ga­ni­za­tional struc­tures, in­clud­ing not just na­tional gov­ern­ments but also ur­ban po­lit­i­cal ma­chines such as Tammany Hall, crim­i­nal gangs such as the Mafia, and even re­li­gious cults. Because its only firm prin­ci­ple is per­sonal loy­alty to the boss, it has no spe­cific agenda. Fascism, in con­trast, is ide­o­log­i­cal, ag­gres­sive, and, at least in its early stages, rev­o­lu­tion­ary. It seeks to dom­i­nate pol­i­tics, to crush re­sis­tance, and to rewrite the so­cial con­tract.

Over Trump’s past year, what orig­i­nally looked like an ef­fort to make the gov­ern­ment his per­sonal play­thing has drifted dis­tinctly to­ward doc­tri­nal and op­er­a­tional fas­cism. Trump’s ap­petite for leben­sraum, his claim of un­lim­ited power, his sup­port for the global far right, his politi­ciza­tion of the jus­tice sys­tem, his de­ploy­ment of per­for­ma­tive bru­tal­ity, his os­ten­ta­tious vi­o­la­tion of rights, his cre­ation of a na­tional para­mil­i­tary po­lice—all of those de­vel­op­ments be­speak some­thing more pur­pose­ful and sin­is­ter than run-of-the-mill greed or gang­ster­ism.

When the facts change, I change my mind. Recent events have brought Trump’s gov­ern­ing style into sharper fo­cus. Fascist best de­scribes it, and re­luc­tance to use the term has now be­come per­verse. That is not be­cause of any one or two things he and his ad­min­is­tra­tion have done but be­cause of the to­tal­ity. Fascism is not a ter­ri­tory with clearly marked bound­aries but a con­stel­la­tion of char­ac­ter­is­tics. When you view the stars to­gether, the con­stel­la­tion plainly ap­pears.

Demolition of norms. From the be­gin­ning of his first pres­i­den­tial run in 2015, Trump de­lib­er­ately crashed through every bound­ary of ci­vil­ity; he mocked Senator John McCain’s war hero­ism, mocked fel­low can­di­date Carly Fiorina’s face, seem­ingly mocked the Fox News host Megyn Kelly’s men­stru­a­tion, slurred im­mi­grants, and much more. Today he still does it, re­cently mak­ing an ob­scene ges­ture to a fac­tory worker and call­ing a jour­nal­ist “piggy.” This is a fea­ture of the fas­cist gov­ern­ing style, not a bug. Fascists know that what the American Founders called the “republican virtues” im­pede their po­lit­i­cal agenda, and so they glee­fully trash lib­eral pieties such as rea­son and rea­son­able­ness, ci­vil­ity and civic spirit, tol­er­a­tion and for­bear­ance. By mock­ing de­cency and say­ing the un­sayable, they open the way for what William Galston has called the “dark pas­sions” of fear, re­sent­ment, and es­pe­cially dom­i­na­tion—the kind of pol­i­tics that shifts the pub­lic dis­course to ground on which lib­er­als can­not com­pete.

Glorification of vi­o­lence. Every state uses vi­o­lence to en­force its laws, but lib­eral states use it re­luc­tantly, whereas fas­cism em­braces and flaunts it. Trump thus praises a vi­o­lent mob; en­dorses tor­ture; muses fondly about punch­ing, body-slam­ming, and shoot­ing pro­test­ers and jour­nal­ists; and re­port­edly sug­gests shoot­ing pro­test­ers and mi­grants. His re­cruit­ment ads for ICE glam­or­ize mil­i­tary-style raids of homes and neigh­bor­hoods; his pro­pa­ganda takes child­ish de­light in the killing of civil­ians; and we have all seen videos of agents drag­ging peo­ple out of cars and homes—partly be­cause the gov­ern­ment films them. Like the de­mo­li­tion of civic de­cency, the val­oriza­tion of vi­o­lence is not in­ci­den­tal to fas­cism; it is part and par­cel.

Might is right. Also char­ac­ter­is­tic of fas­cism is what George Orwell called “bully-worship”: the prin­ci­ple that, as Thucydides fa­mously put it, “the strong do what they can and the weak suf­fer what they must.” This view came across in Trump’s no­to­ri­ous Oval Office meet­ing with Ukrainian President Volodymyr Zelensky, in which Trump showed open con­tempt for what he re­garded as Ukraine’s weak­ness; it came across ex­plic­itly, and chill­ingly, when Stephen Miller, the pres­i­den­t’s most pow­er­ful aide, told CNN’s Jack Tapper: “We live in a world, in the real world, that is gov­erned by strength, that is gov­erned by force, that is gov­erned by power. These are the iron laws of the world that have ex­isted since the be­gin­ning of time.” Those words, though alien to the tra­di­tions of American and Christian moral­ity, could have come from the lips of any fas­cist dic­ta­tor.

Politicized law en­force­ment. Liberals fol­low the law whether they like it or not; fas­cists, only when they like it. Nazism fea­tured a “dual state,” where, at any mo­ment, the pro­tec­tions of or­di­nary law could cease to ap­ply. Trump makes no se­cret of de­spis­ing due process of law; he has de­manded count­less times that his op­po­nents be jailed (“Lock her up!” chants, with his en­dorse­ment, were a promi­nent fea­ture of his 2016 cam­paign), and he has sug­gested the Constitution’s “termination” and said “I don’t know” when asked if he is re­quired to up­hold it. His sin­gle most dan­ger­ous sec­ond-term in­no­va­tion is the re­pur­pos­ing of fed­eral law en­force­ment to per­se­cute his en­e­mies (and shield his friends). No prior pres­i­dent has pro­duced any­thing like Trump’s di­rect and pub­lic or­der for the Justice Department to in­ves­ti­gate two for­mer of­fi­cials, or like his bla­tantly re­tal­ia­tory pros­e­cu­tions of James Comey and Letitia James. “At least 470 peo­ple, or­ga­ni­za­tions and in­sti­tu­tions have been tar­geted for ret­ri­bu­tion since Trump took of­fice—an av­er­age of more than one a day,” Reuters re­ported in November (and to­day one can add oth­ers to the list, be­gin­ning with Federal Reserve Chair Jerome Powell). Had Trump done noth­ing else, his de­mo­li­tion of in­de­pen­dent and apo­lit­i­cal law en­force­ment would still have moved the U. S. gov­ern­ment closer than ever be­fore to a fascis­tic model.

Dehumanization. Fascism draws its le­git­i­macy from its claims of de­fend­ing the peo­ple from en­e­mies who are an­i­mals, crim­i­nals, brutes. Trump char­ac­ter­izes (for in­stance) po­lit­i­cal op­po­nents as “vermin” and im­mi­grants as “garbage” who are “poisoning the blood of our coun­try” (language straight out of the Third Reich). Vice President Vance, as a sen­a­tor, en­dorsed a book called Unhumans (a ti­tle that refers to the left). And who can for­get his false claim that Haitians abduct and eat pet cats and dogs?

Police-state tac­tics. Trump has turned ICE into a sprawl­ing para­mil­i­tary that roves the coun­try at will, searches and de­tains nonci­t­i­zens and cit­i­zens with­out war­rants, uses force os­ten­ta­tiously, op­er­ates be­hind masks, re­ceives skimpy train­ing, lies about its ac­tiv­i­ties, and has been told that it en­joys “absolute im­mu­nity.” He more than dou­bled the agen­cy’s size in 2025, and its bud­get is now larger than those of all other fed­eral law-en­force­ment agen­cies com­bined, and larger than the en­tire mil­i­tary bud­gets of all but 15 coun­tries. “This is go­ing to af­fect every com­mu­nity, every city,” the Cato Institute scholar David Bier re­cently ob­served. “Really al­most every­one in our coun­try is go­ing to come in con­tact with this, one way or the other.” In Minneapolis and else­where, the agency has be­haved provoca­tively, some­times bru­tally, and ar­guably il­le­gally—be­hav­iors that Trump and his staff have en­cour­aged, shielded, and sent cam­era crews to pub­li­cize, per­haps in the hope of elic­it­ing vi­o­lent re­sis­tance that would jus­tify fur­ther crack­downs, a stan­dard fas­cist strat­a­gem. Homeland Security Secretary Kristi Noem’s re­cent ap­pear­ance with a sign read­ing One of ours, all of yours seemed to nod to­ward an­other fas­cist standby, col­lec­tive pun­ish­ment—as did the ad­min­is­tra­tion’s de­ci­sion to flood Minneapolis with thou­sands of of­fi­cers af­ter res­i­dents there be­gan protest­ing fed­eral tac­tics, a pri­or­i­ti­za­tion that was ex­plic­itly ret­ribu­tive.

Undermining elec­tions. Trump’s re­cent mus­ing that there should be no 2026 elec­tion may or may not have been joc­u­lar (as the White House has main­tained), but he and his MAGA sup­port­ers be­lieve they never lose an elec­tion, pe­riod. They went to great lengths to over­turn the 2020 elec­tion, as the pros­e­cu­tor Jack Smith’s in­dict­ment of Trump and sub­se­quent re­port de­tail ad nau­seam. Rigging, steal­ing, or out­right can­cel­ing elec­tions is, of course, job one for fas­cists. Although Trump is term-lim­ited, we must not ex­pect that he and his MAGA loy­al­ists will vol­un­tar­ily turn over the White House to a Democrat in 2029, re­gard­less of what the vot­ers say—and the sec­ond in­sur­rec­tion will be far bet­ter or­ga­nized than the first.

What’s pri­vate is pub­lic. Classical fas­cism re­jects the fun­da­men­tal lib­eral dis­tinc­tion be­tween the gov­ern­ment and the pri­vate sec­tor, per Mussolini’s dic­tum: “No in­di­vid­u­als or groups out­side the State.” Among Trump’s most au­da­cious (if only in­ter­mit­tently suc­cess­ful) ini­tia­tives are his ef­forts to com­man­deer pri­vate en­ti­ties, in­clud­ing law firms, uni­ver­si­ties, and cor­po­ra­tions. One of his first acts as pres­i­dent last year was to brazenly defy a newly en­acted law by tak­ing the own­er­ship of TikTok into his own hands. Bolton un­der­stood this men­tal­ity when he said, “He can’t tell the dif­fer­ence be­tween his own per­sonal in­ter­est and the na­tional in­ter­est, if he even un­der­stands what the na­tional in­ter­est is.”

Attacks on news me­dia. Shortly af­ter tak­ing of­fice in 2017, Trump de­nounced the news me­dia as “the en­emy of the American peo­ple,” a phrase fa­mil­iar from dic­ta­tor­ships abroad. His hos­til­ity never re­lented, but in his sec­ond term, it has reached new heights. Trump has threat­ened broad­cast li­censes, abused his reg­u­la­tory au­thor­ity, ma­nip­u­lated own­er­ship deals, filed ex­or­bi­tant law­suits, played fa­vorites with jour­nal­is­tic ac­cess, searched a re­porter’s home, and vil­i­fied news out­lets and jour­nal­ists. Although Trump can­not dom­i­nate news me­dia in the United States in the way that Prime Minister Viktor Orbán has done in Hungary, he is run­ning the Orbán play­book. No other pres­i­dent, not even Richard Nixon (no friend of the me­dia), has used such bla­tantly il­lib­eral tac­tics against the press.

Territorial and mil­i­tary ag­gres­sion. One rea­son I held out against iden­ti­fy­ing Trumpism with fas­cism in his first term was Trump’s ap­par­ent lack of in­ter­est in ag­gres­sion against other states; if any­thing, he had seemed shy about us­ing force abroad. Well, that was then. In his sec­ond term, he has used mil­i­tary force promis­cu­ously. Of course, many pres­i­dents have de­ployed force, but Trump’s ex­plic­itly preda­tory use of it to grab Venezuela’s oil and his gang­ster-style threat to take Greenland from Denmark “the easy way” or “the hard way” were 1930s-style au­thor­i­tar­ian moves. The same goes for his con­tempt for in­ter­na­tional law, bind­ing al­liances, and transna­tional or­ga­ni­za­tions such as the European Union—all of which im­pede the state’s un­con­strained ex­er­cise of its will, a cen­tral fas­cist tenet. (Mussolini: “Equally for­eign to the spirit of Fascism … are all in­ter­na­tion­al­is­tic or League su­per­struc­tures which, as his­tory shows, crum­ble to the ground when­ever the heart of na­tions is deeply stirred by sen­ti­men­tal, ide­al­is­tic or prac­ti­cal con­sid­er­a­tions.”)

Transnational reach. Like au­thor­i­tar­i­ans gen­er­ally, fas­cists love com­pany; the world is safer for them if there are more of them. In his sec­ond term, Trump has bro­ken with long-stand­ing U. S. pol­icy by di­al­ing back sup­port for hu­man rights while prais­ing and sup­port­ing au­thor­i­tar­ian pop­ulists and il­lib­eral na­tion­al­ists in Serbia, Poland, Hungary, Germany, Turkey, El Salvador, and Slovakia, among other places—and by be­ing weirdly def­er­en­tial to the strong­man Russian President Vladimir Putin. Even more strik­ing is his de facto align­ment against America’s lib­eral al­lies and their par­ties in Europe, which he holds in con­tempt.

Blood-and-soil na­tion­al­ism. A fas­cist trade­mark is its in­sis­tence that the coun­try is not just a col­lec­tion of in­di­vid­u­als but a peo­ple, a Volk: a mys­ti­cally de­fined and eth­ni­cally pure group bound to­gether by shared blood, cul­ture, and des­tiny. In keep­ing with that idea, Trump has re­pu­di­ated birthright cit­i­zen­ship, and Vance has called to “redefine the mean­ing of American cit­i­zen­ship in the 21st cen­tury” so that pri­or­ity goes to Americans with longer his­tor­i­cal ties: “the peo­ple whose an­ces­tors fought in the Civil War,” as he put it, or peo­ple whom oth­ers on the MAGA right call “heritage Americans.” In other words, some Americans are more volk­ish than oth­ers.

White and Christian na­tion­al­ism. While Vance, Trump, and MAGA do not pro­pound an ex­plicit ide­ol­ogy of racial hi­er­ar­chy, they make no se­cret of pin­ing for a whiter, more Christian America. Trump has found many ways to com­mu­ni­cate this: for ex­am­ple, by mak­ing clear his dis­dain for “shithole” coun­tries and his pref­er­ence for white Christian im­mi­grants; by point­edly ac­cept­ing white South Africans as po­lit­i­cal refugees (while clos­ing the door to most other asy­lum seek­ers); by re­nam­ing mil­i­tary bases to share the names of Confederate gen­er­als (after Congress or­dered their names re­moved); by say­ing that civil-rights laws led to whites’ be­ing “very badly treated.” In his National Security Strategy, he cas­ti­gates Europe for al­low­ing im­mi­gra­tion to un­der­mine “civilizational self-con­fi­dence” and pro­claims, “We want Europe to re­main European,” a ral­ly­ing cry of white Christian na­tion­al­ists across the con­ti­nent. Taking his cue, the Department of Homeland Security has prop­a­gated unashamedly white-na­tion­al­ist themes, and na­tional parks and mu­se­ums have scrubbed their ex­hibits of ref­er­ences to slav­ery.

Mobs and street thugs. The use of mili­tias and mobs to ha­rass, rough up, and oth­er­wise in­tim­i­date op­po­nents is a stan­dard fas­cist strat­a­gem (the text­book ex­am­ple be­ing Hitler’s Kristallnacht pogrom in 1938). As few will need re­mind­ing, the Trump-MAGA par­al­lel is the mob and mili­tia vi­o­lence against the U. S. Capitol on January 6, 2021. Trump know­ingly laid ground­work for this op­er­a­tion, call­ing on mili­tia forces to “stand back and stand by” in September 2020 and later dog-whistling “Be there, will be wild!” to his sup­port­ers. His par­don of all of the Capitol at­tack­ers—more than 1,500, in­clud­ing the most vi­o­lent—only proved what we knew, which is that they had his bless­ing. While Trump has found state vi­o­lence ad­e­quate to his pur­poses so far in his sec­ond term, street vi­o­lence is self-ev­i­dently in his reper­toire.

Leader ag­gran­dize­ment. Since 2016, when he de­clared that “I alone can fix it” and bragged that his sup­port­ers would re­main loyal if he shot some­one on Fifth Avenue, Trump has cul­ti­vated a per­son­al­ity cult. Although some of his ef­forts at self-ag­gran­dize­ment can seem com­i­cal (the gild­ing of the Oval Office, the re­nam­ing of the Kennedy Center, the pro­posed tri­umphal arch), he un­der­stands the cen­tral­ity of leader wor­ship in a fas­cist-style regime. In sharp con­tradis­tinc­tion to the American pres­i­den­tial tra­di­tion since George Washington, he makes no pre­tense of serv­ing the peo­ple or the Constitution. His mind­set, his sym­bol­ism, and his rhetoric all un­der­score the point he made to The New York Times this month: his own mind and moral­ity are the only lim­its on his global power. This is Fascism 101.

Alternative facts. As Orwell, Hannah Arendt, and prac­ti­cally every other scholar of au­thor­i­tar­i­an­ism have em­pha­sized, cre­at­ing a re­al­ity-dis­tor­tion field is the first thing a fascis­tic gov­ern­ment will do, the bet­ter to drive its own twisted nar­ra­tive, con­fuse the cit­i­zenry, de­mor­al­ize po­lit­i­cal op­po­nents, and jus­tify every man­ner of cor­rup­tion and abuse. While other pres­i­dents (including some good ones) have lied, none have come close to Trump’s de­ploy­ment of Russian-style mass dis­in­for­ma­tion, as I de­tail in my book The Constitution of Knowledge. From the start of his first term, Trump has made “alternative facts” a hall­mark of his gov­ern­ing style, is­su­ing lies, ex­ag­ger­a­tions, and half-truths at a rate of 20 a day. Predictably, his sec­ond term has brought more of the same. Following his lead, a MAGA-fied post­mod­ern right glee­fully trashes ob­jec­tiv­ity as elit­ism and truth as a mask for power.

Politics as war. A dis­tinc­tive mark of fas­cism is its con­cep­tion of pol­i­tics, best cap­tured by Carl Schmitt, an early-20th-cen­tury German po­lit­i­cal the­o­rist whose doc­trines le­git­imized Nazism. Schmitt re­jected the Madisonian view of pol­i­tics as a so­cial ne­go­ti­a­tion in which dif­fer­ent fac­tions, in­ter­ests, and ide­ol­ogy come to agree­ment, the core idea of our Constitution. Rather, he saw pol­i­tics as a state of war be­tween en­e­mies, nei­ther of which can un­der­stand the other and both of which feel ex­is­ten­tially threat­ened—and only one of which can win. The aim of Schmittian pol­i­tics is not to share the coun­try but to dom­i­nate or de­stroy the other side. This con­cep­tion has been ev­i­dent in MAGA pol­i­tics since Michael Anton (now a Trump-administration of­fi­cial) pub­lished his fa­mous ar­ti­cle ar­gu­ing that the 2016 elec­tion was a life-and-death bat­tle to save the coun­try from the left (a “Flight 93” elec­tion: “charge the cock­pit or you die”). In the speech given by Stephen Miller at Charlie Kirk’s memo­r­ial ser­vice, MAGA’s em­brace of Schmittian to­tal­ism found its apoth­e­o­sis: “We are the storm. And our en­e­mies can­not com­pre­hend our strength, our de­ter­mi­na­tion, our re­solve, our pas­sion … You are noth­ing. You are wicked­ness.”

Governing as rev­o­lu­tion. Although born in rev­o­lu­tion, the American lib­eral tra­di­tion, es­pe­cially its con­ser­v­a­tive branch, prizes con­ti­nu­ity, sta­bil­ity, and in­cre­men­tal change guided by rea­son. Fascism, by con­trast, “is not re­ac­tionary but rev­o­lu­tion­ary,” as Mussolini in­sisted. It seeks to up­root and re­place the old or­der and em­braces bold, ex­hil­a­rat­ing ac­tion un­shack­led to ra­tio­nal de­lib­er­a­tion. MAGA em­braces its own rev­o­lu­tion­ary ethos, what Russell Vought, the ad­min­is­tra­tion’s Office of Management and Budget di­rec­tor and prob­a­bly its most for­mi­da­ble in­tel­lect, has called “radical con­sti­tu­tion­al­ism,” a doc­trine that would vi­ti­ate many checks on pres­i­den­tial power. In pur­suit of this vi­sion, Vought told Tucker Carlson in a November 2024 in­ter­view, “The pres­i­dent has to move ex­ec­u­tively as fast and as ag­gres­sively as pos­si­ble, with a rad­i­cal con­sti­tu­tional per­spec­tive, to be able to dis­man­tle that [federal] bu­reau­cracy and their power cen­ters” be­cause “the bu­reau­cra­cies hate the American peo­ple.” He pre­dicted, “If you have a rad­i­cal con­sti­tu­tion­al­ism, it’s go­ing to be desta­bi­liz­ing … But it’s also ex­hil­a­rat­ing.” He said he would put fed­eral agen­cies “in trauma,” an idea echoed by Christopher Rufo, an ar­chi­tect of Trump’s at­tack on uni­ver­si­ties, which Rufo de­scribed as a “counterrevolution blue­print” to put uni­ver­si­ties “in an ex­is­ten­tial ter­ror.” As Trump shut­tered a con­gres­sion­ally man­dated agency, re­named an in­ter­na­tional body of wa­ter, ar­rested an op-ed writer, de­ported im­mi­grants to a for­eign gu­lag, ter­ror­ized American cities, threat­ened an ally, and more, he showed how it looks when a rad­i­cal­ized state aban­dons ra­tio­nal de­lib­er­a­tion and goes to war against it­self.

One can ob­ject that there are el­e­ments of clas­si­cal European fas­cism that are not found in Trumpism (mass ral­lies and pub­lic rit­u­als, for ex­am­ple)—or that there are ad­di­tional el­e­ments of Trumpism that be­long on the list (MAGA’s hy­per­mas­culin­ity, misog­yny, and co-op­tion of Christianity all re­sem­ble fas­cist pat­terns). The ex­er­cise of com­par­ing fas­cis­m’s var­i­ous forms is not pre­cise. If his­to­ri­ans ob­ject that Trump is not a copy of Mussolini or Hitler or Franco, the re­ply is yes—but so what? Trump is build­ing some­thing new on old prin­ci­ples. He is show­ing us in real time what 21st-century American fas­cism looks like.

If, how­ever, Trump is a fas­cist pres­i­dent, that does not mean that America is a fas­cist coun­try. The courts, the states, and the me­dia re­main in­de­pen­dent of him, and his ef­forts to brow­beat them will likely fail. He may lose his grip on Congress in November. He has not suc­ceeded in mold­ing pub­lic opin­ion, ex­cept against him­self. He has out­run the man­date of his vot­ers, his coali­tion is frac­tur­ing, and he has ne­glected tools that al­low pres­i­dents to make en­dur­ing change. He and his party may defy the Constitution, but they can­not rewrite it, thank good­ness.

Read: How to tell if your pres­i­dent is a dic­ta­tor

So the United States, once the world’s ex­em­plary lib­eral democ­racy, is now a hy­brid state com­bin­ing a fas­cist leader and a lib­eral Constitution; but no, it has not fallen to fas­cism. And it will not.

In which case, is there any point in call­ing Trump a fas­cist, even if true? Doesn’t that alien­ate his vot­ers? Wouldn’t it be bet­ter just to de­scribe his ac­tions with­out la­bel­ing him con­tro­ver­sially?

Until re­cently, I thought so. No longer. The re­sem­blances are too many and too strong to deny. Americans who sup­port lib­eral democ­racy need to rec­og­nize what we’re deal­ing with in or­der to cope with it, and to rec­og­nize some­thing, one must name it. Trump has re­vealed him­self, and we must name what we see.

It’s al­most your turn, get ready!

* Use WASD to move around and the ar­row keys to look left and right.

* Space to shoot, Shift to sprint. E to in­ter­act with doors/​ob­jects.

* Number keys for se­lect­ing weapons. Escape/Enter for menu use.

* Press Tab to show the map. If you die, press E to respawn, noob.

So… what ex­actly is this?

You know the 1993 clas­sic DOOM? I made it run on an ear­bud, then I con­nected it to the in­ter­net and made it pos­si­ble for vis­i­tors like you to sit in a queue for hours play the game re­motely!.

Yeah but it won’t just run on any old ear­bud, this only works with the Pinebuds Pro, the only ear­buds with open source firmware.

Can I look at the code or run this on my own Pinebuds?

You sure can! There are two rel­e­vant re­pos:

* DOOMBuds for the DOOM port that will run on your ear­bud

* DOOMBUDS-JS to in­ter­act with the ear­bud through your browser

Wait, why am I look­ing at a twitch stream?

This was a nec­es­sary op­ti­mi­sa­tion to avoid pay­ing out­go­ing band­width fees, once you’re 5th in the queue, the twitch player will switch to a low-la­tency MJPEG stream.

wow this front end code is atro­cious, state man­age­ment is every­whe-

shhhh don’t look don’t look it’s ok just join the queue

Give us more info, how did you get this to work?

Let’s switch to a more read­able font first.

I’ll put out an ar­ti­cle / video div­ing deeper into this later, but here are a few bits of info:

This pro­ject is made up of four parts:

The DOOM port that runs on the ear­buds

The ‘serial server’ that acts as a bridge be­tween the ear­buds and the web server and also transcodes the MJPEG stream to twitch

The web server that serves as­sets, man­ages the queue, for­wards key­presses and dis­plays the MJPEG stream

The sta­tic web­page that tells your browser what to dis­play on the screen and how to com­mu­ni­cate with the web server

The firmware pushes up against a few hard­ware lim­i­ta­tions:

Serial Connection

Earbuds don’t have dis­plays, so the only way to trans­fer data to/​from them is ei­ther via blue­tooth, or the UART con­tact pads.

Bluetooth is pretty slow, you’d be lucky to get a con­sis­tent 1mbps con­nec­tion, UART is eas­ily the bet­ter op­tion.

DOOM’s frame­buffer is (width * height) bytes, 320 * 200 = 96kB. (doom’s in­ter­nal frame­buffer is 8-bit not 24-bit)

The UART con­nec­tion pro­vides us with 2.4mbps of us­able band­width. 2,400,000 / 8 / 96,000 gives us… 3 frames per sec­ond.

Clearly we need to com­press the video stream. Modern video codecs like h264 con­sume way too much CPU and RAM.

The only fea­si­ble ap­proach is send­ing the video as an MJPEG stream. MJPEG is a stream of JPEG im­ages shown one af­ter the other.

I found an ex­cel­lent JPEG en­coder for em­bed­ded de­vices here, thanks Larry!

A con­ser­v­a­tive es­ti­mate for the av­er­age HIGH qual­ity JPEG frame is around 13.5KB, but most scenes (without en­e­mies) are around 11kb.

Theoretical max­i­mum FPS:

- Optimistic: `2,400,000 / (11,000 * 8)` = 27.3 FPS

- Conservative: `2,400,000 / (13,500 * 8)` = 22.2 FPS

CPU

The stock open source firmware has the CPU set to 100mhz, so I cranked that up to 300mhz and dis­abled low power mode.

The Cortex-M4F run­ning at 300mhz is ac­tu­ally more than enough for DOOM, how­ever it strug­gles with JPEG en­cod­ing.

This is why it maxes out at ~18fps, I don’t think there’s much else I can do to speed it up.

RAM

By de­fault, we only have ac­cess to 768KB of RAM, af­ter dis­abling the co-proces­sor it gets bumped up to the ad­ver­tised 992KB.

DOOM re­quires 4MB of RAM, though there are plenty of op­ti­mi­sa­tions that can re­duce this amount.

Pre-generating lookup ta­bles, mak­ing vari­ables const, read­ing const vari­ables from flash, dis­abling DOOM’s caching sys­tem, re­mov­ing un­needed vari­ables. It all adds up!

FLASH

The share­ware DOOM 1 wad (assets file) is 4.2MB and the ear­buds can only store 4MB of data.

Thankfully, frag­glet, a well-known doom mod­der, has al­ready solved this is­sue for me.

Squashware is his trimmed-down DOOM 1 wad that is only 1.7MB in size.

With this wad file, every­thing com­fort­ably fits in flash.

I thought you’d never ask! (please hire me)

This text is for de­vel­op­ers that have an in­tu­itive knowl­edge of what data­base in­dexes are, but don’t nec­es­sar­ily know how they work in­ter­naly, what are the trade­offs as­so­ci­ated with in­dexes, what are the types of in­dexes pro­vided by post­gres and how you can use some of its more ad­vanced op­tions to make them more op­ti­mized for your use case.

Indexes are spe­cial data­base ob­jects pri­mar­ily de­signed to in­crease the speed of data ac­cess, by al­low­ing the data­base to read less data from the disk. They can also be used to en­force con­straints like pri­mary keys, unique keys and ex­clu­sion. Indexes are im­por­tant for per­for­mance but do not speedup a query un­less the query matches the columns and data types in the in­dex. Also, as a very rough rule of thumb, an in­dex will only help if less than 15-20% of the table will be re­turned in the query, oth­er­wise the query plan­ner, a part of post­gres used to de­ter­mine how the query is go­ing to be ex­e­cuted, might pre­fer a se­quen­tial scan. In fact, re­al­ity is much more com­plex than this rule of thumb. The query plan­ner uses sta­tis­tics and pre­de­fined costs as­so­ci­ated with each type of scan to do its job, but we’re only go­ing ap­proach the query plan­ner be­hav­ior tan­gen­tially in this ar­ti­cle. So, if your query re­turns a large per­cent­age of the table, con­sider refac­tor­ing it, us­ing sum­mary ta­bles or other tech­niques be­fore throw­ing an in­dex at the prob­lem. With that in mind, let’s give a closer look at how Postgres stores your data in the disk and how in­dexes help to speedup query­ing this data.

There are six types of in­dexes avail­able in the de­fault post­gres in­stal­la­tion and more types avail­able through ex­ten­sions. Typically, they work by as­so­ci­at­ing a key value with a data lo­ca­tion in one or more rows of the table con­tain­ing that key. Each line is iden­ti­fied by a TID, or tu­ple id.

To un­der­stand in­dexes, it is im­por­tant to first un­der­stand how post­gres stores table data on disk. Every table in post­gres has one or more cor­re­spond­ing files on disk, de­pend­ing on its size. This set of files is called a heap and it is di­vided into 8kb pagesh. All table rows, in­ter­nally re­ferred to as “tuples”, are saved in these files and do not have a spe­cific or­der. The in­dex is a tree struc­ture that links the in­dexes columns to the row lo­ca­tors, also known as ctid, in the heap. We’ll zoom into the in­dex in­ter­nals later.

To see the heap files we can use a few post­gres in­ter­nal ta­bles to see where they’re lo­cated in the disk. First, we can en­ter psql and use show da­ta_di­rec­tory to show the di­rec­tory Postgres uses to store data­bases phys­i­cal files.

Now we can use the in­ter­nal pg_­class to find the file where the heap table is stored:

Finally, we can check the file on disk by run­ning this com­mand in the shell (ls $PGDATA/base/

The file has size 0 be­cause we haven’t done any INSERTs in this table yet.

Let’s add a cou­ple of rows to our table:

We can add the ctid field to the query to re­trieve the ctid of each line. The ctid is an in­ter­nal field that has the ad­dress of the line in the heap. Think of it as a pointer to the row lo­ca­tion in the heap. It con­sists of a tu­ple in the for­mat (m, n) where m is the block id and n is the tu­ple off­set. “ctid” stands for “current tu­ple id”. Here you can note that the row with id one is stored in the page 0, off­set 1.

Let’s add more play­ers to the table so that the to­tal rows is one mil­lion:

After adding more rows to the table its cor­re­spond­ing file is 30MB. Internally, it is di­vided into 8kb pages.

When we query a table with­out an in­dex, Postgres reads all tu­ples in every page and ap­ply a fil­ter. For ex­am­ple, let’s an­a­lyze the com­mand be­low that searches for rows whose name col­umn value is equal to “Ronaldo” and show how the data­base per­formed this search. We use the ex­plain com­mand with the op­tions (analyse, buffers). analyse will ac­tu­ally ex­e­cute the query in­stead of just us­ing cost es­ti­mates, and the buffers op­tion shows how much IO work was done.

Note the in out­put the line start­ing with ” -> Parallel Seq scan on foo”. This line de­notes that the data­base per­formed a se­quen­tial search and read all the rows in the table. The ex­e­cu­tion time for this query was 265.021ms. Also note the line that says “Buffers: shared hit=97 read=6272”. This mean that we needed to read 97 pages from mem­ory, and 6272 pages from disk.

Now let’s add an in­dex on the name col­umn and see how the same query per­forms. We’re us­ing the com­mand cre­ate in­dex con­cur­rently be­cause we don’t want to block the table for writes.

Here we see that the in­dex was used and that in this case the ex­e­cu­tion time was re­duced from 264.21 to 0.074 mil­lisec­onds, and the data­base only needed to read 4 pages! The re­duc­tion in ex­e­cu­tion time hap­pens be­cause, now, in­stead of read­ing all the rows in the table, the data­base uses the in­dex. The in­dex is a tree struc­ture map­ping the value “Ronaldo” to the ctid(s) of the rows that have this value in the name col­umn (in our ex­am­ple we only have one such row). The ctid is then used to quickly lo­cate these rows on the heap.

If we use \di+ to show the in­dexes in our data­base we can see that the in­dex we’ve cre­ated oc­cu­pies 30MB, roughly the same size as the foo table.

It is im­por­tant to high­light that the ex­tra speed brought by in­dices is as­so­ci­ated with sev­eral costs that must be con­sid­ered when de­cid­ing where and how to ap­ply them.

Indexes are stored in a sep­a­rate area of the heap and take up ad­di­tional disk space. The more in­dexes a table has, the greater the amount of disk space re­quired to store them. This in­curs in ad­di­tional stor­age costs for your data­base and for back­ups, in­creased repli­ca­tion traf­fic, and in­creased backup and failover re­cov­ery times. Bear in mind that its not un­com­mon for btree in­dexes to be larger than the table it­self. Learning about par­tial in­dexes, and mul­ti­col­umn in­dexes, as well as about other more space ef­fi­cient in­dex types such as BRIN can be help­ful.

Also, there is a main­te­nance cost in writ­ing op­er­a­tions such as UPDATE, INSERT and DELETE, if a field that is part of an in­dex is mod­i­fied, the cor­re­spond­ing in­dex needs to be up­dated, which can add sig­nif­i­cant over­head to the writ­ing process.

The query plan­ner (also known as query op­ti­mizer) is the com­po­nent re­spon­si­ble for de­ter­min­ing the best ex­e­cu­tion strat­egy for a query. With more in­dexes avail­able, the query plan­ner has more op­tions to con­sider, which can in­crease the time needed to plan the query, es­pe­cially in sys­tems with many com­plex queries or where there are many in­dexes avail­able.

PostgreSQL main­tains a por­tion of fre­quently ac­cessed data and in­dex pages in mem­ory in its shared buffers. When an in­dex is used, the rel­e­vant in­dex pages are loaded into shared buffers to speed up ac­cess. The more in­dexes you have and the more they are used, the more shared buffer mem­ory is nec­es­sary. Since shared buffers are lim­ited and are also used for caching data pages, fill­ing the shared buffers with in­dexes can lead to less ef­fi­cient caching of table data. It’s also good to keep in mind that the whole in­dexed col­umn is copied in every node of the btree, since there’s a limit in node size ca­pac­ity, the larger the in­dexed col­umn the deeper the tree will be.

Another as­pect of mem­ory us­age is that PostgreSQL uses work mem­ory when it ex­e­cutes queries that in­volves sort­ing or com­plex in­dex scans (involving multi-col­umn or cov­er­ing in­dexes). Larger in­dexes re­quire more mem­ory for these op­er­a­tions. Also, in­dexes re­quire mem­ory to store some meta­data about their struc­ture, col­umn names and sta­tis­tics in the sys­tem cat­a­log cache. And fi­nally in­dexes re­quire mem­ory for main­tainance op­er­a­tions like vac­u­um­ing and rein­dex­ing op­er­a­tions.

The B-Tree is a very pow­er­ful data struc­ture, pre­sent not only in Postgres but in al­most every data­base man­age­ment sys­tem, since it is a very good gen­eral pur­pose in­dex. It was in­vented by Rudolf Bayer and Edward M. McCreight while work­ing at Boeing. Nobody re­ally knows if the “B” in B-tree stands for Bayer, Boeing, bal­anced or bet­ter, and it does­n’t re­ally mat­ter. What re­ally mat­ters is that it en­ables us to search el­e­ments in the tree in O(log n) time. If you’re not fa­mil­iar with Big-O no­ta­tion, all you need to know is that is is re­ally fast - you only need to make 20 com­par­isons in or­der to find an el­e­ment in a set with 1 mil­lion items. Moreover, it can main­tain O(log n) time com­plex­ity for data sets that are larger than the RAM avail­able on a com­puter. This means that disks can be used to ex­tend RAM, thanks to the btree ef­fi­cient pre­ven­tion of disk page ac­cesses to find the de­sired data. In PostgreSQL the btree is the most com­mon type of in­dex and its the de­fault, it’s also used to sup­port sys­tem and TOAST in­dexes. Even an empty data­base has hun­dreds of btree in­dexes. It is the only in­dex type that can be used for pri­mary and unique key con­straints.

In con­trast with a bi­nary tree, the BTree is a bal­anced tree and all of its leave nodes have the same dis­tance from the root. The root nodes and in­ner nodes have point­ers to lower lev­els, and the leaf nodes have the keys and point­ers to the heap. Postgres btrees also have point­ers to the left and right nodes for eas­ier for­ward and back­ward scan­ning. Nodes can have mul­ti­ple keys and these keys are sorted so that it’s easy to walk in or­dered di­rec­tions and to per­form ORDER BY and JOIN op­er­a­tions. The val­ues are only stored in the leaf nodes, this makes the tree more com­pact and fa­cil­i­tates a full tra­ver­sal of the ob­jects in a tree with just a lin­ear pass through all the leaf nodes. This is just a sim­pli­fied de­scrip­tion of PostgreSQL Btree in­dexes, if you want to get into the low level de­tails, I sug­gest you to read the README and the pa­per that in­spired them. Below there’s a sim­pli­fied il­lus­tra­tion of a Postgres Btree.

Postgres can use mul­ti­ple in­dexes to han­dle cases that can­not be han­dled by sin­gle in­dex scans, by form­ing AND and OR con­di­tions across sev­eral in­dex scans with the sup­port of bitmaps. The bitmaps are ANDed or ORed to­gether as needed by the query and fi­nally the table rows are vis­ited and re­turned. Let’s say we have a query like this:

If the age and lo­gin_­count columns are in­dexed, post­gres scans in­dex age for all pages with age=30 and makes a bitmap where the pages that might con­tain rows with age=30 are true. In a sim­i­lar way, it builds a bitmap us­ing the lo­gin_­count in­dex. It then ANDs the two bitmaps to form a third bitmap, and per­forms a table scan, only read­ing the pages that might con­tain can­di­date val­ues, and only adding the rows where age=30 and lo­gin_­count=100 to the re­sult set.

Multi-column in­dexes are an al­ter­na­tive for us­ing mul­ti­ple in­dexes. They’re gen­er­aly go­ing to be smaller and faster than us­ing mul­ti­ple in­dexes, but they’ll also be less flex­i­ble. That’s be­cause the or­der of the columns mat­ter, be­cause the data­base can search for a sub­set of the in­dexed columns, as long as they are the left­most columns. For ex­am­ple, if you have an in­dex on col­umn a and an­other in­dex on col­umn b, these in­dexes will serve all the of queries be­low:

On the other hand, only the first two queries would use an in­dex if you cre­ated a multi-col­umn in­dex on (a, b) with a com­mand like cre­ate in­dex on my_table(a, b); So, when build­ing multi-col­umn in­dexes choose the or­der of the columns well so that your in­dex can be used by the most queries pos­si­ble.

Partial in­dexes al­low you to use a con­di­tional ex­pres­sion to con­trol what sub­set of rows will be in­dexed, this can bring you many ben­e­fits:

* your in­dex can be smaller and more likely fit in RAM.

* your in­dex is shal­lower, so lookups are quicker

* less over­head for in­dex/​up­date/​delete (but can also mean more over­head if the col­umn you’re us­ing to fil­ter rows in/​out of the in­dex is up­dated very fre­quently trig­ger­ing con­stant in­dex main­te­nance)

They’re mostly use­ful in sit­u­a­tions where you don’t care about some rows, or when you’re in­dex­ing on a col­umn where the pro­por­tion of one value is much greater than oth­ers. I’ll give two ex­am­ples be­low.

Let’s say you have a rules table where the rows can be marked as en­abled/​dis­abled, the vast ma­jor­ity of the rows are dis­abled and in your queries you only care about en­abled rows. In this case, you would have a par­tial in­dex, fil­ter­ing out the dis­able rows like this:

Now imag­ine you’re build­ing a todo ap­pli­ca­tion and the sta­tus col­umn value can be ei­ther TODO, DOING, and DONE. Suppose you have 1M rows and this is the cur­rent dis­tri­b­u­tion of rows in each sta­tus:

Since post­gres keeps sta­tis­tics about the dis­tri­b­u­tion of val­ues in your table columns and knows that the vast ma­jor­ity of the rows are in the TODO sta­tus, it would choose to do a se­quen­tial scan on the tasks table when you have sta­tus=‘TODO’ in the WHERE clause of your query, even if you have an in­dex on sta­tus, leav­ing most part of the in­dex un­used and wast­ing space. In this case, a par­tial scan such as the one be­low is rec­om­mended:

If you have a query that se­lects only columns in an in­dex, Postgres has all in­for­ma­tion needed by the query in the in­dex and does­n’t need to fetch pages from the heap to re­turn the re­sult. This op­ti­miza­tion is called in­dex-only scan. To un­der­stand how it works, con­sider the fol­low­ing sce­nario:

In the first query, post­gres can do an in­dex-only scan and avoid fetch­ing data from the heap be­cause the val­ues a and b are pre­sent in the in­dex. In the sec­ond query, since c is­n’t in the in­dex, pos­gres needs to fol­low the ref­er­ence to the heap to fetch its value. In the first query we al­lowed post­gres do to an in­dex-only scan with the help of a multi-col­umn in­dex, but we could also achieve the same re­sult by us­ing a cov­er­ing in­dex. The syn­tax for cre­at­ing a cov­er­ing in­dex looks like this:

This is more space ef­fi­cient than cre­at­ing a multi-col­umn in­dex on (a, b, c), be­cause c will only be in­serted at the leaf nodes of the btree. Also, we might want to use a cov­er­ing in­dex in cases where we want an unique in­dex and c would “break” the unique­ness of the in­dex.

Expression in­dexes to in­dex the re­sult of an ex­pres­sion or func­tion, rather than just the raw col­umn val­ues. This can be ex­tremely use­ful when you fre­quently query based on a trans­formed ver­sion of your data. It is nec­es­sary if you use a func­tion as part of a where clause as in the ex­am­ple be­low:

In this ex­am­ple above, Postgres won’t use the in­dex be­cause it was was built against the name col­umn. In or­der to make it work, the in­dex key has to call the lower func­tion just like it’s used in the where clase. To fix it, do:

Now, when you run a query like this:

Now PostgreSQL can use the ex­pres­sion in­dex to ef­fi­ciently find the match­ing rows.

Expression in­dexes can be cre­ated us­ing var­i­ous types of ex­pres­sions:

User-defined func­tions: As long as they are im­mutable.

The hash in­dex dif­fers from B-Tree in strucutre, it is much more alike a hashmap data struc­ture pre­sent in most pro­gram­ming lan­guages (e.g. dict in Python, ar­ray in php, HashMap in java, etc). Instead of adding the full col­umn value to the in­dex, a 32bit hash code is de­rived from it and added to the hash. This makes hash in­dexes much smaller than btrees when in­dex­ing longer data such as UUIDs, URLs, etc. Any data type can be in­dexed with the help of post­gres hash­ing func­tions. If you type \df hash* and press TAB in psql, you’ll see that there are more then 50 hash re­lated func­tions. Although it grace­fully han­dles hash con­flicts, it works bet­ter for even dis­tri­b­u­tion of hash val­ues and is most suited to unique or mostly unique data. Under the cor­rect con­di­tions it will not only be smaller than btree in­dexes, but also it will be faster for reads when com­pared with btress. Here’s what the of­fi­cial docs says about it:

“In a B-tree in­dex, searches must de­scend through the tree un­til the leaf page is found. In ta­bles with mil­lions of rows, this de­scent can in­crease ac­cess time to data. The equiv­a­lent of a leaf page in a hash in­dex is re­ferred to as a bucket page. In con­trast, a hash in­dex al­lows ac­cess­ing the bucket pages di­rectly, thereby po­ten­tially re­duc­ing in­dex ac­cess time in larger ta­bles. This re­duc­tion in “logical I/O” be­comes even more pro­nounced on in­dexes/​data larger than shared_buffers/​RAM.”

As for its lim­i­ta­tions, it only sup­ports equal­ity op­er­a­tions and is­n’t go­ing to be help­ful if you need to or­der by the in­dexed field. It also does­n’t sup­port multi-col­umn in­dexes and check­ing for unique­ness. For a in-depth analy­sis of how hash in­dexes fare in re­la­tion to btree, check Evgeniy Demin’s blog post on the sub­ject.

BRIN stands for Block Range Index and its name tells a lot about how it is im­ple­mented. Nodes in BRIN in­dexes store the min­i­mum and max­i­mum val­ues of a range of val­ues pre­sent in the page re­ferred by the in­dex. This makes the in­dex more com­pact and cache friendly, but re­stricts the use cases for it. If you have a very large in a work load that is heavy on writes and low on deletes and up­dates. You can think of a BRIN in­dex as an op­ti­mizer for se­quen­tial scans of large amounts of data in very large data­bases, and is a good op­ti­miza­tion to try be­fore par­ti­tion­ing a table. For a BRIN in­dex to work well, the in­dex key should be a col­umn that strongly cor­re­lates to the lo­ca­tion of the row in the heap. Some good use cases for BRIN are ap­pend-only ta­bles and ta­bles stor­ing time se­ries data.

BRIN won’t work well for ta­bles where the rows are up­dated con­stantly, due to the na­ture of MVCC that du­pli­cates rows and stores them in a dif­fer­ent part of the heap. This tu­ple du­pli­ca­tion and mov­ing af­fect the cor­re­la­tion neg­a­tively and re­duces the ef­fec­tive­ness of the in­dex. Using ex­ten­sions such as pg_repack or pg_squeeze is­n’t rec­om­mended for ta­bles that use BRIN in­dexes, since they change the in­ter­nal data lay­our fo the table and mess up the cor­re­la­tion. Also, this in­dex is lossy in the sense that the in­dex leaf nodes point to pages taht might con­tain a value within a par­tic­u­lar range. For this rea­son a BRIN is more help­ful if you need to re­turn large sub­set of data, and a btree would be more read per­for­mant for queries that only re­turn one or few rows. You can make the in­dex more or less lossy by ad­just­ing the page_per_range con­fig­u­ra­tion, the trade off will be in­dex size.

Generalized in­verted in­dex is ap­pro­pri­ate for when you want to search for an item in com­pos­ite data, such as find­ing a word in a blob of text, an item in an ar­ray or an ob­ject in a JSON. The GIN is gen­er­al­ized in the sense that it does­n’t need to know how it will acel­er­ate the search for some item. Instead, there’s a set of cus­tom strate­gies spe­cific for each data type. Please note that in or­der to in­dex an JSON value it needs to be stored in a JSONB col­umn. Similarly, if you’re in­dex­ing text it’s bet­ter to store it as (or con­vert it to) tsvec­tor or use the pg_trgm ex­ten­sion.

The Generalized Search Tree and the Space-Partitioned Generalized Search Tree are tree struc­tures that can be use as a base tem­plate to im­ple­ment in­dexes for spe­cific data types. You can think of them as frame­work for build­ing in­dexes. The GiST is a bal­anced tree and the SP-GiST al­low for the de­vel­op­ment of non-bal­anced data struc­tures. They are use­ful for in­dex­ing points and geo­met­ric types, inet, ranges and text vec­tors. You can find an ex­ten­sive list of the built-in strate­gies shipped with post­gres in the of­fi­cial doc­u­men­ta­tion. If you need an in­dex to en­able full-text search in your ap­pli­ca­tion, you’ll have to choose be­tween GIN and GiST. Roughly speak­ing, GIN is faster for lookups but it’s big­ger and has greater build­ing and main­tainance costs. So the right in­dex type for you will de­pend on your ap­pli­ca­tion re­quire­ments.

Understanding and ef­fec­tively us­ing in­dexes is cru­cial for op­ti­miz­ing data­base per­for­mance in PostgreSQL. While in­dexes can greatly speed up query ex­e­cu­tion and im­prove over­all ef­fi­ciency, it’s im­por­tant to be mind­ful of their im­pact on write op­er­a­tions and stor­age. By care­fully se­lect­ing the ap­pro­pri­ate types of in­dexes based on your spe­cific use cases you can en­sure that your PostgreSQL data­base re­mains both fast and ef­fi­cient. I hope this ar­ti­cle taught you at least one or two things you did­n’t know about Postgres in­dexes, and that you’re bet­ter equiped to deal with dif­fer­ent sce­nar­ios in­volv­ing data­bases from now on.

The Trump White House yes­ter­day posted a ma­nip­u­lated photo of Nekima Levy Armstrong, a Minnesota civil rights at­tor­ney who was ar­rested af­ter protest­ing in a church where a pas­tor is al­legedly also an Immigration and Customs Enforcement (ICE) of­fi­cial.

Secretary of Homeland Security Kristi Noem posted what seems to be the orig­i­nal photo of Armstrong be­ing led away by an of­fi­cer yes­ter­day morn­ing. A half hour later, the of­fi­cial White House X ac­count posted an al­tered ver­sion in which Armstrong’s face was ma­nip­u­lated to make it ap­pear that she was cry­ing.

“The White House shared an AI-edited photo of Nekima, de­pict­ing her in tears and scared when, in ac­tu­al­ity, she was poised, de­ter­mined, and un­afraid,” NAACP President and CEO Derrick Johnson said yes­ter­day.

Reader-added con­text on X said, “This photo has been dig­i­tally al­tered to make Nekima Levy Armstrong ap­pear to be in dis­tress. The Director of DHS her­self posted the unedited photo in an ear­lier an­nounce­ment.” White House Deputy Communications Director Kaelan Dorr de­fended the post af­ter crit­i­cism of the im­age ma­nip­u­la­tion.

“Enforcement of the law will con­tinue. The memes will con­tinue. Thank you for your at­ten­tion to this mat­ter,” Dorr wrote. The White House post with the ma­nip­u­lated im­age called Levy Armstrong a “far-left ag­i­ta­tor” who “orchestrated[ed] church ri­ots in Minnesota.”

A DHS press re­lease about the ar­rest used the same im­age posted by Noem, with­out the al­ter­ation.

Jordan Kushner, an at­tor­ney for Levy Armstrong, said, “It is just so out­ra­geous that the White House would make up sto­ries about some­one to try and dis­credit them. She was com­pletely calm and com­posed and ra­tio­nal. There was no one cry­ing. So this is just out­ra­geous defama­tion.”

Speaking to The Associated Press, Kushner also said that the “video Levy Armstrong’s hus­band shot ‘dismantles what they claim’ and that the video would be re­leased soon.”

As many as 30,000 peo­ple could have been killed in the streets of Iran on Jan. 8 and 9 alone, two se­nior of­fi­cials of the coun­try’s Ministry of Health told TIME—indicating a dra­matic surge in the death toll. So many peo­ple were slaugh­tered by Iranian se­cu­rity ser­vices on that Thursday and Friday, it over­whelmed the state’s ca­pac­ity to dis­pose of the dead. Stocks of body bags were ex­hausted, the of­fi­cials said, and eigh­teen-wheel semi-trail­ers re­placed am­bu­lances.

The gov­ern­men­t’s in­ter­nal count of the dead, not pre­vi­ously re­vealed, far sur­passes the toll of 3,117 an­nounced on Jan. 21 by regime hard­lin­ers who re­port di­rectly to Iran’s Supreme Leader Ali Khamenei. (Ministries re­port to the elected President.) The 30,000 fig­ure is also far be­yond tal­lies be­ing com­piled by ac­tivists me­thod­i­cally as­sign­ing names to the dead. As of Saturday, the U. S.-based Human Rights Activists News Agency said it had con­firmed 5,459 deaths and is in­ves­ti­gat­ing 17,031 more.TIME has been un­able to in­de­pen­dently ver­ify these fig­ures.The Health Ministry’s two-day fig­ure roughly aligns with a count gath­ered by physi­cians and first re­spon­ders, and also shared with TIME. That sur­rep­ti­tious tally of deaths recorded by hos­pi­tals stood at 30,304 as of Friday, ac­cord­ing to Dr. Amir Parasta, a German-Iranian eye sur­geon who pre­pared a re­port of the data. Parasta said that num­ber does not re­flect protest-re­lated deaths of peo­ple reg­is­tered at mil­i­tary hos­pi­tals, whose bod­ies were taken di­rectly to morgues, or that hap­pened in lo­cales the in­quiry did not reach. Iran’s National Security Council has said protests took place in around 4,000 lo­ca­tions across the coun­try.

“We are get­ting closer to re­al­ity,” Dr. Parasta said. “But I guess the real fig­ures are still way higher.”That ap­pears to be the re­al­ity im­plicit in the gov­ern­men­t’s in­ter­nal fig­ure of more than 30,000 deaths in two days. A slaugh­ter on that scale, in the space of 48 hours, had ex­perts on mass killing grop­ing for com­par­isons.“Most spasms of killing are not from shoot­ings,” said Les Roberts, a pro­fes­sor at Columbia University who spe­cial­izes in the epi­demi­ol­ogy of vi­o­lent death. “In Aleppo [Syria] and in Fallujah [Iraq], when spasms of death this high have oc­curred over a few days, it in­volved mostly ex­plo­sives with some shoot­ing.”The only par­al­lel of­fered by on­line data­bases oc­curred in the Holocaust. On the out­skirts of Kyiv on Sept. 29 and 30, 1941, Nazi death squads ex­e­cuted 33,000 Ukrainian Jews by gun­shot in a ravine known as Babyn Yar. In Iran, the killing fields ex­tended across the coun­try where, since Dec. 28, hun­dreds of thou­sands of cit­i­zens had as­sem­bled in the streets chant­ing first, for re­lief from an econ­omy in freefall, and soon for the down­fall of the Islamic regime. During the first week, se­cu­rity forces con­fronted some demon­stra­tions, us­ing mostly non-lethal force, but with of­fi­cials also of­fer­ing con­cil­ia­tory lan­guage, the regime re­sponse was un­cer­tain. That changed dur­ing the week­end com­menc­ing Jan. 8. Protests peaked, as op­po­si­tion groups, in­clud­ing Reza Pahlavi, the ex­iled son of Iran’s for­mer shah, urged peo­ple to join the throngs, and U.S. President Donald Trump re­peated vows to pro­tect them, though no help ar­rived.

Witnesses say mil­lions were in the streets when au­thor­i­ties shut down the in­ter­net and all other com­mu­ni­ca­tions with the out­side world. Rooftop snipers and trucks mounted with heavy ma­chine guns opened fire, ac­cord­ing to eye­wit­nesses and cell phone footage. On Friday, Jan. 9, an of­fi­cial of the Islamic Revolutionary Guard Corps warned on state tele­vi­sion to any­one ven­tur­ing into the streets, “if … a bul­let hits you, don’t com­plain.”It took days for the re­al­ity to pen­e­trate the in­ter­net black­out. Images of the blood­ied bod­ies trick­led out via il­licit Starlink satel­lite in­ter­net con­nec­tions. The task of count­ing the dead was ham­pered, how­ever, be­cause the au­thor­i­ties had also cut off lines of com­mu­ni­ca­tions in­side Iran. The first firm in­for­ma­tion came from a Tehran doc­tor who told TIME that just six hos­pi­tals in the cap­i­tal had recorded at least 217 pro­tester deaths af­ter Thursday’s as­sault. Health care work­ers in Iran es­ti­mated at least 16,500 pro­test­ers had been killed by Jan. 10, ac­cord­ing to an ear­lier re­port by Dr. Parasta in Munich. Friday’s up­date built on that re­search, he said.

“I am gen­uinely im­pressed by how quickly this work was pulled to­gether un­der ex­tremely con­strained and risky con­di­tions,” said Paul B. Spiegel, a pro­fes­sor at the Johns Hopkins University International School of Health. Like Roberts, he ex­pressed wari­ness of ex­trap­o­lat­ing from the fig­ures pro­vided by hos­pi­tals. Roberts, who trav­eled into war zones to re­search civil­ian death rates in Iraq and the Democratic Republic of Congo, said, “the 30,000 ver­i­fied deaths are al­most cer­tainly an un­der­es­ti­mate.”The emer­gence of the Ministry of Health num­bers ap­pears to con­firm that—while un­der­scor­ing the stakes for both Iranians and a regime that, in 1979, came to power when a sit­ting gov­ern­ment was con­fronted by mil­lions of peo­ple de­mand­ing its down­fall. On Friday, Jan. 9, Sahba Rashtian, an as­pir­ing an­i­ma­tion artist, joined friends on the streets in Isfahan, a city in cen­tral Iran fa­mous for its beauty. “Before any­one started chant­ing,” a friend told TIME, “Sahba was seen col­lapsed on the ground. Her sis­ter no­ticed blood on her hand.”

Sahba died on an op­er­at­ing table at a nearby hos­pi­tal. She was 23.

“She al­ways joked about her beau­ti­ful name,” her friend said. “She’d laugh and say, ‘Sahba means wine, and I am for­bid­den in the Islamic Republic.’”

At the bur­ial, the friend said, re­li­gious rites were barred, and Rashtian’s fa­ther wore white.

“Congratulations,” he told mourn­ers, ac­cord­ing to the friend. “My daugh­ter be­came a mar­tyr on the path to free­dom.”

The Federal Aviation Administration has is­sued a na­tion­wide se­cu­rity no­tice, ef­fec­tively cre­at­ing a mov­ing drone no-fly zone around op­er­a­tions con­ducted by Immigration and Customs Enforcement (ICE) and other com­po­nents of the Department of Homeland Security.

The no­tice, NOTAM FDC 6/4375, pro­hibits un­manned air­craft sys­tems from op­er­at­ing within 3,000 feet lat­er­ally and 1,000 feet ver­ti­cally of DHS fa­cil­i­ties and mo­bile as­sets, in­clud­ing ground ve­hi­cle con­voys and their es­corts. The re­stric­tion ap­plies na­tion­wide and con­tin­u­ously, rather than at fixed lo­ca­tions or dur­ing de­fined time win­dows.

Because ICE operates under DHS and rou­tinely con­ducts en­force­ment ac­tions us­ing mo­bile ve­hi­cle con­voys in pub­lic spaces, the re­stric­tion func­tions as a drone no-fly zone around ICE op­er­a­tions, in­clud­ing ar­rests, trans­port ac­tiv­i­ties and other field ac­tions.

The FAA clas­si­fies the re­stricted air­space as “national de­fense air­space,” and cites its au­thor­ity un­der fed­eral se­cu­rity statutes. Drone op­er­a­tors who vi­o­late the re­stric­tion may face crim­i­nal pros­e­cu­tion, civil penal­ties, ad­min­is­tra­tive en­force­ment ac­tions, or re­vo­ca­tion of FAA op­er­at­ing priv­i­leges. The no­tice also states that drones deemed a cred­i­ble se­cu­rity threat may be in­ter­cepted, seized, dam­aged, or de­stroyed.

Unlike tra­di­tional Temporary Flight Restrictions, the NOTAM does not pro­vide ge­o­graphic co­or­di­nates, ac­ti­va­tion times, or pub­lic no­ti­fi­ca­tion when the re­stric­tion is in ef­fect near a spe­cific lo­ca­tion. Instead, the re­stricted air­space moves with DHS as­sets, mean­ing the no-fly zone can ap­pear wher­ever ICE or other DHS units op­er­ate.

The new NOTAM re­places an ear­lier se­cu­rity no­tice, FDC 5/6378, which cov­ered sim­i­lar fed­eral agen­cies but was less ex­plicit about mo­bile op­er­a­tions. The up­dated ver­sion re­moves am­bi­gu­ity by clearly stat­ing that the re­stric­tion ap­plies to mov­ing DHS as­sets, in­clud­ing ve­hi­cles and con­voys, and not just fixed fa­cil­i­ties such as of­fices or bases.

That clar­i­fi­ca­tion has drawn at­ten­tion from drone op­er­a­tors and civil lib­er­ties groups be­cause it cre­ates dy­namic, in­vis­i­ble ex­clu­sion zones that may be im­pos­si­ble to iden­tify in real time. The FAA does not pub­lish pub­lic track­ing of DHS or ICE move­ments, and the NOTAM does not in­clude a mech­a­nism for drone pi­lots to de­ter­mine when cov­ered as­sets are nearby.

In prac­ti­cal terms, a drone op­er­a­tor fly­ing legally in a pub­lic area could un­know­ingly en­ter re­stricted air­space if an ICE con­voy passes within the pro­tected ra­dius. The FAA in­structs op­er­a­tors to “exercise cau­tion” when fly­ing near DHS fa­cil­i­ties and mo­bile as­sets, but of­fers no spe­cific guid­ance on how to do so in en­vi­ron­ments where en­force­ment ac­tiv­ity is not pub­licly dis­closed.

The no­tice men­tions lim­ited ex­cep­tions. Drone op­er­a­tions con­ducted in di­rect sup­port of na­tional de­fense, home­land se­cu­rity, law en­force­ment, fire­fight­ing, search and res­cue, or dis­as­ter re­sponse mis­sions may be au­tho­rized with ad­vance co­or­di­na­tion. Operators seek­ing ap­proval are in­structed to co­or­di­nate with DHS or other cov­ered agen­cies, or con­tact the FAA’s System Operations Support Center.

The FAA cites mul­ti­ple fed­eral statutes as the le­gal ba­sis for the re­stric­tion, in­clud­ing laws gov­ern­ing na­tional de­fense air­space and counter-UAS mit­i­ga­tion.