What is Hackers' Pub?

Hackers' Pub is a place for software engineers to share their knowledge and experience with each other. It's also an ActivityPub-enabled social network, so you can follow your favorite hackers in the fediverse and get their latest posts in your feed.

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This is a link to an article written by someone else, not me:

"I tried building my startup entirely on European infrastructure. Here's the stack I landed on, what was harder than expected, and what you still can't avoid."

coinerella.com/made-in-eu-it-w

We need more stories like this being shared in the open. You can criticise some parts of the decisions made here, but that's not the point. Someone tried, learned and shares the result. *That's* the point.

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청와대 직원들이 조간신문 나오는 -이것부터가 잘못되었다. 요즘 세상에 신문 인쇄가 업무 기준이라니 - 새벽 5시 30분에 출근해서 일러야 밤 10시쯤 퇴근하고, 주 6일제에 토/일도 실질적으로 당번제로 출근하고 있다고 함. 어느 분 표현이 적절하다 싶어 가져옵니다 "그리고 이 중노동을 근거로 이후 승진, 공천, 각종 이권들을 요구할게 예상되고 그런 보상이라도 주어져야겠다는 논리를 들이밀텐데 이게 과연 좋기만 한 일일지 벌써 걱정입니다."

RE: https://bsky.app/profile/did:plc:a6qvfkbrohedqy3dt6k5mdv6/post/3mfb25qiibc2o

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RT: @owenjonesjourno The first proper poll of Gorton and Denton is out, conducted by Omnisis.

It shows:

🟢 The Greens on 22%

🟣 Reform UK on 20%

🔴 Labour on 18%

🤷‍♀️ Undecideds on 31%

It shows the Greens are best placed to defeat Reform - but it all depends on Undecideds.

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「普通の市民は戦争が嫌いだ。しかし政策を決定するのは指導者達であり、国民をそれに巻き込むのは…簡単なことだ。自分達が外国から攻撃されていると説明するだけでいい。平和主義者は愛国心がなく国家を危険に晒す人々だと非難すればいいだけ。この方法はどの国でも通用する」(ヘルマン・ゲーリング)

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I’ve just published the first article of a new series on my blog: “Django ORM standalone” 🧩

The idea is to use Django ORM in standalone mode to connect to existing or legacy databases and work only with the ORM, without the rest of Django, using inspectdb for reverse engineering the schema and querying data with Django QuerySets 🔎

If you’re curious about using Django ORM this way, here’s the link, and let me know what you think 💡
paulox.net/2026/02/20/django-o

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無編集の写真を投稿することがおおいんだけど、uneditedタグをつけてるとたまに怒られるというかどうも怒ってる感じの人からツッコミがはいる

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If you're on LinkedIn and are thinking about verifying your account with them, maybe read this first. It walks through LinkedIn's privacy disclosure to identify 17 companies that may receive and process the data you submit, including name, passport photo, selfie, facial geometry, NFC data chip, national ID #, DoB, email, phone number, address, IP address, device type, MAC address, language, geolocation etc. Unsurprisingly, it seems the biggest recipients are US-based AI companies.

thelocalstack.eu/posts/linkedi

A screenshot from thelocalstack.eu 

// THE 17 COMPANIES THAT TOUCH YOUR FACE

Persona maintains a public list of subprocessors — third-party companies that process your personal data on their

behalf. Here's the ful list:
COMPANY WHAT THEY DO WITH YOUR DATA LocATION
Anthropic Data Extraction and Analysis San Francisco, USA
Openal Data Extraction and Analysis San Francisco, USA
Grogeloud Data Extraction and Analysis San Jose, USA
AWS Infrastructure, Image Processing Houston, USA
Google Cloud Platform Infrastructure as a Service Mountain View, USA
Resistant Al Document Analysis New York, USA
FingerprintJs Device Analysis Chicago, USA
MongoDB Database Services New York, USA
Snowflake Database Services Bozeman, USA
Elasticsearch Search and Analytics Engine Mountain View, USA
Confluent ETL Services Mountain View, USA
DBT ETL Services Philadelphia, USA
Sigma Computing Data Analytics. San Francisco, USA
Tableau Data Analytics. Seattle, USA
Stripe Gredit Card Processing South San Francisco, USA
Twilio Communication APs (Phone, SMS) Denver, USA
Persona Identities Canada Gustomer Support & Development Toronto, Canada
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If you're on LinkedIn and are thinking about verifying your account with them, maybe read this first. It walks through LinkedIn's privacy disclosure to identify 17 companies that may receive and process the data you submit, including name, passport photo, selfie, facial geometry, NFC data chip, national ID #, DoB, email, phone number, address, IP address, device type, MAC address, language, geolocation etc. Unsurprisingly, it seems the biggest recipients are US-based AI companies.

thelocalstack.eu/posts/linkedi

A screenshot from thelocalstack.eu 

// THE 17 COMPANIES THAT TOUCH YOUR FACE

Persona maintains a public list of subprocessors — third-party companies that process your personal data on their

behalf. Here's the ful list:
COMPANY WHAT THEY DO WITH YOUR DATA LocATION
Anthropic Data Extraction and Analysis San Francisco, USA
Openal Data Extraction and Analysis San Francisco, USA
Grogeloud Data Extraction and Analysis San Jose, USA
AWS Infrastructure, Image Processing Houston, USA
Google Cloud Platform Infrastructure as a Service Mountain View, USA
Resistant Al Document Analysis New York, USA
FingerprintJs Device Analysis Chicago, USA
MongoDB Database Services New York, USA
Snowflake Database Services Bozeman, USA
Elasticsearch Search and Analytics Engine Mountain View, USA
Confluent ETL Services Mountain View, USA
DBT ETL Services Philadelphia, USA
Sigma Computing Data Analytics. San Francisco, USA
Tableau Data Analytics. Seattle, USA
Stripe Gredit Card Processing South San Francisco, USA
Twilio Communication APs (Phone, SMS) Denver, USA
Persona Identities Canada Gustomer Support & Development Toronto, Canada
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RE: fosstodon.org/@paulox/11610288

A++ content. I was in a call with @mkennedyMichael Kennedy and @pythonbynightMario Munoz this week, where this topic came up again.

We looked, and I thought Django's package size was 200M bigger than it actually is. Django is only 10.9 MB compressed, which is within ~1 MB of SQLAlchemy, which is kind of impressive to think about.

So running the Django ORM doesn't quite have the same mental tax as I have assumed all of these years.

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緊急快訊:美國最高法院裁定,川普大部份關稅非法無效,認為憲法不授予總統及行政機關權力自行加徵關稅

判決針對動用《國際緊急經濟權力法》IEEPA而開徵的關稅,包括全部「對等關稅」,以及向中加墨三國徵收的「芬太尼關稅」

9名法官以6比3同意這份判辭

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If you're on LinkedIn and are thinking about verifying your account with them, maybe read this first. It walks through LinkedIn's privacy disclosure to identify 17 companies that may receive and process the data you submit, including name, passport photo, selfie, facial geometry, NFC data chip, national ID #, DoB, email, phone number, address, IP address, device type, MAC address, language, geolocation etc. Unsurprisingly, it seems the biggest recipients are US-based AI companies.

thelocalstack.eu/posts/linkedi

A screenshot from thelocalstack.eu 

// THE 17 COMPANIES THAT TOUCH YOUR FACE

Persona maintains a public list of subprocessors — third-party companies that process your personal data on their

behalf. Here's the ful list:
COMPANY WHAT THEY DO WITH YOUR DATA LocATION
Anthropic Data Extraction and Analysis San Francisco, USA
Openal Data Extraction and Analysis San Francisco, USA
Grogeloud Data Extraction and Analysis San Jose, USA
AWS Infrastructure, Image Processing Houston, USA
Google Cloud Platform Infrastructure as a Service Mountain View, USA
Resistant Al Document Analysis New York, USA
FingerprintJs Device Analysis Chicago, USA
MongoDB Database Services New York, USA
Snowflake Database Services Bozeman, USA
Elasticsearch Search and Analytics Engine Mountain View, USA
Confluent ETL Services Mountain View, USA
DBT ETL Services Philadelphia, USA
Sigma Computing Data Analytics. San Francisco, USA
Tableau Data Analytics. Seattle, USA
Stripe Gredit Card Processing South San Francisco, USA
Twilio Communication APs (Phone, SMS) Denver, USA
Persona Identities Canada Gustomer Support & Development Toronto, Canada
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I've started my exploration of using @timbray's Quamina project for saving some compute time in the filters module of

Currently the GoAP storage backends iterate over resources (usually stored as raw JSON bytes), unmarshal them into GoActivityPub object structs, and *only* then apply the custom filtering logic on those objects. Since the majority of the objects generally fail the filtering logic, all that JSON decoding is wasted compute time and makes things slower.

Ideally quamina will allow me to check the raw JSON payloads directly against the filters, streamlining the execution and speeding things up. :goose_hacker:

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미니애폴리스 이후, 노동조합과 흑인 조직이 나서기 시작했다 www.sisain.co.kr/news/article... "인구 40명만의 도시 미니애폴리스에서 최대 10만명이 모이는 트럼프 이민정책 반대 시위가 매주 벌어진다. 그리고 이민정책 반대를 넘어 무도한 공권력에 저항하는 반(反)트럼프 시위로 확대 중이다. 학생들도 학교에 가지 않은 채 시위에 참여하고, 이전까지 트럼프의 이민정책을 강하게 반대하지 않던 노동조합들도 적극 나섰다."

미니애폴리스 이후, 노동조합과 흑인 조직이 나서기 시작...

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Shout out to everyone reading this paper, not understanding it, and drawing the wrong conclusions.🤷🏿‍♂️

nature.com/articles/s41586-026

Switching to Twitter's algorithmic feed from chronological, only shifts political attitudes to the right *for people susceptible to far-right nonsense.*

Because they start following far-right dudes🤡

Switching back to chronological doesn't undo the far-right shift...

Because the people affected don't unfollow the far-right dudes. And they don't start following more normal people🤡

Again, Black folk use Twitter the *most*. Black people get exposed to far-right dudes but are the *least* far-right

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@thisismissemEmelia 👸🏻 I have just implemented that for the GoActivityPub servers and it's easier than it sounds.

The only important step required is to convert the client authorization token (presumably an OAuth2 bearer token) to a valid actor and then further to a valid Private Key with which to sign the remote request. After that the only thing remaining is to pipe verbatim the received response to the client...

@steveSteve Bate @smallcircles🫧 socialcoding.. @evanEvan Prodromou

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