Rockstar's long-awaited Grand Theft Auto VI is launching November 19th, 2026 for PlayStation 5 and Xbox Series S/X consoles. The game will be available digitally at launch, with physical cases containing codes, not discs, so your options for preordering are straightforward. The preloading phase for the game begins on November 12th, which should give you […]

I’m building Euro Toolhub , a German-first index of European software, SaaS, cloud and AI alternatives. The idea is simple: many companies, agencies, developers and privacy-conscious users want alternatives to common tools when they care about things like data residency, open source, self-hosting, European jurisdiction or reducing dependency on non-European providers. But most existing lists stop at listing tools. I want Euro Toolhub to go one step further. Each provider profile can include: country and jurisdiction category alternative-to mappings open source status self-hosting availability EU data residency DPA availability certifications where known target audience strengths and limitations a transparent sovereignty score embeddable badges for providers The project starts in German because the first target market is DACH, but the structure is prepared for more languages later. The long-term vision is to build a practical decision platform for digital sovereignty: not just “which European alternatives exist?”, but “which one fits my actual use case?” Current categories include web analytics, cloud and hosting, newsletter tools, CRM, email, password managers, AI APIs, project management, video conferencing and e-signatures. I’m looking for feedback from developers, SaaS founders, privacy people and self-hosting communities: Which European tools should be added? Which categories matter most? What would make a sovereignty score trustworthy? Should the provider dataset be opened through GitHub for corrections and submissions? Project: https://www.euro-toolhub.eu/de Provider submission: https://www.euro-toolhub.eu/de/anbieter-eintragen ``

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Not gonna lie, this is my current vision of software engineering today. submitted by /u/DaemonBatterySaver [link] [留言]

Slides have an odd status in engineering: we make them constantly, but we treat them as disposable. They rarely live in a repo. They rarely go through review. The diagram you spent twenty minutes aligning in Keynote is gone the moment the talk ends. Dinghy's Slide Builder treats a slide like any other artifact: a folder of source files that compiles to a single deliverable. What it is A presentation builder layered on top of RevealJS , wired into the same Dinghy CLI you already have: YAML DSL: recognized keys map to semantic blocks, and any other key becomes the matching HTML element, so you describe slides in a structured, indented form. Markdown and HTML, auto-loaded: drop a .md or .html file in the slide folder and it becomes a section. Self-contained HTML output: assets inlined, a single file you can share or host anywhere. Live reload dev server: run dinghy slide start and edit-to-reload feedback. Prezi-style zoom and pan: exclusive to Dinghy, covered below. A YAML slide The core idea is that a slide is a tree of HTML elements, and YAML is a tidy way to describe nested structure: sections : - badge : Show Case title : Slide Builder subtitle : author RevealJS presentations in YAML ul : li : - YAML DSL maps keys to HTML elements - Self-contained HTML output - Live reload development server Some keys are recognized aliases: badge becomes <div class="badge"> , title becomes <h2 class="title"> , subtitle becomes <p class="subtitle"> . Any other key, such as p , h3 , ul , or li , becomes that HTML element directly. Multi-file slides are just multiple YAML files in the same folder, picked up in filename order. A Markdown slide If you want to add a section quickly, plain Markdown works: ## Slide Builder - YAML DSL maps keys to HTML elements - Self-contained HTML output - Live reload dev server Markdown files become slides automatically. You can mix YAML, Markdown, and raw HTML in the same slide and use whichever fits each section. The single-file output Run dinghy slid

Here's a bug that looks impossible until you understand Gson. You have this data class in your Pokedex app: data class PokemonStat ( @SerializedName ( "base_stat" ) val baseStat : Int , val stat : StatInfo ) A teammate cleans up the code and deletes what looks like a redundant line: data class PokemonStat ( val baseStat : Int , // @SerializedName removed val stat : StatInfo ) It compiles . No red errors. He runs the app — and every Pokemon's baseStat is 0 . Not the real 45 or 49. Just 0 . Everywhere. And Gson never threw an error, never logged a warning, never said a single word. If you can explain why this happens, you understand Gson better than most juniors. This is also a favorite interview question. Let's break it fully. What Gson actually does When the JSON comes back from the server, Gson goes key by key: Read a key from the JSON — say base_stat . Look for a Kotlin property with the exact same name . Found it? Pour the value in. Not found? Leave that property at its default value and move on. That's the entire matching game — exact name match, or nothing. Now look at the "cleaned up" class. The JSON key is base_stat . The Kotlin property is baseStat . Those are not the same string . Gson looks for a property called base_stat , doesn't find one, shrugs, and leaves baseStat at its default. The default for an Int is 0 . That's your bug. @SerializedName("base_stat") was never redundant. It was the sticky note telling Gson: "this property is called baseStat in Kotlin, but look for base_stat in the JSON." Delete the note, and Gson stops matching. Two ways to fix it: Rename the property to base_stat — works, but breaks Kotlin's camelCase convention. Put @SerializedName("base_stat") back — keeps the clean name and matches. This is the right one. But why 0 ? Why not a crash? This is the part that surprised me. A missing field feels like it should be an error. It isn't. Gson treats a missing key as allowed . It builds your object, fills the fields it found, and leaves

Note: If you're new to execution calculations, I'd recommend starting with my previous post which covers them in detail, then coming back here. What is attribute capturing and why would you use it Attribute capturing refers to directly exposing certain attributes to your execution calculation from attribute sets, to be used in execution calculations. Capturing attributes lets you handle things like damage in a more complex way. So for example, you could have advantages and weaknesses against certain damage types, or an attribute like armor that should reduce incoming damage. This is just two use cases, but once you learn how to do it, you should naturally be able to see in what other ways they can be used. In this example, I will show how to get attribute magnitude from captured attributes and using them in calculations, which is the most common way of using captured attributes. Capturing attributes Defining the struct, declaring and defining attribute capture definitions In this post, I will show how to use a static struct to access all your captured attributes, as a good performance-aware solution. You are also free to choose not to use the struct. For the struct approach, the first step is to go to the .cpp of the execution calculation, and define your struct there. In the struct, we first use the DECLARE_ATTRIBUTE_CAPTUREDEF() macro, passing in the name of your attribute. After that, we make the constructor of the struct, and in the constructor we use the DEFINE_ATTRIBUTE_CAPTUREDEF() macro, passing in the attribute set that has the attribute, the attribute from it, whether the attribute from the Target or Source should be used (the Target is the ASC the ExecCalc is outputting its result to, and the Source is the ASC that called it), and a bool for if the captured attribute should be snapshotted (if the attribute should be frozen at ExecCalc GE application (snapshotted) or if the value should be read at execution time). In my case, I will show 2 examples of non-

Installing Ubuntu Server 24.04 LTS in an offline mode (no LAN cable or WiFi connected) leaves you with an unmanaged network interface which requires manual configuration post-install. The interface enp4s0 is unmanaged by systemd-networkd and also the service itself is disabled. NOTE: This guide applies to Ubuntu server. On Ubuntu desktop you have the NetworkManager service installed and the steps would be different. To fix the problem follow the steps below: Create a Brand New Netplan Configuration File Look into /etc/netplan . You will probably see the dir is empty. This means the installer completely gave up on configuring the network and didn't create any profiles. Create a new file, e.g. vim /etc/netplan/01-netcfg.yaml . Paste the following configuration network : version : 2 renderer : networkd ethernets : enp4s0 : dhcp4 : true This makes the interface managed by networkd instead of the desktop NetworkManager. Fix permissions The new file needs to be readable only by root so fix it's permissions chmod 600 /etc/netplan/01-netcfg.yaml . Enable network service Enable the network service and make it start on boot: systemctl enable systemd-networkd systemctl start systemd-networkd Run netplan Finally, we need to tell Ubuntu to use our new configuration and activate the network netplan generate netplan apply Network should be up! ip a

Episode 1/4 of the mini-series The week Supabase lied to me 4 times . The three following episodes cover a mutation silently swallowed by the SDK [CANONICAL URL EPISODE 2: to fill in after push], an RLS recursion resolved by a JWT hook [CANONICAL URL EPISODE 3: to fill in after push], and a query that stops at exactly 1000 rows without saying so [CANONICAL URL EPISODE 4: to fill in after push]. The Tuesday the security probe spoke It's 9:12am on a Tuesday in May. The daily drift probe has been running automatically for three weeks — an aclexplode query across all public objects, filtered on anon . I don't open it every morning. That morning, it's waiting for me with a row that has no business being there. Niran sets a coffee on the corner of my desk without a word. He reads the output over my shoulder. A PII backup table — personal data in plaintext, created two days earlier for a bulk reclassification — shows up in the list with SELECT , INSERT , UPDATE , DELETE granted to anon . Accessible to any unauthenticated curl request. He lets three seconds pass and says: "It's not RLS." Then he goes back to his hoodie. He's right. It's not an RLS bug. The table itself is open, at the GRANT layer, before RLS even applies. Three objects, three doors, one mechanism That week, I realize I'm not dealing with an isolated incident. Three distinct objects, in three different migrations, each open a door nobody thought they'd opened. The backup table first. Then a policy set TO public because the public landing page needs it, which lets a POST {} from anon through with an HTTP 400 NOT NULL response instead of 401 Unauthorized . And finally four SECURITY DEFINER functions written to execute transactional operations with their owner's privileges, all invocable by anon because EXECUTE defaults to TO PUBLIC at CREATE time. Three objects, three superficially distinct mechanisms, yet one shared root. At every CREATE , Postgres completes the migration with an implicit GRANT the author nev