标签：#ev

This was my very first side project 3 years ago. I guess I have a soft spot for it, because this is actually my 3rd time completely rewriting it from scratch. The new version turns flat scanned PDFs into searchable files, or converts photos of text into editable Word docs. It runs client-side for privacy (except for ai features), and the core OCR features are completely unlimited (no account required). → https://olocr.com submitted by /u/Embarrassed_Ad719 [link] [留言]

Hi everyone, I want to verify if I'm missing anything. I am making a small restaurant website and I want to make it comply with German GDPR. I notice there are solutions like Cookiebot. I was wondering if we can make all of the compliance stuffs by ourselves, or if these 3rd party solutions have something superior that we cannot execute on our own? Thanks submitted by /u/leon8t [link] [留言]

https://cityknow.vercel.app Whenever I look up a city in Google Maps, I mostly see only the same touristic landmarks. However, I wanted to know what the actual city looks like, like the neighbourhoods, side streets, the mundane stuff. So I built CityKnow. You search a city, and get a grid of random street-level images arranged by distance from the center (inner rings show the core, outer rings show the suburbs). Would love any feedback! submitted by /u/BarisSayit [link] [留言]

This is a submission for the GitHub Finish-Up-A-Thon Challenge What I Built pq — jq for Parquet. A 50 MB Rust single binary that wraps DuckDB's query engine in a jq-style expression DSL, optimized for terminal one-liners and unix pipes. $ pq sales.parquet 'group_by .country | sum .revenue | top 3 by sum_revenue' ┌─────────┬─────────────┐ │ country ┆ sum_revenue │ ╞═════════╪═════════════╡ │ US ┆ 19065.00 │ │ FR ┆ 999.99 │ │ DE ┆ 312.00 │ └─────────┴─────────────┘ Where it started. I work in adtech. I look at parquet files dozens of times a day — campaign deliveries, partner exports, audience snapshots. Every existing option was painful: Tool Pain pyarrow / pandas 5-second cold start, 200 MB virtualenv parquet-tools JVM, slow, no query support pqrs Inspector only — can't filter or project duckdb CLI Great engine, but SELECT email FROM 'file.parquet' WHERE country='US' is too verbose to type 50 times a day Spark Are you serious pq is the tool I actually want — single binary, no JVM, no Python, jq-style syntax for piping into the rest of the unix toolbox. It's been my default cat for parquet since v0.5. Demo Repo : github.com/thehwang/parq Latest release : v0.14.0 (this submission) Install : brew install thehwang/parq/pq Tutorial : doc/tutorial.md — 30-minute hands-on walkthrough A taste of what shipped in v0.14: # Streaming JSON output (was the only buffered format until v0.14) $ pq big.parquet '.id, .country' -o json | head -c 200 # returns instantly even on a 40 GB file # Schema-drift gate for CI $ pq diff baseline.parquet candidate.parquet # Schema diff - a: ` baseline.parquet ` - b: ` candidate.parquet ` ## Added (1) | column | type | nullable | |-----------|---------|----------| | ` country ` | VARCHAR | yes | $ echo $? 1 # exits non-zero on drift, slots into CI without scripting And the new TUI Explain panel — press capital E for EXPLAIN ANALYZE , get row-group pruning per scan (this is exactly the panel you see on the cover image at the top of this post): Expla

The role is Junior software engineer, nextjs and python. Fully remote and the interview is online. I'm confident I can deliver but I'm not so confident I can do good enough at the technical interview, if there will be one. I have more than a week to prepare. What are my options here? How can I not bomb the technical interview if they do one? Anything I can do to offset the damage? submitted by /u/Shahadat__ [link] [留言]

https://preview.redd.it/fa5yz70xka4h1.jpg?width=1080&format=pjpg&auto=webp&s=4d13acefd4e2a21999756d282c21b342e96136b3 Recently added a small fun feature on my portfolio's about page, a "Summon bok" button that unleashes a horde of lil boks, you can drag and play play with it. She clearly approved the final result if anyone wants to summon her themselves (you can drag n play) https://thevaibhav.co/about submitted by /u/BuriBuriZaymon [link] [留言]

I wanted to build a build a game, but this time, instead of implementing an existing game I tried to make something unique, without reinventing the wheel: memory mahjong . Initially, I started with a more ambitious project, with more complex mechanics that seemed to take ages, so I said, first I'll shift towards something that I can finish fast but focusing on polishing and simple mechanics. So I took the simplest idea and make it more playable. A memory game combined with mahjong tiles. So, I used mahjong tiles and made the matching rules more interesting: Tiles can match by number across different suits, not just identical pairs Dragon tiles clear as a set of three Flower tiles act as wilds 4 different board layouts so each round feels a bit different It's still a memory game at its core but there's more to think about than just remembering positions. Build with React and then made into a NextJs site. submitted by /u/quantotius [link] [留言]

As handheld consoles continue to grow and push the limits of what you can actually hold in your hands, the Arduboy FX-C comes in a refreshingly pocketable package. It manages to squeeze the best features of past models and some welcome upgrades into a handheld that’s still no larger or thicker than a few credit […]

I live in a part of Los Angeles where I feel safer bringing pepper spray on walks. The problem is, I don't always remember to bring it with me, and it's not legal to carry it everywhere I go. Pebblebee's $59.99 Halo Bluetooth tracker surprised me by being a suitable replacement because it doubles as […]

submitted by /u/veroz [link] [留言]

I'm building a webapp that converts location text into geo co-ordinates. Google's APIs works great and I doubt I would go beyond the USD200 free credits each month. However, I am not keen to have a postpaid commitment since there is no guarantee that I won't go above USD200. There does not seem to be a way to set any global limits on spending in Google Cloud either. I prefer something that is on a prepaid model like how OpenAI or Claude does it. submitted by /u/sonomodata [link] [留言]

hey guys, i’ve been frustrated for a while by how bloated and ad-heavy existing wheel fitment databases are. if you’ve ever tried to look up a simple bolt pattern or offset, you know the pain: 3 trackers, 5 pop-ups, and a database that looks like it was built in 2005. so i decided to build a "zero-bloat" alternative: https://boltpatternhq.com/ the core challenge here wasn't the AI part—it was the data structure. i needed to map 10,000+ vehicles with PCD, center bore, and offset specs in a way that was instantly searchable but didn’t require a massive backend hit. a few technical details for those curious: architecture: the site is served as a pure static frontend (html/css/js). no backend, no server maintenance. search: i’m using a pre-computed client-side search index (json-based) for the auto-complete. it’s instant, local-first, and keeps the search experience snappier than any backend call. ai integration: this is the fun part. i'm using cloudflare workers ai to run the models directly at the edge. it avoids all the typical "openai wrapper" latency and cost issues. the model is constrained specifically to my structured database, which helps keep the fitment advice precise and prevents it from hallucinating wildly. it’s still a work in progress, but the goal was to create something "utility-first" for car guys who just want the specs without the tracking trash. i'm currently looking for feedback on the ux of the search widget and the load performance. does the search feel snappy enough on your side? would love to hear what you guys think about the tech stack. submitted by /u/SideQuestDev [link] [留言]

I have been thinking a lot about coding agents lately. Not really about whether they can write good code, because usually they can, sometimes they can't. That part is obvious. But the risk is shifting from wrong answers to wrong outcomes. The part that feels more important to me is this: should the agent actually own the write authority? We already don't trust humans without roles, limits, reviews, and accountability. Developers use PRs, pilots use checklists, bank clerks have transfer limits. Capable agents need the same structure, but machine-readable. Right now a lot of setups still look roughly like this: agent reads the repo agent decides what to change agent has a GitHub token agent creates commits, branches, or PRs I don't think this is the right default. The agent can reason. The agent can inspect files. The agent can propose changes. But the moment it can directly create external impact, the problem changes. It is no longer just: did the agent say something wrong? It becomes: did the agent create the wrong outcome? That is a much more expensive failure mode. Intent is not authority The pattern I like more is simple: agent reads directly agent proposes intent a boundary decides an adapter materializes only admitted work So the agent does not get the write credentials. It submits a structured intent instead, which could look like: { "operation" : "write" , "target" : { "repo" : "example/app" , "branch" : "main" , "path" : "docs/config/agent-policy.md" }, "source_state" : { "blob_sha" : "8f31c2..." }, "requested_effect_hash" : "sha256:..." } This is then not a command anymore, it is a suggestion, or an intent. The system still has to decide whether this proposed outcome should exist. That decision layer can check things like: is this actor allowed? is this repo allowed? is this path in scope? does the source state still match? is this operation allowed? was the same effect already created? should this become a reviewable PR? Only after that should there be an

I'll keep this brief. Most of us can write great code. The harder part? Finding clients who actually pay well and don't ghost you after the first message. I struggled with that for a long time. Then a few weeks ago, something clicked - and the two platforms that changed everything for me were LinkedIn and Reddit. Here's why they work: 🔹 LinkedIn - Real people with real budgets post here. It's less about cold outreach and more about being present and visible. Set up your alerts, keep your profile sharp, and let opportunities come to you. Patience pays off. 🔹 Reddit - Underrated, honestly. Yes, the lead volume is lower, but the quality is surprisingly solid. People posting in relevant subreddits are often genuine and ready to hire. Bonus: no geo-restrictions, so you're playing in a global market from day one. The secret sauce? Be in the right subreddit at the right time. That's genuinely it. If you've been sleeping on either of these platforms, give them a real shot. You might be closer to consistent freelance work than you think. submitted by /u/theonlyaswin [link] [留言]

I really like the look of Bootstrap v2, but it is ancient. It does not use flexbox, customizing it nowadays is more difficult… Of course, using Bootstrap v2 for a serious project now would be laughable. Design trends are just too different today. But I need something like Bootstrap v2 for a personal project, maybe used by at most a dozen people. submitted by /u/AwwThisProgress [link] [留言]

In November 2023 we ran our first global Hytale servers on Google Kubernetes Engine using Veltrix 3.2 as our configuration orchestrator. The Treasure Hunt Engine—a service that fans spawn to claim event loot—started crashing every time search volume exceeded 12 k RPM. Grafana showed a steady climb of 503 errors on /hunt/claim until the autoscaler maxed out at 32 G1 CPU cores and still couldnt keep up. Operators kept filing tickets that boiled down to one sentence: We click the map, nothing happens. We never saw the actual error because the ingress controller was swallowing it and returning a generic Too many requests. What we tried first (and why it failed) Our first move was to crank up the nginx-ingress-controller replicas from 3 to 12 and switch the load-balancer tier from GKE Standard to Premium. The 503 rate dropped to 8 k RPM, but now the p99 latency on claims spiked from 80 ms to 420 ms. The culprit was a recursive call in the hunt service: every claim required a round trip to the player-profile service to validate tier eligibility, and that service was on a shared Postgres 15.4 cluster with 3 k TPS of unrelated traffic. The error stack in Jaeger was literally tracing_id=7f3a1c8… server=profile-db pool_timeout . We tried adding connection pooling with PgBouncer, but the hunt service was using raw libpq and refused to reuse connections—no matter how many times we told it. The Architecture Decision We ripped the validation out of the synchronous path and made the hunt engine publish an event called HuntTierCheckRequired to a dedicated Kafka topic player-events-tier . The hunt service would respond to the client with a 202 Accepted immediately, then the loot-claim worker would listen to that topic and, if the tier passed, publish HuntLootReady . The worker ran in the same pod but on a separate goroutine with a 60-second TTL so we didnt leak memory if the tier service hung. We moved the player-profile service to an SSD-backed CloudSQL instance and gave it 32 GB R

<form action= "https://bank.com/transfer" method= "POST" > <input name= "to" value= "attacker" > <input name= "amount" value= "10000" > </form> <script> document . forms [ 0 ]. submit () </script> Five lines of HTML on a malicious page. When a user who's logged into bank.com in another tab visits this page, the browser auto-submits the form, attaches their session cookie, and ten thousand dollars leave their account. They didn't click anything. The malicious site didn't see their password. There was no XSS, no breach, no leak in the traditional sense. The browser did exactly what it was designed to do. That's CSRF — Cross-Site Request Forgery — and it's been the classic "confused deputy" attack on the web for two decades. Let's walk through what makes it work, why CORS doesn't help, and the one cookie flag that mostly killed it around 2020. Why the browser attaches your cookie to that request Cookies belong to a domain. When you log into bank.com , the bank sets a session cookie in your browser: Set-Cookie: session=abc123; HttpOnly From that point on, every single request your browser sends to bank.com carries that cookie. Every page load. Every API call. Every image fetch. The browser does it automatically, without asking, and regardless of who triggered the request. That last word is the door CSRF walks through. The browser attaches the cookie based on where the request is going , not where it came from . So when evil.com triggers a POST to bank.com/transfer , the browser sees a request destined for bank.com , looks up the cookies for bank.com , and attaches them. As far as the bank's server can tell, the request looks exactly like one the user submitted from inside the bank's own page. This is the "confused deputy" idea. Your browser is the deputy. It has authority on your behalf (your cookies). And it's been tricked into using that authority for someone else's benefit. The server has no way to tell the difference, because from its point of view, there isn't one.

Live app: https://layoffs.kadoa.com Data and code are open source: https://github.com/kadoa-org/layoffs-tracker The federal WARN Act requires employers with 100+ workers to give 60 days notice before mass layoffs or plant closings (different thresholds by state, but roughly 50+ jobs lost). But the notices are scattered across 50 state websites, each with its own format, broken links, and no API. I think this should be transparent and easy-to-access public data, so I built an open-source aggregator for it. submitted by /u/madredditscientist [link] [留言]

submitted by /u/rebane2001 [link] [留言]