Fair solutions on Datnoid. There are 3 different ways to launch a token on Datnoid. Random Selection, FCFS, or instant launch. Random Selection The pre orders are shuffled and executed in the new random order. If you are the last person to preorder, you still have a chance of getting the first buy (best price quote). First Come First Served No shuffling and the earlier you are, the better price quote you will receive. Instant Launch Skip the scheduling entirely and as soon as you create your token it is available for anyone and everyone to start swapping. When viewing the pre orders tab on a token, it will display which type of launch the dev chose. Regardless of the launch type, being one of the first to place a preorder will earn you the most points.
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How does Fair Launch System work on Datnoid? There are 3 different ways to launch a token on Datnoid- Random selection, FCFS, or instant launch. Random Selection The pre orders are shuffled and executed in the new random order. If you are the last person to preorder, you still have a chance of getting the first buy (best price quote). First Come First Served No shuffling and the earlier you are, the better price quote you will receive. Instant Launch Skip the scheduling entirely and as soon as you create your token it is available for anyone and everyone to start swapping. When viewing the pre orders tab on a token, it will display which type of launch the dev chose. Regardless of the launch type, being one of the first to place a preorder will earn you the most points.
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Hello, Just wrapped up a project utilizing Room database, where I seamlessly executed CRUD operations in a To-Do application. Additionally, I explored Shared Preferences, implementing a simple yet effective login and signup feature. Can't wait to leverage these skills in future projects! #RoomDatabase #CRUD #AndroidDev #SharedPreference #LearningAndGrowing
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Hey Dev Community! 👋 Just merged a PR (#696) into the BlueBubbles Server that I'm pretty excited about, fixing a persistent issue with missed notifications. 🔔 The core problem was two-fold: file change events weren't being handled consistently, and the polling logic was susceptible to time drift. This led to delays and sometimes, missed messages altogether. 😬 My solution involved a few key changes: Timestamp Normalization: I introduced logic to ensure timestamps always fall within a 24-hour window, preventing massive data fetches and server strain. Basically, prevTime is now adjusted if it's too far in the past. Drift Compensation: Added a 30-second subtraction from timestamps (prevTime - 30000) to account for potential time drift between systems. This catches more edge cases where events might be missed by a few seconds. ⏱️ Cache Pruning: Implemented a call to cache.trimCaches() to keep the cache lean and mean, ensuring faster operations. 🧹 Why is this important? Well, reliable and timely notifications are critical for a seamless messaging experience! Users should now see significantly fewer missed messages and a generally more responsive server. This was a fun challenge that involved diving deep into event handling and timestamp manipulation. Proved once again how crucial precise time management is! 💪 Got a recent coding win you're proud of? Share it below! 👇 #CodingSolutions #TechDeepDive #BlueBubblesDev #NotificationFix #OpenSourceContribution
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🟢 Titan Storage: New Version Launch Celebration! We are ready to introduce the latest version of Titan Storage, designed to deliver an exceptional user experience and unmatched data security. Here’s what’s new: 📍 New Version Highlights — Redesigned Interface: Enjoy a seamless and intuitive user experience! — No Registration Required: Use anonymously for enhanced privacy protection. — Private Sharing Feature: Share your data securely with ease. — Customizable Storage Regions: Flexible data management tailored to your needs. 📍 Introducing the New Titan Storage Developer Center — Explore these powerful features for developers: — API Documentation: Comprehensive guides to streamline service integration. — SDK Downloads: Ready-to-use SDKs for JavaScript and Go to simplify development. — Code Examples: Practical examples to help you get started quickly. — Developer Forum: Connect, share insights, and find solutions with the community. — We deeply appreciate your continued support for Titan Storage and can’t wait to hear your thoughts on the new version! Experience the upgrades and explore the new features today!
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I added a regular proxmox module for normal VM deployment using cloudinit. This module utilizes count for a more efficient module declaration. #terraform #proxmox #cloudinit #homelab
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From a QuestDB user on Slack: "Just upgraded to 8.2.2, getting massive perf improvements for this query, used to take 3-5s; now its ~20-30ms." 🤯 Beyond this ~250x speedup, #QuestDB 8.2.2 brings: ✔️ Real-time ingestion charts in the Web Console ✔️ TTL for automatic data retention ✔️ Query Tracing for debugging ✔️ LAG/LEAD window functions (Moving Averages, etc.) ✔️ DECLARE SQL syntax …and more! We’re excited for what’s next: Materialized Views are coming in QuestDB 8.3. Stay tuned! 💥
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When you write a high-performance database, you have to focus on small performance improvements here and there—they eventually add up. Our latest release, 8.2.2, comes with new features, bug fixes, and maintenance patches, but it wasn’t specifically about performance improvements. Yet, just a few minutes after announcing the new version in our Slack channel, one of our users reported huge performance gains for a specific query. We traced it back to a new optimization introduced in this version—one we hadn’t even mentioned in the release blog post. And for this particular use case, it turned out to be a game changer. It goes to show that excellence isn’t always about big changes, but about incremental improvements and a continuous focus on performance, even in the small, everyday commits. #questdb #timeseries #database
From a QuestDB user on Slack: "Just upgraded to 8.2.2, getting massive perf improvements for this query, used to take 3-5s; now its ~20-30ms." 🤯 Beyond this ~250x speedup, #QuestDB 8.2.2 brings: ✔️ Real-time ingestion charts in the Web Console ✔️ TTL for automatic data retention ✔️ Query Tracing for debugging ✔️ LAG/LEAD window functions (Moving Averages, etc.) ✔️ DECLARE SQL syntax …and more! We’re excited for what’s next: Materialized Views are coming in QuestDB 8.3. Stay tuned! 💥
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Recently, I was working building in-memory cache and after some research, I decided to go with BadgerDB (a key-value store built in Go) because it allows for easy switching between in-memory and disk storage. The real surprise came when I started testing which data format would be the fastest for serialization/deserialization. For simplicity, I chose to focus on MessagePack and Gob. HashiCorp offers a solid package for handling MessagePack encoding/decoding, and I was blown away by how fast it was while keeping memory usage impressively low—staying under 5 allocations per byte
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It only takes one errant statement to drown your production logs in a sea of debug messages. Excessive noise in logs increases storage costs and complicates troubleshooting. With Datable.io, you can filter on any property with a single line of JavaScript. Check out our new recipe for filtering out debug logs!
Filter Logs
docs.datable.io
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Serverpod 2.2, code-named "Futurism," is now out. 🚀 It brings a fully featured testing framework plus two cool experimental features. 🧪 Links below. ⬇️ 📺 Keynote: https://lnkd.in/dPX5Jjcd ✍️ Blog post: https://lnkd.in/dwiPSheJ
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