Show HN: Open-Source Pong Game https://ift.tt/WZj83x9

Show HN: Open-Source Pong Game Need feedback on this game folks! I'm open to any contributions and opinions! https://ift.tt/D5WrZMk February 4, 2024 at 11:05PM

Show HN: Aidely is AI powered thread; AI and Humans cooperation https://ift.tt/3M8tXpo

Show HN: Aidely is AI powered thread; AI and Humans cooperation Discover the future of community engagement with our iPhone app. Seamlessly blend human creativity with AI prowess as users collaborate with ChatGPT, Bard, and Llama to spark captivating threads and discussions. Join us in shaping the next frontier of content creation. https://www.aidely.io/ February 4, 2024 at 08:18PM

Show HN: USD 0.99/TB/month cloud storage https://ift.tt/m2hgP0y

Show HN: USD 0.99/TB/month cloud storage https://ift.tt/9WDMJZ7 February 4, 2024 at 07:46PM

Show HN: Unofficial Google Lens OCR API https://ift.tt/3GEoUYa

Show HN: Unofficial Google Lens OCR API Default OCR in ShareX is pretty bad, so I reverse-engineered Lens API and made a library to call unofficial Lens API and made a script for ShareX to OCR the captured region. URL points to library I've made, there's a tutorial for ShareX in separate file: https://ift.tt/WjxCTSv... https://ift.tt/15KF2yP February 4, 2024 at 05:38PM

Show HN: A Python PDF Form Library https://ift.tt/3LzPHgm

Show HN: A Python PDF Form Library Hi HN! I have a project that I have been working on for three years that I’d love to show you today called PyPDForm ( https://ift.tt/ptmB5ZI ). It is a Python library that specializes in processing PDF forms, with the most outstanding feature being programmatically filling a PDF form by simply feeding a Python dictionary. I used to work at a startup company with Python as our backend stack. We were constantly given paper documents by our clients that we needed to generate into PDFs. We were doing it using reportlab scripts and I quickly found the process tedious and time consuming for more complex PDFs. This is where the idea of this project came from. Instead of writing lengthy and unmaintainable reportlab scripts to generate PDFs, you can just turn any paper document into a PDF form template and PyPDFForm can fill it easily. On top of the GitHub repo, here are some additional resources for this project: PyPi: https://ift.tt/o7IFetV Docs: https://ift.tt/BSlYhz9 A public speak I did about this project: https://www.youtube.com/watch?v=8t1RdAKwr9w I hope you guys find the library helpful for your own PDF generation workflow. Feel free to try it, test it, leave comments or suggestions, and open issues. And of course if you are willing, kindly give me a star on GitHub. https://ift.tt/ptmB5ZI February 4, 2024 at 06:55AM

Show HN: Reusable components with Django and HTMX https://ift.tt/fJXxLlh

Show HN: Reusable components with Django and HTMX https://ift.tt/AxYhq4w February 2, 2024 at 07:52PM

Show HN: An open source performance monitoring tool https://ift.tt/rQvg1c9

Show HN: An open source performance monitoring tool Hey HN. We’re Jay and Vadim from Highlight.io ( https://highlight.io ). We’re building an open source [1] monitoring platform for web applications. Today we’re excited to be sharing a performance tool we’ve been working on, which helps you inspect the latency of code execution from the client to the server. As engineers at past startups, we often had to debug slow queries, poor load times, inconsistent errors, etc... While tools like Jaegar [2] helped us inspect server-side performance, we had no way to tie user events to the traces we were inspecting. In other words, although we had an idea of what API route was slow, there wasn’t much visibility into the actual bottleneck. This is where our performance product comes in: we’re rethinking a tracing/performance tool that focuses on bridging the gap between the client and server. What’s unique about our approach is that we lean heavily into creating traces from the frontend. For example, if you’re using our Next.js SDK, we automatically connect browser HTTP requests with server-side code execution, all from the perspective of a user. We find this much more powerful because you can understand what part of your frontend codebase causes a given trace to occur. There’s an example here [3]. From an instrumentation perspective, we’ve built our SDKs on-top of OTel, so you can create custom spans to expand highlight-created traces in server routes that will transparently roll up into the flame graph you see in our UI. You can also send us raw OTel traces and manually set up the client-server connection if you want. [4] Here’s an example of what a trace looks like with a database integration using our Golang GORM SDK, triggered by a frontend GraphQL query [5] [6]. In terms of how it's built, we continue to rely heavily on ClickHouse as our time-series storage engine. Given that traces require that we also query based on an ID for specific groups of spans (more akin to an OLTP db), we’ve leveraged the power of CH materialized views to make these operations efficient (described here [7]). To try it out, you can spin up the project with our self hosted docs [8] or use our cloud offering at app.highlight.io. The entire stack runs in docker via a compose file, including an OpenTelemetry collector for data ingestion. You’ll need to point your SDK to export data to it by setting the relevant OTLP endpoint configuration (ie. environment variable OTEL_EXPORTER_OTLP_LOGS_ENDPOINT [9]). Overall, we’d really appreciate feedback on what we’re building here. We’re also all ears if anyone has opinions on what they’d like to see in a product like this! [1] https://ift.tt/nBXmbdD [2] https://ift.tt/XSNLRg1 [3] https://ift.tt/LGZFPaf... [4] https://ift.tt/PushfQc... [5] https://ift.tt/NXGChug [6] https://ift.tt/DnGOrHU... [7] https://ift.tt/NJmLIv9 [8] https://ift.tt/nj9fRFc... [9] https://ift.tt/6MJmBZj... https://ift.tt/0Piv4yg February 1, 2024 at 09:02PM