The best Hacker News stories from Show from the past day
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Show HN: OpenTimes – Free travel times between U.S. Census geographies
Hi HN! Today I'm launching OpenTimes, a free database of roughly 150 billion pre-computed, point-to-point travel times between United States Census geographies. In addition to letting you visualize travel isochrones on the homepage, OpenTimes also lets you download massive amounts of travel time data for free and with no limits.<p>The primary goal here is to enable research and fill a gap I noticed in the open-source spatial ecosystem. Researchers (social scientists, economists, etc.) use large travel time matrices to quantify things like access to healthcare, but they often end up paying Google or Esri for the necessary data. By pre-calculating times between commonly-used research geographies (i.e. Census) and then making those times easily accessible via SQL, I hope to make large-scale accessibility research cheaper and simpler.<p>Some technical bits that may be of interest to HN folks:<p>- The entire OpenTimes backend is just static Parquet files on R2. There's no RDBMS or running service. The whole thing costs about $10/month to host and is free to serve.<p>- All travel times were calculated by pre-building the inputs (OSM, OSRM networks) and then distributing the compute over hundreds of GitHub Actions jobs.<p>- The query/SQL layer uses a setup I haven't seen before: a single DuckDB database file with views that point to static Parquet files via HTTP.<p>Finally, the driving times are optimistic since they don't (yet) account for traffic. This is something I hope to work on in the near future. Enjoy!
Show HN: OpenTimes – Free travel times between U.S. Census geographies
Hi HN! Today I'm launching OpenTimes, a free database of roughly 150 billion pre-computed, point-to-point travel times between United States Census geographies. In addition to letting you visualize travel isochrones on the homepage, OpenTimes also lets you download massive amounts of travel time data for free and with no limits.<p>The primary goal here is to enable research and fill a gap I noticed in the open-source spatial ecosystem. Researchers (social scientists, economists, etc.) use large travel time matrices to quantify things like access to healthcare, but they often end up paying Google or Esri for the necessary data. By pre-calculating times between commonly-used research geographies (i.e. Census) and then making those times easily accessible via SQL, I hope to make large-scale accessibility research cheaper and simpler.<p>Some technical bits that may be of interest to HN folks:<p>- The entire OpenTimes backend is just static Parquet files on R2. There's no RDBMS or running service. The whole thing costs about $10/month to host and is free to serve.<p>- All travel times were calculated by pre-building the inputs (OSM, OSRM networks) and then distributing the compute over hundreds of GitHub Actions jobs.<p>- The query/SQL layer uses a setup I haven't seen before: a single DuckDB database file with views that point to static Parquet files via HTTP.<p>Finally, the driving times are optimistic since they don't (yet) account for traffic. This is something I hope to work on in the near future. Enjoy!
Show HN: OpenTimes – Free travel times between U.S. Census geographies
Hi HN! Today I'm launching OpenTimes, a free database of roughly 150 billion pre-computed, point-to-point travel times between United States Census geographies. In addition to letting you visualize travel isochrones on the homepage, OpenTimes also lets you download massive amounts of travel time data for free and with no limits.<p>The primary goal here is to enable research and fill a gap I noticed in the open-source spatial ecosystem. Researchers (social scientists, economists, etc.) use large travel time matrices to quantify things like access to healthcare, but they often end up paying Google or Esri for the necessary data. By pre-calculating times between commonly-used research geographies (i.e. Census) and then making those times easily accessible via SQL, I hope to make large-scale accessibility research cheaper and simpler.<p>Some technical bits that may be of interest to HN folks:<p>- The entire OpenTimes backend is just static Parquet files on R2. There's no RDBMS or running service. The whole thing costs about $10/month to host and is free to serve.<p>- All travel times were calculated by pre-building the inputs (OSM, OSRM networks) and then distributing the compute over hundreds of GitHub Actions jobs.<p>- The query/SQL layer uses a setup I haven't seen before: a single DuckDB database file with views that point to static Parquet files via HTTP.<p>Finally, the driving times are optimistic since they don't (yet) account for traffic. This is something I hope to work on in the near future. Enjoy!
Show HN: Quickly connect to WiFi by scanning text, no typing needed
I travel and work remotely a lot. Every new place—hotels, cafes, coworking spaces—means dealing with a new WiFi network. Sometimes there's a QR code, which is convenient, but usually, it's a hassle: manually finding the right SSID (especially frustrating when hotels have one SSID per room), then typing long, error-prone passwords.<p>To simplify this, I made a small Android app called Wify. It uses your phone's camera to capture WiFi details (network name and password) from printed text, then generates a QR code right on your screen. You can instantly connect using Google Circle to Search or Google Lens. You can also import an image from your gallery instead of using the camera.<p>Currently, it's Android-only since I daily-drive a Pixel 7, and WiFi APIs differ significantly between Android and iOS.
Play Store link: <a href="https://play.google.com/store/apps/details?id=com.yilinjuang.wify">https://play.google.com/store/apps/details?id=com.yilinjuang...</a><p>I'd appreciate your feedback or suggestions!
Show HN: My high school team’s space probe
Me and a few friends made this design document as part of our entry to the UK CanSat competition where a high school team is required to build a probe to be launched. The probe must serve some purpose, and ours was to map the temperature and pressure of the air at different altitudes.<p>We had the opportunity to launch it a week ago and you can find the video of our launch here: <a href="https://drive.google.com/file/d/16bsLzxjP7OWRqVvCB62cLv7QYLRWPKZK/view" rel="nofollow">https://drive.google.com/file/d/16bsLzxjP7OWRqVvCB62cLv7QYLR...</a><p>During the launch we reached 400m above sea level, and the can pulled 70gs successfully. The parachute and can stayed intact. Unfortunately, on the day, we were unable to successfully implement GPS.<p>The raw results are here: <a href="https://drive.google.com/file/d/1oK1vukjcNcsaXMAPeFlzZ66aHlRS0Vas/view" rel="nofollow">https://drive.google.com/file/d/1oK1vukjcNcsaXMAPeFlzZ66aHlR...</a>
And a slightly cleaned up version is here:<a href="https://drive.google.com/file/d/1xYhkp3sWoJF0bCkkvFs1AygSdLUHyrYp/view" rel="nofollow">https://drive.google.com/file/d/1xYhkp3sWoJF0bCkkvFs1AygSdLU...</a><p>I used my data presentation software to present our results here: <a href="https://drive.google.com/file/d/1-r7lT0J4MDLiYfuaasDXJsr5rCA1FNMD/view" rel="nofollow">https://drive.google.com/file/d/1-r7lT0J4MDLiYfuaasDXJsr5rCA...</a> The software (in the form of a python script to be executed in blender) can be found here: <a href="https://drive.google.com/file/d/1LHP7OwgI_O8t6-NBI0ZPn9JUt2GVgZEi/view" rel="nofollow">https://drive.google.com/file/d/1LHP7OwgI_O8t6-NBI0ZPn9JUt2G...</a> It's not pretty, but it works.<p>The differences in temperature and pressure results were exaggerated in the so that the gradient could be clearly seen.<p>Unfortunately, we did not get into the final (judged on this document) but it was an awesome experience nevertheless. The judges used this form to mark us: <a href="https://drive.google.com/file/d/1eZnum5zuJvkLzY7RLtm9A-NNzxwt_iO8/view" rel="nofollow">https://drive.google.com/file/d/1eZnum5zuJvkLzY7RLtm9A-NNzxw...</a> We would love to get any feedback from more experienced people, as we intend to do similar projects in the future and at least two of us want to be professional engineers. I'm happy to reply to any comments.
Show HN: My high school team’s space probe
Me and a few friends made this design document as part of our entry to the UK CanSat competition where a high school team is required to build a probe to be launched. The probe must serve some purpose, and ours was to map the temperature and pressure of the air at different altitudes.<p>We had the opportunity to launch it a week ago and you can find the video of our launch here: <a href="https://drive.google.com/file/d/16bsLzxjP7OWRqVvCB62cLv7QYLRWPKZK/view" rel="nofollow">https://drive.google.com/file/d/16bsLzxjP7OWRqVvCB62cLv7QYLR...</a><p>During the launch we reached 400m above sea level, and the can pulled 70gs successfully. The parachute and can stayed intact. Unfortunately, on the day, we were unable to successfully implement GPS.<p>The raw results are here: <a href="https://drive.google.com/file/d/1oK1vukjcNcsaXMAPeFlzZ66aHlRS0Vas/view" rel="nofollow">https://drive.google.com/file/d/1oK1vukjcNcsaXMAPeFlzZ66aHlR...</a>
And a slightly cleaned up version is here:<a href="https://drive.google.com/file/d/1xYhkp3sWoJF0bCkkvFs1AygSdLUHyrYp/view" rel="nofollow">https://drive.google.com/file/d/1xYhkp3sWoJF0bCkkvFs1AygSdLU...</a><p>I used my data presentation software to present our results here: <a href="https://drive.google.com/file/d/1-r7lT0J4MDLiYfuaasDXJsr5rCA1FNMD/view" rel="nofollow">https://drive.google.com/file/d/1-r7lT0J4MDLiYfuaasDXJsr5rCA...</a> The software (in the form of a python script to be executed in blender) can be found here: <a href="https://drive.google.com/file/d/1LHP7OwgI_O8t6-NBI0ZPn9JUt2GVgZEi/view" rel="nofollow">https://drive.google.com/file/d/1LHP7OwgI_O8t6-NBI0ZPn9JUt2G...</a> It's not pretty, but it works.<p>The differences in temperature and pressure results were exaggerated in the so that the gradient could be clearly seen.<p>Unfortunately, we did not get into the final (judged on this document) but it was an awesome experience nevertheless. The judges used this form to mark us: <a href="https://drive.google.com/file/d/1eZnum5zuJvkLzY7RLtm9A-NNzxwt_iO8/view" rel="nofollow">https://drive.google.com/file/d/1eZnum5zuJvkLzY7RLtm9A-NNzxw...</a> We would love to get any feedback from more experienced people, as we intend to do similar projects in the future and at least two of us want to be professional engineers. I'm happy to reply to any comments.
Show HN: My high school team’s space probe
Me and a few friends made this design document as part of our entry to the UK CanSat competition where a high school team is required to build a probe to be launched. The probe must serve some purpose, and ours was to map the temperature and pressure of the air at different altitudes.<p>We had the opportunity to launch it a week ago and you can find the video of our launch here: <a href="https://drive.google.com/file/d/16bsLzxjP7OWRqVvCB62cLv7QYLRWPKZK/view" rel="nofollow">https://drive.google.com/file/d/16bsLzxjP7OWRqVvCB62cLv7QYLR...</a><p>During the launch we reached 400m above sea level, and the can pulled 70gs successfully. The parachute and can stayed intact. Unfortunately, on the day, we were unable to successfully implement GPS.<p>The raw results are here: <a href="https://drive.google.com/file/d/1oK1vukjcNcsaXMAPeFlzZ66aHlRS0Vas/view" rel="nofollow">https://drive.google.com/file/d/1oK1vukjcNcsaXMAPeFlzZ66aHlR...</a>
And a slightly cleaned up version is here:<a href="https://drive.google.com/file/d/1xYhkp3sWoJF0bCkkvFs1AygSdLUHyrYp/view" rel="nofollow">https://drive.google.com/file/d/1xYhkp3sWoJF0bCkkvFs1AygSdLU...</a><p>I used my data presentation software to present our results here: <a href="https://drive.google.com/file/d/1-r7lT0J4MDLiYfuaasDXJsr5rCA1FNMD/view" rel="nofollow">https://drive.google.com/file/d/1-r7lT0J4MDLiYfuaasDXJsr5rCA...</a> The software (in the form of a python script to be executed in blender) can be found here: <a href="https://drive.google.com/file/d/1LHP7OwgI_O8t6-NBI0ZPn9JUt2GVgZEi/view" rel="nofollow">https://drive.google.com/file/d/1LHP7OwgI_O8t6-NBI0ZPn9JUt2G...</a> It's not pretty, but it works.<p>The differences in temperature and pressure results were exaggerated in the so that the gradient could be clearly seen.<p>Unfortunately, we did not get into the final (judged on this document) but it was an awesome experience nevertheless. The judges used this form to mark us: <a href="https://drive.google.com/file/d/1eZnum5zuJvkLzY7RLtm9A-NNzxwt_iO8/view" rel="nofollow">https://drive.google.com/file/d/1eZnum5zuJvkLzY7RLtm9A-NNzxw...</a> We would love to get any feedback from more experienced people, as we intend to do similar projects in the future and at least two of us want to be professional engineers. I'm happy to reply to any comments.
Show HN: 10 teams are racing to build a pivotal tracker replacement
A lot has changed since the shutdown of pivotal tracker was discussed here. As there were no viable alternatives it seems every month there was a new project popping up. With the last month before the sunsetting approaching, it starts to get exciting who will make it in time, who stays in the race and what the differentiating features of the projects will be.
Show HN: 10 teams are racing to build a pivotal tracker replacement
A lot has changed since the shutdown of pivotal tracker was discussed here. As there were no viable alternatives it seems every month there was a new project popping up. With the last month before the sunsetting approaching, it starts to get exciting who will make it in time, who stays in the race and what the differentiating features of the projects will be.
Show HN: Aiopandas – Async .apply() and .map() for Pandas, Faster API/LLMs Calls
Show HN: Web Audio Spring-Mass Synthesis
Hi, I'm the author of this little Web Audio toy which does physical modeling synthesis using a simple spring-mass system.<p>My current area of research is in sparse, event-based encodings of musical audio (<a href="https://blog.cochlea.xyz/sparse-interpretable-audio-codec-paper.html" rel="nofollow">https://blog.cochlea.xyz/sparse-interpretable-audio-codec-pa...</a>). I'm very interested in decomposing audio signals into a description of the "system" (e.g., room, instrument, vocal tract, etc.) and a sparse "control signal" which describes how and when energy is injected into that system. This toy was a great way to start learning about physical modeling synthesis, which seems to be the next stop in my research journey. I was also pleasantly surprised at what's possible these days writing custom Audio Worklets!
Show HN: Web Audio Spring-Mass Synthesis
Hi, I'm the author of this little Web Audio toy which does physical modeling synthesis using a simple spring-mass system.<p>My current area of research is in sparse, event-based encodings of musical audio (<a href="https://blog.cochlea.xyz/sparse-interpretable-audio-codec-paper.html" rel="nofollow">https://blog.cochlea.xyz/sparse-interpretable-audio-codec-pa...</a>). I'm very interested in decomposing audio signals into a description of the "system" (e.g., room, instrument, vocal tract, etc.) and a sparse "control signal" which describes how and when energy is injected into that system. This toy was a great way to start learning about physical modeling synthesis, which seems to be the next stop in my research journey. I was also pleasantly surprised at what's possible these days writing custom Audio Worklets!
Show HN: Fashion Shopping with Nearest Neighbors
I made this website with my wife in mind; it makes it possible to browse for similar fashion products over many different retailers at once.<p>The backend is written in Swift, and is hosted on a single Mac Mini. It performs nearest neighbors on the GPU over ~3M product images.<p>No vector DB, just pure matrix multiplications. Since we aren't just doing approximate nearest neighbors but rather sorting all results by distance, it's possible to show different "variety" levels by changing the stride over the sorted search results.<p>Nearest neighbors are computed in a latent vector space. The model which produces the vectors is also something I trained in pure Swift.<p>The underlying data is about 2TB scraped from <a href="https://www.shopltk.com/" rel="nofollow">https://www.shopltk.com/</a>.<p>All the code is at <a href="https://github.com/unixpickle/LTKlassifier" rel="nofollow">https://github.com/unixpickle/LTKlassifier</a>
Show HN: Fashion Shopping with Nearest Neighbors
I made this website with my wife in mind; it makes it possible to browse for similar fashion products over many different retailers at once.<p>The backend is written in Swift, and is hosted on a single Mac Mini. It performs nearest neighbors on the GPU over ~3M product images.<p>No vector DB, just pure matrix multiplications. Since we aren't just doing approximate nearest neighbors but rather sorting all results by distance, it's possible to show different "variety" levels by changing the stride over the sorted search results.<p>Nearest neighbors are computed in a latent vector space. The model which produces the vectors is also something I trained in pure Swift.<p>The underlying data is about 2TB scraped from <a href="https://www.shopltk.com/" rel="nofollow">https://www.shopltk.com/</a>.<p>All the code is at <a href="https://github.com/unixpickle/LTKlassifier" rel="nofollow">https://github.com/unixpickle/LTKlassifier</a>
Show HN: Metacheck – preview how any link appears on social media and chat apps
Hey HN,<p>I’ve been an indie hacker for a while, but I haven’t had much success with my past projects. Recently, I came across Marc Lou’s advice about building free tools just for fun, so I decided to give it a shot.<p>I built Metacheck, a simple tool that lets you preview how any link will appear on Twitter/X, LinkedIn, Whatsapp, Telegram, and other platforms. No API keys, no setup—just paste a link and see the preview.<p>Why I built this
I often ran into issues where social platforms displayed broken or unexpected link previews. Debugging Open Graph meta tags was annoying, so I made a tool to make it easier.<p>How it works
Fetches metadata from any URL
Parses Open Graph & Twitter Card tags
Shows real-time previews of how the link will look when shared<p>Try it out: <a href="https://metacheck.appstate.co/" rel="nofollow">https://metacheck.appstate.co/</a>
Show HN: Metacheck – preview how any link appears on social media and chat apps
Hey HN,<p>I’ve been an indie hacker for a while, but I haven’t had much success with my past projects. Recently, I came across Marc Lou’s advice about building free tools just for fun, so I decided to give it a shot.<p>I built Metacheck, a simple tool that lets you preview how any link will appear on Twitter/X, LinkedIn, Whatsapp, Telegram, and other platforms. No API keys, no setup—just paste a link and see the preview.<p>Why I built this
I often ran into issues where social platforms displayed broken or unexpected link previews. Debugging Open Graph meta tags was annoying, so I made a tool to make it easier.<p>How it works
Fetches metadata from any URL
Parses Open Graph & Twitter Card tags
Shows real-time previews of how the link will look when shared<p>Try it out: <a href="https://metacheck.appstate.co/" rel="nofollow">https://metacheck.appstate.co/</a>
Show HN: Metacheck – preview how any link appears on social media and chat apps
Hey HN,<p>I’ve been an indie hacker for a while, but I haven’t had much success with my past projects. Recently, I came across Marc Lou’s advice about building free tools just for fun, so I decided to give it a shot.<p>I built Metacheck, a simple tool that lets you preview how any link will appear on Twitter/X, LinkedIn, Whatsapp, Telegram, and other platforms. No API keys, no setup—just paste a link and see the preview.<p>Why I built this
I often ran into issues where social platforms displayed broken or unexpected link previews. Debugging Open Graph meta tags was annoying, so I made a tool to make it easier.<p>How it works
Fetches metadata from any URL
Parses Open Graph & Twitter Card tags
Shows real-time previews of how the link will look when shared<p>Try it out: <a href="https://metacheck.appstate.co/" rel="nofollow">https://metacheck.appstate.co/</a>
Show HN: A personal YouTube frontend based on yt-dlp
Show HN: A personal YouTube frontend based on yt-dlp
Show HN: A personal YouTube frontend based on yt-dlp