Med-Mastodon

SMT<a class="hashtag" rel="nofollow noopener" href="https://bsky.app/search?q=%23RStats" target="_blank">#RStats</a> <a class="hashtag" rel="nofollow noopener" href="https://bsky.app/search?q=%23duckdb" target="_blank">#duckdb</a> gurus, is thread safety the main reason we don't have (as of today) R level user defined functions like the duckdb's snake binding ? Or the reason is that we don't really have scalar functions ? <a href="https://github.com/duckdb/duckdb-r/issues/181" rel="nofollow noopener" target="_blank">github.com/duckdb/duckd...</a> <a href="https://github.com/duckdb/duckdb-r/issues/181" rel="nofollow noopener" target="_blank">User Defined Functions with R ...</a>

Jakob Mikschupdates about <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> <a href="https://mastodon.social/tags/spatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#spatial</a> joins <a href="https://mastodon.social/tags/geo" class="mention hashtag" rel="nofollow noopener" target="_blank">#geo</a> <a href="https://mastodon.social/tags/gis" class="mention hashtag" rel="nofollow noopener" target="_blank">#gis</a> <a href="https://mastodon.social/tags/geodata" class="mention hashtag" rel="nofollow noopener" target="_blank">#geodata</a> <a href="https://mastodon.social/tags/gistribe" class="mention hashtag" rel="nofollow noopener" target="_blank">#gistribe</a> <a href="https://mastodon.social/tags/gischat" class="mention hashtag" rel="nofollow noopener" target="_blank">#gischat</a> <a href="https://mastodon.social/tags/sql" class="mention hashtag" rel="nofollow noopener" target="_blank">#sql</a> <a href="https://duckdb.org/2025/08/08/spatial-joins.html" rel="nofollow noopener" translate="no" target="_blank">https://duckdb.org/2025/08/08/spatial-joins.html</a>

Olivier LeroyMy talks at <a href="https://mastodon.social/@useR_conf" class="u-url mention" rel="nofollow noopener" target="_blank">@useR_conf</a> is here <a href="https://defuneste.codeberg.page/useR_2025/" rel="nofollow noopener" translate="no" target="_blank">https://defuneste.codeberg.page/useR_2025/</a>tldr: I think storing "big" data as a parquet files, stored in s3 accessed with duckDB and wrapped in an R package is a nice way to save some of your sanity. Now that we know that DuckDB is great let start showing how R can make it in production! 😉 Side notes: loved using {litedown} and codeberg for the prez. Mermai.js you are also great but I am not rdy!<a href="https://fosstodon.org/tags/Rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#Rstats</a> <a href="https://fosstodon.org/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>

Egor Kotov 🌐🏃‍♂️🚊🚋🚙Get 9-30x speed doing areal-weighted interpolation with my new {𝐝𝐮𝐜𝐤𝐬𝐟} <a href="https://datasci.social/tags/rstats" class="mention hashtag" rel="nofollow noopener" target="_blank">#rstats</a> package compared to {sf}/{areal}. Experimental, but tested against both {areal} and {sf}. <a href="https://github.com/e-kotov/ducksf" rel="nofollow noopener" translate="no" target="_blank">https://github.com/e-kotov/ducksf</a> . Despite the costs of moving data between R and <a href="https://datasci.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>, the performance of {𝐝𝐮𝐜𝐤𝐬𝐟} is impressive, thanks to <a href="https://datasci.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> . Look at the attached benchmark results. And be sure to read the recent post of <a href="https://mastodon.social/@duckdb" class="u-url mention" rel="nofollow noopener" target="_blank">@duckdb</a> about the performance improvements of their spatial joins here: <a href="https://duckdb.org/2025/08/08/spatial-joins.html" rel="nofollow noopener" translate="no" target="_blank">https://duckdb.org/2025/08/08/spatial-joins.html</a>

Micah SherrNerd post!I just discovered that <a href="https://fediscience.org/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> (follow at <a href="https://mastodon.social/@duckdb" class="u-url mention" rel="nofollow noopener" target="_blank">@duckdb</a>), which is a really cool <a href="https://fediscience.org/tags/opensource" class="mention hashtag" rel="nofollow noopener" target="_blank">#opensource</a> tool that allows you to directly do SQL queries against csv, json, and many more file types (among with many other features), also lets you output query results directly to <a href="https://fediscience.org/tags/LaTeX" class="mention hashtag" rel="nofollow noopener" target="_blank">#LaTeX</a>.

Jan van der Laan<a href="https://mastodon.online/@statstas" class="u-url mention" rel="nofollow noopener" target="_blank">@statstas</a> <a href="https://datasci.social/tags/duckdb" class="mention hashtag" rel="nofollow noopener" target="_blank">#duckdb</a> can connect to external databases using odbc (<a href="https://duckdb.org/docs/stable/clients/odbc/windows.html" rel="nofollow noopener" translate="no" target="_blank">https://duckdb.org/docs/stable/clients/odbc/windows.html</a>) and can write parquet. That might work (I have zero experience with this).

boB Rudis 🇺🇦 🇬🇱 🇨🇦I track <a href="https://infosec.exchange/@stratosphere" class="u-url mention" rel="nofollow noopener" target="_blank">@stratosphere</a>'s posts & their bot has a daily top 10 sketch IPs list. My 🧠 kept 👀 lots of "*.100" IPs & I was curious how frequently they showed up.Went back 200 posts w/GH:McKael/madonctl using both R and DuckDB.Def block these.— <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>: <a href="https://ray.so/SdMcBZa" rel="nofollow noopener" translate="no" target="_blank">https://ray.so/SdMcBZa</a> — <a href="https://mastodon.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#RStats</a>: <a href="https://ray.so/naTBBMS" rel="nofollow noopener" translate="no" target="_blank">https://ray.so/naTBBMS</a>

Thomas SandmannThis week, I learned how to create and explore a data lake with duckdb, using its new ducklake extension. It was surprisingly easy to hand over the creation and management of parquet files with larg(ish) tables to ducklake. I loved being able to explore the data using R, python or plain SQL - even within the same Quarto document! <a href="https://tomsing1.github.io/blog/posts/ducklake/" rel="nofollow noopener" translate="no" target="_blank">https://tomsing1.github.io/blog/posts/ducklake/</a> <a href="https://genomic.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#RStats</a> <a href="https://genomic.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://genomic.social/tags/duckdb" class="mention hashtag" rel="nofollow noopener" target="_blank">#duckdb</a> <a href="https://genomic.social/tags/ducklake" class="mention hashtag" rel="nofollow noopener" target="_blank">#ducklake</a> <a href="https://genomic.social/tags/quarto" class="mention hashtag" rel="nofollow noopener" target="_blank">#quarto</a>

Olivier Leroy<a href="https://mapstodon.space/@kylebarron" class="u-url mention" rel="nofollow noopener" target="_blank">@kylebarron</a> For the neophyte, who is behind that project? <a href="https://fosstodon.org/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> has very easy to identify leaders since your bring that comparison.

Jesus Castagnetto 🇵🇪"Using <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> <a href="https://mastodon.social/tags/WASM" class="mention hashtag" rel="nofollow noopener" target="_blank">#WASM</a> + <a href="https://mastodon.social/tags/Cloudflare" class="mention hashtag" rel="nofollow noopener" target="_blank">#Cloudflare</a> <a href="https://mastodon.social/tags/R2" class="mention hashtag" rel="nofollow noopener" target="_blank">#R2</a> to host and query big <a href="https://mastodon.social/tags/data" class="mention hashtag" rel="nofollow noopener" target="_blank">#data</a> (for almost free)"<a href="https://mastodon.social/tags/BigData" class="mention hashtag" rel="nofollow noopener" target="_blank">#BigData</a> <a href="https://mastodon.social/tags/SQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#SQL</a><a href="https://andrewpwheeler.com/2025/06/29/using-duckdb-wasm-cloudflare-r2-to-host-and-query-big-data-for-almost-free/" rel="nofollow noopener" translate="no" target="_blank">https://andrewpwheeler.com/2025/06/29/using-duckdb-wasm-cloudflare-r2-to-host-and-query-big-data-for-almost-free/</a>

Data QuineDiscovering DuckDB Use Cases via GitHub - Petrica Leuca"TL;DR: In this post, we use the GitHub API to find repositories that mention DuckDB, then use DuckDB itself to parse and query the results efficiently with SQL."Think a lot of projects/organisations would like some of the techniques shown in this post for finding out who else is using their code on GitHub and for what purpose.<a href="https://duckdb.org/2025/06/27/discovering-w-github" rel="nofollow noopener" translate="no" target="_blank">https://duckdb.org/2025/06/27/discovering-w-github</a><a href="https://datasci.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenSource</a> <a href="https://datasci.social/tags/GitHub" class="mention hashtag" rel="nofollow noopener" target="_blank">#GitHub</a> <a href="https://datasci.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>

boB Rudis 🇺🇦 🇬🇱 🇨🇦Looks like I shld spend an ~hour or so poring over the <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> docs, b/c TIL `UNNEST` has optional parameters for making it easier to get a nice, flat table from deeply nested JSON (et al.).I'll bet I've missed other hidden gems like that despite having stared at the docs many times.

aeriqueGreat talk by Hannes Mühleisen of <a href="https://genart.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> about tables being a fundamental technology to civilization and not dismissing databases, SQL & ACID just because some implementation are getting old in the tooth.DuckDB sounds awesome and I know <a href="https://mastodon.nl/@bert_hubert" class="u-url mention" rel="nofollow noopener" target="_blank">@bert_hubert</a> is a big fan.<a href="https://genart.social/tags/JoyOfCoding" class="mention hashtag" rel="nofollow noopener" target="_blank">#JoyOfCoding</a> <a href="https://genart.social/tags/JoyOfCoding2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#JoyOfCoding2025</a>

boB Rudis 🇺🇦 🇬🇱 🇨🇦Drop #669 (2025-06-23): Monday Morning (Barely) Grab BagThe Monday Drop discusses 3 main topics: a Rube Goldberg-inspired data pipeline to archive X posts into <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>, the <a href="https://mastodon.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#RStats</a> package {fplot} for automating distribution plot creation in R, and an article from CSS-Tricks on advanced CSS color techniques, detailing color spaces and models for modern web development.<a href="http://dailydrop.hrbrmstr.dev/2025/06/23/drop-669-2025-06-23-monday-morning-barely-grab-bag/" rel="nofollow noopener" translate="no" target="_blank">http://dailydrop.hrbrmstr.dev/2025/06/23/drop-669-2025-06-23-monday-morning-barely-grab-bag/</a>

hrbrmstr's Daily DropDrop #669 (2025-06-23): Monday Morning (Barely) Grab BagRube Goldberg X-traction Pipeline; fplot; Color Everything in CSSSomething for (hopefully) everyone as we start off this brutally hot (in many parts of the northern hemisphere) terminal week of June.Stay safe out there. Type your email…Subscribe TL;DR(This is an LLM/GPT-generated summary of today’s Drop using Ollama + Qwen 3 and a custom prompt.)<ul><li>A Rube Goldberg-inspired data pipeline is created to archive X posts into a DuckDB database, using XCancel, Inoreader, and a DuckDB script for automation (<a href="https://en.wikipedia.org/wiki/Rube_Goldberg" rel="nofollow noopener" target="_blank">https://en.wikipedia.org/wiki/Rube_Goldberg</a>)</li><li>The <code>{fplot}</code> R package automates the creation of distribution plots by detecting data types and selecting appropriate visualizations, with options for global relabeling of variables (<a href="https://lrberge.github.io/fplot/" rel="nofollow noopener" target="_blank">https://lrberge.github.io/fplot/</a>)</li><li>The CSS-Tricks article “Color Everything in CSS” provides an in-depth look at color spaces, models, and gamuts in modern web development, offering a comprehensive guide to advanced CSS color techniques (<a href="https://css-tricks.com/color-everything-in-css/" rel="nofollow noopener" target="_blank">https://css-tricks.com/color-everything-in-css/</a>)</li></ul> Rube Goldberg X-traction PipelineI don’t see many mentions of <a href="https://en.wikipedia.org/wiki/Rube_Goldberg" rel="nofollow noopener" target="_blank">Rube Goldberg</a> in pop-culture settings anymore, which is a shame, since I used to enjoy poring over them in my younger days. Perhaps the reason for the lack of mentions is that many data pipelines have much in common with those complex, over-“engineerd” contraptions.Case in point for a recent “need” of mine: I wanted a way to store posts from users on X into a DuckDB database, for archival and research purposes. I already use <a href="https://xcancel.com" rel="nofollow noopener" target="_blank">XCancel</a>’s ability to generate an RSS feed for an account/search, which I yank into Inoreader for the archival part (the section header shows the XCancel-generated RSS feed for the White House’s other, even more MAGA, propaganda account).Inoreader’s API is…not great. It can most certainly be machinated (I have an R package with the function I need in it), but I really wanted a solution that let me just use DuckDB for all the work.Then, I rememberd, if you put feeds in Inoreader folders, you can turn that folder into a JSON feed that gets updates every ~30 minutes or so. This one:is for a series of feeds related to what’s going on in the Middle East right now.With that JSON URL in hand, it’s as basic as: <pre>#!/usr/bin/env bash# for cache bustingepoch=$(date +%s)duckdb articles.ddb <<EOQLOAD json;INSTALL shellfs FROM community;LOAD shellfs;CREATE TABLE IF NOT EXISTS broadcast_feed_items ( url VARCHAR PRIMARY KEY, title VARCHAR, content_html VARCHAR, date_published VARCHAR, tags VARCHAR[], authors JSON);-- this is where the update magic happensINSERT OR IGNORE INTO broadcast_feed_itemsFROM read_json('curl -s https://www.inoreader.com/stream/user/##########/tag/broadcast/view/json?since=${epoch} | jq .items[] |')SELECT url, title, content_html, date_published, tags, authors;-- Thinned out JSON content for viewing appCOPY ( FROM broadcast_feed_items SELECT content_html, -- "title" is useless for the most part since this is an X post date_published AS "timestamp", regexp_replace(authors.name, '"', '', 'g') AS handle) TO 'posts.json' (FORMAT JSON, ARRAY );EOQ</pre> There are other ways to unnest the data than using <code>jq</code> and the <code>shellfs</code> DuckDB extension, but the more RG the better (for this post)!So the final path is:X -> XCancel -> XCancel RSS -> Inoreader -> Inoreader JSON -> jq -> DuckDBwith virtually no code (save for the snippet, above).I’ve got this running as a systemd timer/service running every 30 minutes.Later this week (when I’m done hand-coding it—yes, sans-Claude), I’ll have a Lit-based vanilla HTML/CS/JS viewer app in one of the Drops. fplot(This is an <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://dailydrop.hrbrmstr.dev/tag/rstats/" target="_blank">#RStats</a> section, so def move along if that is not your cuppa.)My daily git-stalking led me to finding this gem of an R package.<a href="https://lrberge.github.io/fplot/" rel="nofollow noopener" target="_blank"><code>{fplot}</code></a> (<a href="https://github.com/lrberge/fplot?tab=readme-ov-file" rel="nofollow noopener" target="_blank">GH</a>) is designed to automate and simplify the visualization of data distributions (something I have to do every. single. day.). Its core mission is to let folks quickly generate meaningful and aesthetically pleasing distribution plots, regardless of the underlying data type (it supports continuous, categorical, or skewed), by making spiffy choices about the appropriate graphical representation for each variable.Functions in the package detect the nature of your data (e.g., categorical vs. continuous, skewed or not) and automatically selects the most suitable plot type. For example, it will not use the same visualization for a categorical variable as it would for a continuous one, and it adapts further if the data is heavily skewed.Ergonomics are pretty dope, since you only need a single line of code to generate a plot, with the package handling the details of layout and type selection. This is particularly useful for exploratory data analysis or for folks who want quick, visually appealing graphics without extensive customization.Tools are provided to globally relabel variable names for all plots. This is managed via the <code>setFplot_dict()</code> function, which lets us map cryptic/gosh awful or technical variable names to more readable labels that will appear in all subsequent plots.Example usage: <pre>setFplot_dict(c( Origin = "Exporting Country", Destination = "Importing Country", Euros = "Exports Value in €", jnl_top_25p = "Pub. in Top 25% journal", jnl_top_5p = "Publications in Top 5% journal", journal = "Journal", institution = "U.S. Institution", Petal.Length = "Petal Length"))</pre> The typical workflow with fplot is straightforward:<ol><li>Load your data.</li><li>Optionally set global variable labels using <code>setFplot_dict()</code>.</li><li>Call the <code>fplot</code> function on your variable(s) of interest.</li><li>The package automatically determines the best plot type and layout for your data.</li></ol>The same function call can yield different types of plots depending on the data provided, streamlining the process of distributional analysis and visualization.A gallery of examples and a more detailed walk-through are available on the package’s website. Color Everything in CSSThe CSS-Tricks article “<a href="https://css-tricks.com/color-everything-in-css/" rel="nofollow noopener" target="_blank">Color Everything in CSS</a>” offers a comprehensive, up-to-date exploration of how color works in CSS, moving beyond just the basics of color and background-color to cover the deeper technical landscape of color on the web. The article introduces essential concepts like color spaces, color models, and color gamuts, which are foundational for understanding how colors are represented, manipulated, and rendered in browsers today.We’ve covered many of these individual topics before, but this is a well-crafted, all-in-one that does such a good job, I do not wish to steal any thunder from it. Head on over for to level up your CSS skills. FINRemember, you can follow and interact with the full text of The Daily Drop’s free posts on:<ul><li>🐘 Mastodon via <code>@dailydrop.hrbrmstr.dev@dailydrop.hrbrmstr.dev</code></li><li>🦋 Bluesky via <code>https://bsky.app/profile/dailydrop.hrbrmstr.dev.web.brid.gy</code></li></ul>☮️<a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://dailydrop.hrbrmstr.dev/tag/duckdb/" target="_blank">#duckdb</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://dailydrop.hrbrmstr.dev/tag/rstats/" target="_blank">#RStats</a>

SpatialistsEasily obtain OSM and OMF data: <a href="https://mapstodon.space/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> and CLI tools <a href="https://mapstodon.space/tags/QuackOSM" class="mention hashtag" rel="nofollow noopener" target="_blank">#QuackOSM</a> and <a href="https://mapstodon.space/tags/OvertureMaestro" class="mention hashtag" rel="nofollow noopener" target="_blank">#OvertureMaestro</a> offer easier access to data from <a href="https://mapstodon.space/tags/OpenStreetMap" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenStreetMap</a> (<a href="https://mapstodon.space/tags/OSM" class="mention hashtag" rel="nofollow noopener" target="_blank">#OSM</a>) and the Overture Maps Foundation (<a href="https://mapstodon.space/tags/OMF" class="mention hashtag" rel="nofollow noopener" target="_blank">#OMF</a>) through <a href="https://mapstodon.space/tags/PyArrow" class="mention hashtag" rel="nofollow noopener" target="_blank">#PyArrow</a>, <a href="https://mapstodon.space/tags/GeoParquet" class="mention hashtag" rel="nofollow noopener" target="_blank">#GeoParquet</a>, or <a href="https://mapstodon.space/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>. These tools can simplify large-scale geospatial data... <a href="https://spatialists.ch/posts/2025/05/23-easily-obtain-osm-and-omf-data/" rel="nofollow noopener" translate="no" target="_blank">https://spatialists.ch/posts/2025/05/23-easily-obtain-osm-and-omf-data/</a> <a href="https://mapstodon.space/tags/GIS" class="mention hashtag" rel="nofollow noopener" target="_blank">#GIS</a> <a href="https://mapstodon.space/tags/GISchat" class="mention hashtag" rel="nofollow noopener" target="_blank">#GISchat</a> <a href="https://mapstodon.space/tags/geospatial" class="mention hashtag" rel="nofollow noopener" target="_blank">#geospatial</a> <a href="https://mapstodon.space/tags/SwissGIS" class="mention hashtag" rel="nofollow noopener" target="_blank">#SwissGIS</a>

boB Rudis 🇺🇦 🇬🇱 🇨🇦Never gonna not 💙 <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>'s built-in bar chart function

Jesus Castagnetto 🇵🇪"duckplyr fully joins the tidyverse!"<a href="https://www.tidyverse.org/blog/2025/06/duckplyr-1-1-0/" rel="nofollow noopener" translate="no" target="_blank">https://www.tidyverse.org/blog/2025/06/duckplyr-1-1-0/</a> <a href="https://mastodon.social/tags/duckdb" class="mention hashtag" rel="nofollow noopener" target="_blank">#duckdb</a> <a href="https://mastodon.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#RStats</a> <a href="https://mastodon.social/tags/tidyverse" class="mention hashtag" rel="nofollow noopener" target="_blank">#tidyverse</a>

Data Quine"duckplyr fully joins the tidyverse!"<a href="https://www.tidyverse.org/blog/2025/06/duckplyr-1-1-0/" rel="nofollow noopener" translate="no" target="_blank">https://www.tidyverse.org/blog/2025/06/duckplyr-1-1-0/</a><a href="https://datasci.social/tags/DuckPlyr" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckPlyr</a> <a href="https://datasci.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a> <a href="https://datasci.social/tags/RStats" class="mention hashtag" rel="nofollow noopener" target="_blank">#RStats</a> <a href="https://datasci.social/tags/DataAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#DataAnalysis</a>

boB Rudis 🇺🇦 🇬🇱 🇨🇦Bonus Drop #86 (2025-06-15): I Think You May Be ProjectingThe Weekend Bonus Drop covers two data engineering projects utilizing <a href="https://mastodon.social/tags/DuckDB" class="mention hashtag" rel="nofollow noopener" target="_blank">#DuckDB</a>. The first project improves rock-climbing trip planning by integrating climbing routes with precise weather forecasts. The second project organizes Garmin activity data into a clean database. Both exemplify real-world engineering challenges for personal projects, emphasizing practical problem-solving and hands-on learning in data…<a href="http://dailydrop.hrbrmstr.dev/2025/06/15/bonus-drop-86-2025-06-15-i-think-you-may-be-projecting/" rel="nofollow noopener" translate="no" target="_blank">http://dailydrop.hrbrmstr.dev/2025/06/15/bonus-drop-86-2025-06-15-i-think-you-may-be-projecting/</a>

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