rerender and add thumbnail so linkedin renders nicely

_freeze/blog/posts/2025-09-09-h3o-on-cran/index/execute-results/html.json

@@ -1,8 +1,8 @@
 {
-  "hash": "6119954e7cd9d2742a652929e32451c6",
+  "hash": "0e2ac93c67c7c976145259a04d7c7571",
   "result": {
     "engine": "knitr",
-    "markdown": "---\ntitle: \"`h3o` is now on CRAN‼️\"\ndescription: |\n  R users now have access to a pure Rust implementation of Uber's H3, a \n  hexagonal geospatial grid and indexing system.\nauthor: Blake Vernon\ndate: \"2025/09/09\"\nimage: thumbnail.png\nimage-alt: \"The letters h3o on a hexagonal sticker.\"\ncategories: [Release]\n---\n\nThe extendr-powered R package `h3o` provides access to [a pure Rust implementation](https://github.com/HydroniumLabs/h3o) \nof [Uber's H3 Geospatial Indexing System](https://github.com/uber/h3). \nOriginally developed by Josiah Parry, the R package has also become an official \nproduct of extendr, which means community support 🤝 and maintenance 🏗️ into \nthe foreseeable future.\n\n## `h3o` at a glance 👀\n\nThe package provides functionality to interact with H3's grid as vectors, which \ncan be converted to and from `sf` geometries. \n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(h3o)\nlibrary(dplyr)\nlibrary(sf)\nlibrary(tibble)\n\nxy <- data.frame(\n  x = runif(100, -5, 10),\n  y = runif(100, 40, 50)\n)\n\npnts <- st_as_sf(\n  xy,\n  coords = c(\"x\", \"y\"),\n  crs = 4326\n)\n\npnts |> mutate(h3 = h3_from_points(geometry, 5))\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nSimple feature collection with 100 features and 1 field\nGeometry type: POINT\nDimension:     XY\nBounding box:  xmin: -4.984872 ymin: 40.2337 xmax: 9.931386 ymax: 49.8441\nGeodetic CRS:  WGS 84\nFirst 10 features:\n                      geometry              h3\n1    POINT (1.470689 40.78258) 85394603fffffff\n2     POINT (3.65606 41.12884) 853941cbfffffff\n3   POINT (-2.451488 42.25655) 85392937fffffff\n4     POINT (6.997712 40.2337) 85394b93fffffff\n5   POINT (-4.045207 46.06162) 85184313fffffff\n6   POINT (0.4984067 43.33282) 8539663bfffffff\n7    POINT (2.457852 41.96973) 853944affffffff\n8    POINT (8.899564 41.77609) 851eb233fffffff\n9    POINT (1.249403 43.94849) 8539609bfffffff\n10 POINT (-0.7160074 40.27496) 85397223fffffff\n```\n\n\n:::\n:::\n\n\nYou can use the `st_as_sfc()` method to convert H3 hexagons to sf `POLYGON`s.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# replace geometry\nh3_cells <- pnts |>\n  mutate(\n    h3 = h3_from_points(geometry, 4),\n    geometry = st_as_sfc(h3)\n  )\n\n# plot the hexagons\nplot(st_geometry(h3_cells))\n```\n\n::: {.cell-output-display}\n![](index_files/figure-html/unnamed-chunk-1-1.png){width=672}\n:::\n:::\n\n\nH3 cell centroids can be returned using `h3_to_points()`. If `sf` is avilable,\nthe results will be returned as an `sfc` (sf column) object. Otherwise it will\nreturn a list of `sfg` (sf geometries).\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# fetch h3 column\nh3s <- h3_cells[[\"h3\"]]\n\n# get there centers\nh3_centers <- h3_to_points(h3s)\n\n# plot the hexagons with the centers\nplot(st_geometry(h3_cells))\nplot(h3_centers, pch = 16, add = TRUE, col = \"black\")\n```\n\n::: {.cell-output-display}\n![](index_files/figure-html/unnamed-chunk-2-1.png){width=672}\n:::\n:::\n\n\n## H3 at light speed ⚡\n\nBecause it builds on a pure Rust implementation, `h3o` is also very very fast. \nHere are some benchmarks, which also serve to showcase `h3o` tools.\n\n### Creating polygons\n\n\n::: {.cell}\n\n```{.r .cell-code}\nh3_strs <- as.character(h3s)\nbench::mark(\n  h3o = st_as_sfc(h3s),\n  h3jsr = h3jsr::cell_to_polygon(h3_strs),\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o          1      1        17.2        1      1   \n2 h3jsr       18.5   17.8       1        275.     5.77\n```\n\n\n:::\n:::\n\n\n### Converting polygons to H3 cells:\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnc <- st_read(system.file(\"gpkg/nc.gpkg\", package = \"sf\"), quiet = TRUE) |>\n  st_transform(4326) |>\n  st_geometry()\n\nbench::mark(\n  h3o = sfc_to_cells(nc, 5, \"centroid\"),\n  h3jsr = h3jsr::polygon_to_cells(nc, 5),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o         1      1         5.16       1       2.26\n2 h3jsr       5.43   5.30      1         33.7     1   \n```\n\n\n:::\n:::\n\n\n### Converting points to cells\n\n\n::: {.cell}\n\n```{.r .cell-code}\nbench::mark(\n  h3o = h3_from_points(pnts$geometry, 3),\n  h3jsr = h3jsr::point_to_cell(pnts$geometry, 3),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o          1      1        23.8        1      1.31\n2 h3jsr       26.7   26.5       1       1178.     1   \n```\n\n\n:::\n:::\n\n\n### Retrieve edges\n\n\n::: {.cell}\n\n```{.r .cell-code}\nbench::mark(\n  h3o = h3_edges(h3s),\n  h3jsr = h3jsr::get_udedges(h3_strs),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o         1      1         3.10      1        1.03\n2 h3jsr       4.00   3.26      1         7.02     1   \n```\n\n\n:::\n:::\n\n\n### Get origins and destinations from edges.\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# get edges for a single location\neds <- h3_edges(h3s[1])[[1]]\n# strings for h3jsr\neds_str <- as.character(eds)\n\nbench::mark(\n  h3o = h3_edge_cells(eds),\n  h3jsr = h3jsr::get_udends(eds_str),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o          1      1        34.7      1        1.28\n2 h3jsr       45.2   35.8       1        2.52     1   \n```\n\n\n:::\n:::\n\n\n## Installation 📦\n\nYou can install the release version of `h3o` from CRAN with:\n\n``` r\ninstall.packages(\"h3o\")\n```\n\nOr you can install the development version from [GitHub](https://github.com/)\nwith:\n\n``` r\n# install.packages(\"pak\")\npak::pak(\"extendr/h3o\")\n```\n\n## Learn more 🧑‍🎓\n\nSee the package documentation for more details: <http://extendr.rs/h3o/>. \n\nIf you encounter a bug or would like to request new features, head over to the \nGitHub repository: <https://github.com/extendr/h3o>.",
+    "markdown": "---\ntitle: \"`h3o` is now on CRAN‼️\"\ndescription: |\n  R users now have access to a pure Rust implementation of Uber's H3, a \n  hexagonal geospatial grid and indexing system.\nauthor: \n  - name: Blake Vernon\n  - name: Josiah Parry\ndate: \"2025/09/09\"\nimage: thumbnail.png\nimage-alt: \"The letters h3o on a hexagonal sticker.\"\ncategories: [Release]\n---\n\n\n\n![](thumbnail.png)\n\nThe extendr-powered R package `h3o` provides access to [a pure Rust implementation](https://github.com/HydroniumLabs/h3o) \nof [Uber's H3 Geospatial Indexing System](https://github.com/uber/h3). \nOriginally developed by Josiah Parry, the R package has also become an official \nproduct of extendr, which means community support 🤝 and maintenance 🏗️ into \nthe foreseeable future.\n\n\n## `h3o` at a glance 👀\n\nThe package provides functionality to interact with H3's grid as vectors, which \ncan be converted to and from `sf` geometries. \n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(h3o)\nlibrary(dplyr)\nlibrary(sf)\nlibrary(tibble)\n\nxy <- data.frame(\n  x = runif(100, -5, 10),\n  y = runif(100, 40, 50)\n)\n\npnts <- st_as_sf(\n  xy,\n  coords = c(\"x\", \"y\"),\n  crs = 4326\n)\n\nmutate(pnts, h3 = h3_from_points(geometry, 5))\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\nSimple feature collection with 100 features and 1 field\nGeometry type: POINT\nDimension:     XY\nBounding box:  xmin: -4.861231 ymin: 40.05397 xmax: 9.846006 ymax: 49.98446\nGeodetic CRS:  WGS 84\nFirst 10 features:\n                     geometry              h3\n1   POINT (3.169478 45.06344) 851f92d7fffffff\n2    POINT (5.63995 44.91631) 851f9323fffffff\n3   POINT (1.263684 42.55526) 85396207fffffff\n4  POINT (0.3876174 41.06653) 853973b3fffffff\n5  POINT (-1.192501 44.22128) 85184d7bfffffff\n6    POINT (3.86172 41.56535) 8539419bfffffff\n7  POINT (-1.565639 49.98446) 851866bbfffffff\n8   POINT (3.704704 42.74759) 85396e47fffffff\n9    POINT (2.804652 47.0575) 851fb267fffffff\n10 POINT (-4.021278 47.52185) 851846affffffff\n```\n\n\n:::\n:::\n\n\n\nYou can use the `st_as_sfc()` method to convert H3 hexagons to sf `POLYGON`s.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# replace geometry\nh3_cells <- pnts |>\n  mutate(\n    h3 = h3_from_points(geometry, 4),\n    geometry = st_as_sfc(h3)\n  )\n\n# plot the hexagons\nplot(st_geometry(h3_cells))\n```\n\n::: {.cell-output-display}\n![](index_files/figure-html/unnamed-chunk-1-1.png){width=672}\n:::\n:::\n\n\n\nH3 cell centroids can be returned using `h3_to_points()`. If `sf` is avilable,\nthe results will be returned as an `sfc` (sf column) object. Otherwise it will\nreturn a list of `sfg` (sf geometries).\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# fetch h3 column\nh3s <- h3_cells[[\"h3\"]]\n\n# get there centers\nh3_centers <- h3_to_points(h3s)\n\n# plot the hexagons with the centers\nplot(st_geometry(h3_cells))\nplot(h3_centers, pch = 16, add = TRUE, col = \"black\")\n```\n\n::: {.cell-output-display}\n![](index_files/figure-html/unnamed-chunk-2-1.png){width=672}\n:::\n:::\n\n\n\n## H3 at light speed ⚡\n\nBecause it builds on a pure Rust implementation, `h3o` is also very very fast. \nHere are some benchmarks, which also serve to showcase `h3o` tools.\n\n### Creating polygons\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nh3_strs <- as.character(h3s)\nbench::mark(\n  h3o = st_as_sfc(h3s),\n  h3jsr = h3jsr::cell_to_polygon(h3_strs),\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o          1      1        26.1        1      1   \n2 h3jsr       27.0   25.6       1        268.     3.85\n```\n\n\n:::\n:::\n\n\n\n### Converting polygons to H3 cells:\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nnc <- st_read(system.file(\"gpkg/nc.gpkg\", package = \"sf\"), quiet = TRUE) |>\n  st_transform(4326) |>\n  st_geometry()\n\nbench::mark(\n  h3o = sfc_to_cells(nc, 5, \"centroid\"),\n  h3jsr = h3jsr::polygon_to_cells(nc, 5),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o         1      1         7.79       1       5.84\n2 h3jsr       8.96   7.82      1         33.0     1   \n```\n\n\n:::\n:::\n\n\n\n### Converting points to cells\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nbench::mark(\n  h3o = h3_from_points(pnts$geometry, 3),\n  h3jsr = h3jsr::point_to_cell(pnts$geometry, 3),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o          1      1        16.8        1      1.02\n2 h3jsr       16.7   19.4       1       1193.     1   \n```\n\n\n:::\n:::\n\n\n\n### Retrieve edges\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nbench::mark(\n  h3o = h3_edges(h3s),\n  h3jsr = h3jsr::get_udedges(h3_strs),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o         1      1         2.95      1        1   \n2 h3jsr       2.97   2.83      1         7.02     2.65\n```\n\n\n:::\n:::\n\n\n\n### Get origins and destinations from edges.\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\n# get edges for a single location\neds <- h3_edges(h3s[1])[[1]]\n# strings for h3jsr\neds_str <- as.character(eds)\n\nbench::mark(\n  h3o = h3_edge_cells(eds),\n  h3jsr = h3jsr::get_udends(eds_str),\n  check = FALSE,\n  relative = TRUE\n)\n```\n\n::: {.cell-output .cell-output-stdout}\n\n```\n# A tibble: 2 × 6\n  expression   min median `itr/sec` mem_alloc `gc/sec`\n  <bch:expr> <dbl>  <dbl>     <dbl>     <dbl>    <dbl>\n1 h3o          1      1        24.6      1        1   \n2 h3jsr       21.3   26.1       1        2.52     3.01\n```\n\n\n:::\n:::\n\n\n\n## Installation 📦\n\nYou can install the release version of `h3o` from CRAN with:\n\n``` r\ninstall.packages(\"h3o\")\n```\n\nOr you can install the development version from [GitHub](https://github.com/)\nwith:\n\n``` r\n# install.packages(\"pak\")\npak::pak(\"extendr/h3o\")\n```\n\n## Learn more 🧑‍🎓\n\nSee the package documentation for more details: <http://extendr.rs/h3o/>. \n\nIf you encounter a bug or would like to request new features, head over to the \nGitHub repository: <https://github.com/extendr/h3o>.",
     "supporting": [
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blog/posts/2025-09-09-h3o-on-cran/index.qmd

@@ -12,12 +12,15 @@ image-alt: "The letters h3o on a hexagonal sticker."
 categories: [Release]
 ---
 
+![](thumbnail.png)
+
 The extendr-powered R package `h3o` provides access to [a pure Rust implementation](https://github.com/HydroniumLabs/h3o) 
 of [Uber's H3 Geospatial Indexing System](https://github.com/uber/h3). 
 Originally developed by Josiah Parry, the R package has also become an official 
 product of extendr, which means community support 🤝 and maintenance 🏗️ into 
 the foreseeable future.
 
+
 ## `h3o` at a glance 👀
 
 The package provides functionality to interact with H3's grid as vectors, which 
@@ -43,7 +46,7 @@ pnts <- st_as_sf(
   crs = 4326
 )
 
-pnts |> mutate(h3 = h3_from_points(geometry, 5))
+mutate(pnts, h3 = h3_from_points(geometry, 5))
 ```
 
 You can use the `st_as_sfc()` method to convert H3 hexagons to sf `POLYGON`s.