tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of crul and sparsevctrs — release velocity, themes, recent moves, and the top alternatives to consider.
crul took mocking back from webmockr and made it a property of the client itself
crul is the R6-based HTTP client underneath much of rOpenSci's package stack, covering synchronous requests, three flavours of async, pagination and retries. Its 1.6.0 release in July 2025 changed where test mocking lives: each client — HttpClient, Async, AsyncVaried — now takes a mocking parameter at initialisation or per method, and the standalone mock() function is deprecated. Mocking used to be something webmockr switched on from outside; it is now a setting on the client.
Sparse vectors stopped being a storage trick and became something you can do arithmetic on
sparsevctrs supplies sparse vectors that live inside ordinary data frames and tibbles, which is what lets tidymodels carry wide, mostly-zero feature matrices without densifying them. Through 0.2.0 and 0.3.0 the package built out a computation layer on top of that storage — first summary statistics, then scalar and element-wise arithmetic — and everything since has been correctness work at the C level.
crul is the R6-based HTTP client underneath much of rOpenSci's package stack, covering synchronous requests, three flavours of async, pagination and retries. Its 1.6.0 release in July 2025 changed where test mocking lives: each client — HttpClient, Async, AsyncVaried — now takes a mocking parameter at initialisation or per method, and the standalone mock() function is deprecated. Mocking used to be something webmockr switched on from outside; it is now a setting on the client.
The async surface has been the growth area for years — retries reached Async, AsyncVaried, AsyncQueue and HttpRequest in 1.4, AsyncQueue gained the response accessors in 1.2, and 1.5.0 wired async requests up to webmockr. The 1.6.0 change reverses that direction of dependency, and it landed within a minute of webmockr's own release severing its tie to vcr. Read together, the rOpenSci HTTP stack is being deliberately untangled so each package can be used without the others.
With mock() deprecated rather than removed, the next major release is the likely point of deletion. Expect the remaining work to follow the same decoupling theme rather than adding request features.
sparsevctrs supplies sparse vectors that live inside ordinary data frames and tibbles, which is what lets tidymodels carry wide, mostly-zero feature matrices without densifying them. Through 0.2.0 and 0.3.0 the package built out a computation layer on top of that storage — first summary statistics, then scalar and element-wise arithmetic — and everything since has been correctness work at the C level.
The release pattern splits cleanly at 0.3.0. Before it, new functions arrive in batches; after it, five consecutive releases are bug fixes, and the bugs are the kind that come with hand-written sparse kernels: a stack imbalance when sparse_multiplication() returns all zeros, undefined behaviour in multiplication, type errors in sparse_is_na(), coercion failures on NA input. That is the expected cost of an ALTREP-backed numerical layer, and the fixes are landing steadily.
With the arithmetic surface in place and the recent releases all narrow fixes, the next one is more likely another correctness patch than a new function family. The R devel fix in 0.3.5 suggests upcoming R releases are the current source of breakage.
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either crul or sparsevctrs.
A tables-listings-graphs package that reached CRAN and then went quiet.
Tplyr made clinical summary tables explain where every number came from.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
See all crul alternatives → · See all sparsevctrs alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. crul and sparsevctrs are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. crul and sparsevctrs are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top crul alternatives in Analytics are ranked by recent ship velocity. Browse the "crul alternatives" section above for the current picks, or visit /alternatives/crul for the full list with editorial commentary on each.
Top sparsevctrs alternatives in Analytics are ranked by recent ship velocity. Browse the "sparsevctrs alternatives" section above for the current picks, or visit /alternatives/sparsevctrs for the full list with editorial commentary on each.