fillpattern
Pattern fills for ggplot2, hardened against the ways users write sizes
A side-by-side editorial comparison of ecodive and palettecore — release velocity, themes, recent moves, and the top alternatives to consider.
ecodive rebuilt itself into a broad diversity-metric library, breaking as it went
ecodive computes alpha and beta diversity metrics for ecological and microbiome count data, including phylogenetic measures like Faith's PD and the UniFrac family. The 2.0.0 rewrite expanded it from a handful of metrics to roughly fourteen alpha and thirty beta measures while flipping the expected input orientation to samples-as-rows. Subsequent releases have been spent settling the normalisation interface that expansion exposed.
Accessible palettes generated from one seed, with every audit number computed on the hex you actually get
palettecore generates sequential, diverging and categorical colour palettes from a single seed using CIEDE2000 arc-length spacing in OKLCH, and audits each one for colour-vision-deficiency separation, greyscale survival, gamut and WCAG contrast. It exists as a numpy-only Python core and an R mirror validated hex-exact against shared parity fixtures, plus a CLI the project describes as its agent-friendly entry point. Four releases landed inside 24 hours in late July.
ecodive computes alpha and beta diversity metrics for ecological and microbiome count data, including phylogenetic measures like Faith's PD and the UniFrac family. The 2.0.0 rewrite expanded it from a handful of metrics to roughly fourteen alpha and thirty beta measures while flipping the expected input orientation to samples-as-rows. Subsequent releases have been spent settling the normalisation interface that expansion exposed.
This is a package that made its breaking changes deliberately and in a cluster. After 2.0.0 reoriented input and removed the weighted parameter, 2.1.0 superseded rescale with norm, and 2.2.6 changed norm's default from percent to none and removed it from some beta functions entirely. That last one matters more than it reads: normalisation defaults silently change the numbers a metric returns, and the direction is toward making the user state their choice rather than inheriting one.
With the metric surface broad and the normalisation interface now explicit, expect the next releases to stabilise — documentation and edge-case handling around CLR and rarefaction rather than another interface break.
palettecore generates sequential, diverging and categorical colour palettes from a single seed using CIEDE2000 arc-length spacing in OKLCH, and audits each one for colour-vision-deficiency separation, greyscale survival, gamut and WCAG contrast. It exists as a numpy-only Python core and an R mirror validated hex-exact against shared parity fixtures, plus a CLI the project describes as its agent-friendly entry point. Four releases landed inside 24 hours in late July.
The arc is about making the audit honest rather than making the palettes prettier. The 0.2.2 release, prompted by an external review, moved every diagnostic to compute on the 8-bit quantised hex codes actually returned rather than on internal floats — a change that flips results near thresholds and had been quietly overstating one deuteranopia score. The 0.4.0 helix kind and the vividness control extend the generator, but the same release also tightens its own claims, reframing helix as checked rather than assumed CVD-safe.
Given the pattern of auditing its own assertions, expect the next release to extend the cvd_luminance_monotonic diagnostic beyond helix to the other palette kinds.
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 ecodive or palettecore.
Pattern fills for ggplot2, hardened against the ways users write sizes
gcube's recent releases are all packaging metadata, not simulation code
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
ggstats keeps widening what a coefficient or Likert plot can be
State-space data simulation for R, filled in one function at a time
rollama turns a local-LLM wrapper into an instrument for reproducible annotation
See all ecodive alternatives → · See all palettecore alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. palettecore is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. 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. palettecore is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top ecodive alternatives in Analytics are ranked by recent ship velocity. Browse the "ecodive alternatives" section above for the current picks, or visit /alternatives/ecodive for the full list with editorial commentary on each.
Top palettecore alternatives in Analytics are ranked by recent ship velocity. Browse the "palettecore alternatives" section above for the current picks, or visit /alternatives/palettecore for the full list with editorial commentary on each.