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Comparison · Infra & APIs

ggpointless vs slendr

A side-by-side editorial comparison of ggpointless and slendr — release velocity, themes, recent moves, and the top alternatives to consider.

ggpointless vs slendr: at a glance

Featureggpointlessslendr
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2-extensions, data-visualization, pictogram-charts, alpha-gradientspopulation-genetics, simulation, tree-sequences, python-interop
Last editorial update1h ago4h ago
WebsiteVisit →Visit →

What is ggpointless?

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

Read the full ggpointless trajectory →

What is slendr?

Population-genetic simulation in R, opened up to selection and finally easier to install.

slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().

Read the full slendr trajectory →

ggpointless vs slendr: editorial side-by-side

G
ggpointless
INFRA · APIS
0.0

ggpointless keeps adding the ggplot2 layers nobody else bothered to write.

◆ Current state

ggpointless is a small ggplot2 extension collecting geoms that sit outside the standard set — Lexis diagrams, Chaikin-smoothed paths, hanging chains, Fourier reconstructions — and it has grown steadily rather than changed shape. The May release is the largest yet: isotype and pictogram bar charts as stacks of discrete unit cells, a family of geoms that fade paths, segments, curves and reference lines along their length, and geom_gridline(), which draws grid lines as a layer on top of the data rather than beneath it.

◆ Where it's heading

Two patterns are visible. Ideas get generalized rather than left as one-offs: geom_area_fade() in the previous release established alpha gradients via grid::linearGradient(), and the recent release spreads that treatment across paths, lines, steps, segments, curves and the three reference-line geoms, each with the same fade_direction and alpha_fade_to arguments. And each new geom is expected to survive real plots — the unit charts work under coord_equal, coord_polar, coord_radial, coord_flip and faceting, and geom_gridline reads positions from trained scales and inherits styling from the theme's panel grid. The package also tracks ggplot2 closely, requiring 4.0.0 and using make_constructor() and gg_par() internally, and it dropped its bundled datasets outright rather than maintain stale copies.

◆ Prediction

The fade treatment now covers most path-like geoms but not the area and ribbon family beyond geom_area_fade(), which is where the pattern has room left to run. The unit-cell charts arrive with a label helper and no fill or grouping variants, so those are the plausible next additions.

S
slendr
INFRA · APIS
0.0

Population-genetic simulation in R, opened up to selection and finally easier to install.

◆ Current state

slendr specifies spatial and non-spatial population-genetic models in R and simulates them through SLiM or msprime, returning tree sequences that tskit then analyses. Two threads dominate the current releases: keeping in step with fast-moving backends, with SLiM 5.1, pyslim 1.1.0 and Python 3.13 now required, and reducing the setup burden that its Python dependency imposes. Version 1.5.0 adds ephemeral uv-based virtual environments, so init_env(uv = TRUE) can stand in for creating a permanent environment with setup_env().

◆ Where it's heading

Since the 1.0.0 release added non-neutral simulation, the work has shifted from capability to friction. A large share of recent notes concerns Python environment handling, conda activation races on Windows, dependency pruning that made shiny optional, and argument names that misled users, as when gene_flow()'s rate argument turned out to mean total ancestry proportion rather than a rate. That is the profile of a package whose scientific surface is settled and whose remaining problems are the ones users actually hit.

◆ Prediction

Expect the uv-based environment path to move from fallback to default once it has proven itself, given the notes already describe an environment variable for making it so. The deprecated rate argument in gene_flow() is explicitly slated for removal in a future major release, which is the clearest signal here of what a 2.0 would contain.

Alternatives to ggpointless and slendr

Other Infra & APIs 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 ggpointless or slendr.

See all ggpointless alternatives → · See all slendr alternatives →

Recent activity from ggpointless and slendr

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1mo agoslendrEphemeral uv Python environments remove the setup step
  2. 3mo agoggpointlessPictogram unit charts, gridline layers and a family of fading geoms
  3. 5mo agoggpointlessFourier and arch geoms, area fades and glowing points
  4. 7mo agoslendrgene_flow() separates migration rate from ancestry proportion
  5. 9mo agoslendrshiny made optional; SLiM 5.1 and Python 3.13 required
  6. 1y agoslendrconda activation reverted to a slower but reliable path
  7. 1y agoslendrBackends raised to SLiM 5.0, tskit 0.6.4 and msprime 1.3.4
  8. 1y agoslendrNon-neutral models arrive; slim() interface simplified
  9. 2y agoggpointlessgeom_catenary() draws a hanging chain
  10. 3y agoggpointlessgeom_chaikin() adds corner-cutting path smoothing
  11. 4y agoggpointlessgeom_lexis() and the female_leaders dataset

Frequently asked questions

What is the difference between ggpointless and slendr?

They serve adjacent needs but don't currently overlap on shipped themes. ggpointless and slendr 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.

Is ggpointless better than slendr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggpointless and slendr 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to ggpointless?

Top ggpointless alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "ggpointless alternatives" section above for the current picks, or visit /alternatives/ggpointless for the full list with editorial commentary on each.

What are the best alternatives to slendr?

Top slendr alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "slendr alternatives" section above for the current picks, or visit /alternatives/slendr for the full list with editorial commentary on each.