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A side-by-side editorial comparison of afcharts and writeAlizer — release velocity, themes, recent moves, and the top alternatives to consider.
UK government chart styling in ggplot2, chasing ggplot2 v4 and stretching its palette to five.
afcharts supplies the UK Analysis Function's chart styling for ggplot2, as a theme, colour and fill scales, and a use_afcharts() call that applies the styling globally. Version 0.5.1 extends the sequential palette to five shades so it can carry quintile data such as deprivation bands, renames the na_colour argument to na.value, and adds a reset argument to switch the styling back off. The package began as a first release derived from sgplot and has had three releases in roughly two years.
Six months of releases and not one of them touched the scoring models
writeAlizer generates predicted writing-quality scores from features produced by Coh-Metrix, ReaderBench and GAMET, downloading its trained scoring models on demand. Every release in this window — nine of them between September 2025 and February 2026 — is about that download path rather than the scoring: classed error conditions, checksum verification, an offline mode, a mockable artifact directory, and dependency reporting for the model families a user actually invokes.
afcharts supplies the UK Analysis Function's chart styling for ggplot2, as a theme, colour and fill scales, and a use_afcharts() call that applies the styling globally. Version 0.5.1 extends the sequential palette to five shades so it can carry quintile data such as deprivation bands, renames the na_colour argument to na.value, and adds a reset argument to switch the styling back off. The package began as a first release derived from sgplot and has had three releases in roughly two years.
The work splits between palette design and keeping the styling composable. On the design side the sequential palette growing to five shades is driven by a specific reporting need rather than aesthetics, since quintiles are a standard unit in UK official statistics. On the mechanical side, the na.value rename was forced by ggplot2 v4.0.1, theme_af() now respects options set by an earlier use_afcharts() call, and a reset argument acknowledges that global styling needs an off switch. These are the problems a styling package hits once people use it inside larger documents.
Expect continued adjustment to ggplot2 v4, since the na.value rename is unlikely to be the only argument affected, and further palette work driven by the reporting formats government analysts actually publish. As a sibling to aftables in the same Analysis Function family, it is likely to keep tracking that guidance rather than setting its own direction.
writeAlizer generates predicted writing-quality scores from features produced by Coh-Metrix, ReaderBench and GAMET, downloading its trained scoring models on demand. Every release in this window — nine of them between September 2025 and February 2026 — is about that download path rather than the scoring: classed error conditions, checksum verification, an offline mode, a mockable artifact directory, and dependency reporting for the model families a user actually invokes.
The package is being made safe to distribute. CRAN's policy on packages that reach the internet drove the first wave — graceful failure, tests that preflight their URLs and skip, examples seeded from a local mock model — and 1.7.0 turned the accumulated fixes into structure with named error classes for each failure mode. Only 1.7.2 adds anything a user would ask for: filename handling for Coh-Metrix and GAMET outputs that arrive as paths.
With the artifact registry hardened and documented, the pressure that produced nine releases in six months should ease, and attention can return to the models themselves — the vignette on scoring-model development added in 1.7.2 hints at that. Nothing here promises new models.
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 afcharts or writeAlizer.
mice can finally predict, not just estimate, from multiply imputed data.
A market-microstructure toolkit that keeps adding estimators as the papers land.
A vowel-analysis package trimming dependencies after an email address got it archived.
The R half of the EMU speech database system, fixing what was quietly broken.
A Bayesian model-averaging package spending its 2.0 on memory, not methods.
tidyplots keeps rebuilding its own foundations rather than layering around them.
See all afcharts alternatives → · See all writeAlizer alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. afcharts and writeAlizer 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. afcharts and writeAlizer 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.
Top afcharts alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "afcharts alternatives" section above for the current picks, or visit /alternatives/afcharts for the full list with editorial commentary on each.
Top writeAlizer alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "writeAlizer alternatives" section above for the current picks, or visit /alternatives/writealizer for the full list with editorial commentary on each.