← Back to home
Comparison · Analytics

fastml vs rphylopic

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

fastml vs rphylopic: at a glance

Featurefastmlrphylopic
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesautoml, tidymodels, survival analysis, cross-validationphylogenetics, data-visualization, r-package, ggplot2
Last editorial update1h ago4h ago
WebsiteVisit →Visit →

What is fastml?

fastml added survival modelling and leakage-proof resampling, moving past classification and regression.

A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.

Read the full fastml trajectory →

What is rphylopic?

The R package that puts organism silhouettes on plots keeps widening where they can be drawn.

rphylopic fetches PhyloPic silhouettes and places them into R graphics — base plots, ggplot2 layers, legends, and now phylogenetic trees and igraph networks. The 1.x line has been consistent about two things: adding a new plotting context per release, and steadily replacing its early sizing vocabulary with explicit width and height arguments. Attribution handling is unusually developed for a package this size, with permalinks and per-image credit built into the retrieval functions.

Read the full rphylopic trajectory →

fastml vs rphylopic: editorial side-by-side

F
fastml
ANALYTICS
0.0

fastml added survival modelling and leakage-proof resampling, moving past classification and regression.

◆ Current state

A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.

◆ Where it's heading

The package is moving from convenience wrapper to something that has to be defensible statistically. Nested cross-validation, fold-wise rather than up-front imputation, and explicit leakage checks are all corrections to the shortcuts that make AutoML easy and its scores optimistic. Survival adds a third task type alongside classification and regression, and it arrived with its own metrics rather than being bolted onto the existing ones. Note the entry body is cut off at 8,000 characters, so the release is larger than what is shown.

◆ Prediction

Expect the remaining survival engines to fill in and the sandboxing of custom preprocessing to tighten, since both were still being iterated on within this same release's commit list.

R
rphylopic
ANALYTICS
0.0

The R package that puts organism silhouettes on plots keeps widening where they can be drawn.

◆ Current state

rphylopic fetches PhyloPic silhouettes and places them into R graphics — base plots, ggplot2 layers, legends, and now phylogenetic trees and igraph networks. The 1.x line has been consistent about two things: adding a new plotting context per release, and steadily replacing its early sizing vocabulary with explicit width and height arguments. Attribution handling is unusually developed for a package this size, with permalinks and per-image credit built into the retrieval functions.

◆ Where it's heading

Development is expanding the set of places a silhouette can appear rather than changing what the package does. Base plots came first, then ggplot2 aesthetics and legend glyphs, then trees, then network vertices via an igraph shape registered automatically when both packages load. The other running thread is defensive maintenance against upstream churn: retries on failed API calls, fixes for ggplot2 4.0.0, and now an in-memory cache so repeated calls stop hammering the PhyloPic API. The ysize and size deprecation, opened in 1.5.0, is now complete and the arguments are scheduled for removal.

◆ Prediction

The deprecated ysize and size arguments look set to be removed in the next release, and on the pattern of the last four, another plotting context is a likelier addition than a change to the retrieval layer.

Alternatives to fastml and rphylopic

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 fastml or rphylopic.

See all fastml alternatives → · See all rphylopic alternatives →

Recent activity from fastml and rphylopic

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

  1. 1mo agorphylopicSilhouettes become igraph vertices; API responses cached
  2. 8mo agofastmlVersion 0.7.5
  3. 8mo agorphylopicBase R phylogenies gain silhouette annotation
  4. 1y agofastmlEngine-specific tuning, imbalance handling and explainability
  5. 1y agofastmlSingle-workflow evaluation fix
  6. 1y agofastmlVersion 0.5.0
  7. 1y agorphylopicExplicit width and height replace the old sizing arguments
  8. 2y agorphylopicSilhouette legends and attribution permalinks
  9. 2y agorphylopicSilhouette resolution helper and safer colour defaults
  10. 2y agorphylopicRendering dependencies bumped for grImport2 and rsvg

Frequently asked questions

What is the difference between fastml and rphylopic?

They serve adjacent needs but don't currently overlap on shipped themes. fastml and rphylopic 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 fastml better than rphylopic?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastml and rphylopic 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.

What are the best alternatives to fastml?

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

What are the best alternatives to rphylopic?

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