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bonsai vs silx

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

bonsai vs silx: at a glance

Featurebonsaisilx
SectorAnalyticsAnalytics
Velocity score0.05.0
Sparks · 30d00
Top themestidymodels, gradient-boosting, engines, lightgbmscientific-computing, data-visualization, synchrotron, qt
Last editorial update5d ago2h ago
WebsiteVisit →Visit →

What is bonsai?

bonsai keeps widening tidymodels' boosted-tree engine bench, catboost most recently

bonsai exists to attach non-core tree engines to parsnip's boost_tree() and rand_forest(), and the release history reads as a steady accumulation of them: partykit, aorsf, lightgbm, and now catboost. The 0.4.x line is spent making catboost behave like a full tidymodels citizen rather than adding anything new.

Read the full bonsai trajectory →

What is silx?

silx settles into maintenance a release after its PySide6 migration

silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.

Read the full silx trajectory →

bonsai vs silx: editorial side-by-side

B
bonsai
ANALYTICS
0.0

bonsai keeps widening tidymodels' boosted-tree engine bench, catboost most recently

◆ Current state

bonsai exists to attach non-core tree engines to parsnip's boost_tree() and rand_forest(), and the release history reads as a steady accumulation of them: partykit, aorsf, lightgbm, and now catboost. The 0.4.x line is spent making catboost behave like a full tidymodels citizen rather than adding anything new.

◆ Where it's heading

Each engine follows the same arc — land it, then close the gaps that keep it from tuning cleanly (parameter naming, multi_predict, threading, case weights). Recent work is squarely in that second phase for catboost, with dials supplying the matching parameter objects on its own release schedule. Bug-fix density is high relative to new surface.

◆ Prediction

Expect the catboost integration to keep filling in tuning and GPU-related arguments before any further engine is added; the entries give no signal about which engine would come next.

S
silx
ANALYTICS
5.0

silx settles into maintenance a release after its PySide6 migration

◆ Current state

silx is in the quiet phase after a generational release. 3.1.1 is a single fix to FitWidget loading a fit function from file. The release before it, 3.1.0, was the first real feature work since the migration - asinh axis scaling, twilight colormaps, and dark-theme icons - and 3.0.1 was similarly small. The 3.0.0 cut that reset the Qt binding and Python floor still defines what the line is doing.

◆ Where it's heading

The cadence has slowed markedly since April, and the content has shifted from structural change to plotting and colormap refinement. That is the expected shape after a binding migration: downstream beamline code needs a stable target, so the project trades feature velocity for a quiet surface. The gap between 3.0.1 in May and 3.1.0 in August is the clearest signal of the deliberate slowdown.

◆ Prediction

Expect further point releases servicing the plotting and fitting widgets rather than another structural change, with feature work continuing to arrive in the 3.1.x minors rather than patches.

Alternatives to bonsai and silx

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 bonsai or silx.

See all bonsai alternatives → · See all silx alternatives →

Recent activity from bonsai and silx

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

  1. 5h agosilxFitWidget fix for loading a fit function from file
  2. 9d agosilx3.1.0: asinh axis scaling, twilight colormaps, dark-theme icons
  3. 2mo agobonsaicatboost gains multi_predict() and corrected tuning parameters
  4. 3mo agosilx3.0.1: silx view fails to disable HDF5 file locking
  5. 3mo agosilx3.0.0: PySide6 becomes the default Qt binding, Python 3.10 required
  6. 3mo agosilx3.0.0rc1: release candidate for the PySide6 migration
  7. 1y agobonsaicatboost engine added to boost_tree()
  8. 1y agosilx2.2.2: plot axes limits, OpenGL axes and libhdf5 1.14 fixes
  9. 1y agobonsailightgbm accepts sparse matrices for fit and predict
  10. 2y agobonsaiaorsf fit failure in multisession workers fixed
  11. 2y agobonsaiaorsf engine added; lightgbm gains dataset params and case weights
  12. 3y agobonsailightgbm num_leaves becomes tunable; alias arguments disallowed

Frequently asked questions

What is the difference between bonsai and silx?

They serve adjacent needs but don't currently overlap on shipped themes. silx is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 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.

Is bonsai better than silx?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. silx is currently shipping more aggressively (velocity 5.0 vs 0.0), with 0 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.

What are the best alternatives to bonsai?

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

What are the best alternatives to silx?

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