tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
fable vs gutenbergr
A side-by-side editorial comparison of fable and gutenbergr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
fable vs gutenbergr: at a glance
What is fable?
fable keeps widening its model shelf, one econometric class at a time
fable is the tidyverts forecasting engine, and its releases are almost entirely about which model families it can express. The 0.4.x line added the vector-error-correction and VARIMA classes plus impulse-response methods; 0.5.0 adds fractional differencing via ARFIMA. Between those, the releases are CRAN-check patches and documentation passes.
What is gutenbergr?
gutenbergr has been rebuilt around caching and mirror resilience
gutenbergr downloads Project Gutenberg texts into R. Its recent releases are a sustained reliability push driven largely by one contributor: a download cache with its own function family, mirror discovery with a known-good fallback, a User-Agent string identifying the client, and a section-marker helper. The newest releases are narrow compatibility and duplication fixes on top of that base.
fable vs gutenbergr: editorial side-by-side
fable
0.0ANALYTICS
fable keeps widening its model shelf, one econometric class at a time
◆ Current state
fable is the tidyverts forecasting engine, and its releases are almost entirely about which model families it can express. The 0.4.x line added the vector-error-correction and VARIMA classes plus impulse-response methods; 0.5.0 adds fractional differencing via ARFIMA. Between those, the releases are CRAN-check patches and documentation passes.
◆ Where it's heading
The package is closing the gap with the older forecast package's model coverage while keeping the tidy model-specification grammar. Each substantive release is a new model class plus the generate()/IRF() plumbing to make it behave like the existing ones. Maintenance releases cluster around CRAN policy and ggplot2/tsibble compatibility rather than internal rewrites.
◆ Prediction
Expect the next substantive release to add another model class or extend generate()/IRF() coverage to the classes that still lack them, rather than change the modelling interface.
gutenbergr
0.0ANALYTICS
gutenbergr has been rebuilt around caching and mirror resilience
◆ Current state
gutenbergr downloads Project Gutenberg texts into R. Its recent releases are a sustained reliability push driven largely by one contributor: a download cache with its own function family, mirror discovery with a known-good fallback, a User-Agent string identifying the client, and a section-marker helper. The newest releases are narrow compatibility and duplication fixes on top of that base.
◆ Where it's heading
Development is aimed squarely at the failure modes of depending on a volunteer-run mirror network — cache locally, degrade gracefully when the mirror list cannot be parsed, and identify yourself politely to the servers. The version sequence in this feed is not monotonic, so recency here follows publication date rather than version number.
◆ Prediction
Further work should continue along the caching and mirror-handling line, with dataset refreshes as the Gutenberg catalogue changes.
Alternatives to fable and gutenbergr
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 fable or gutenbergr.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all fable alternatives → · See all gutenbergr alternatives →
Recent activity from fable and gutenbergr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agogutenbergrMirror listing adapted to readMDTable 0.4.0
- 3mo agogutenbergrFixed duplicated lines for multi-author works
- 3mo agogutenbergrMirror selection now uses the published mirror list
- 5mo agogutenbergrSection markers, a User-Agent string and usage vignettes
- 6mo agofablefable adds ARFIMA and fractional differencing ⚡
- 6mo agogutenbergrMirror fallback instead of hard errors
- 7mo agogutenbergrDownloads are now cached, with a cache management API
- 1y agofableIndexing and generate() fixes for VECM models
- 1y agofableVECM and VARIMA models land, plus IRF for VAR and ARIMA ⚡
- 2y agofablePatch for C++ R header changes
- 2y agofableCRAN check patch with generate() fixes
- 3y agofableTSLM forecasts gain Student's t intervals
Frequently asked questions
What is the difference between fable and gutenbergr?
Both compete on the same themes — r-stats — within Analytics. fable and gutenbergr 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 fable better than gutenbergr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fable and gutenbergr 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 fable?
Top fable alternatives in Analytics are ranked by recent ship velocity. Browse the "fable alternatives" section above for the current picks, or visit /alternatives/fable for the full list with editorial commentary on each.
What are the best alternatives to gutenbergr?
Top gutenbergr alternatives in Analytics are ranked by recent ship velocity. Browse the "gutenbergr alternatives" section above for the current picks, or visit /alternatives/gutenbergr for the full list with editorial commentary on each.