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cheapr vs errors

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

cheapr vs errors: at a glance

Featurecheaprerrors
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesperformance, parallelism, simd, c-apiuncertainty-propagation, measurement, r-quantities, formatting
Last editorial update6h ago1h ago
WebsiteVisit →Visit →

What is cheapr?

cheapr turned multi-threaded, and its next stop is a C++20 public API.

cheapr supplies lower-overhead replacements for base R's data manipulation primitives — subsetting, recycling, concatenation, attribute handling, data frame construction. Through 2025 it grew function by function: sset_df/sset_row/sset_col, list_as_df, cheapr_c, counts, str_coalesce, df_modify. The 1.5.0 release in April 2026 changed the nature of the package, adding parallelised math functions, user-settable thread counts, multi-threaded vector initialisers, and a SIMD-parallelised if_else_, with threading on by default at two threads.

Read the full cheapr trajectory →

What is errors?

errors keeps making uncertainty print the way each scientific field expects.

errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.

Read the full errors trajectory →

cheapr vs errors: editorial side-by-side

C
cheapr
ANALYTICS
0.0

cheapr turned multi-threaded, and its next stop is a C++20 public API.

◆ Current state

cheapr supplies lower-overhead replacements for base R's data manipulation primitives — subsetting, recycling, concatenation, attribute handling, data frame construction. Through 2025 it grew function by function: sset_df/sset_row/sset_col, list_as_df, cheapr_c, counts, str_coalesce, df_modify. The 1.5.0 release in April 2026 changed the nature of the package, adding parallelised math functions, user-settable thread counts, multi-threaded vector initialisers, and a SIMD-parallelised if_else_, with threading on by default at two threads.

◆ Where it's heading

Two arcs run at once. The visible one is parallelism: what began as single-threaded C shortcuts is becoming a threaded compute layer, and the notes state the C/C++ API is mid-rewrite with a stable form promised at 2.0.0 behind a C++20 requirement. The quieter one is R C API compliance — 1.5.1 removed R_MissingArg, R_UnboundValue, Rf_findVar and Rf_findVarinFrame, the non-API entry points being closed off upstream. The 1.5.x patches since are narrow crash fixes, which reads as consolidation before the 2.0.0 break.

◆ Prediction

Expect 2.0.0 to land the stable C/C++ API behind a C++20 toolchain floor, with more of the existing function surface threaded in the interim. The package has announced both moves in its own release notes.

E
errors
ANALYTICS
0.0

errors keeps making uncertainty print the way each scientific field expects.

◆ Current state

errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.

◆ Where it's heading

Two threads run through this history. One is formatting convergence: uncertainty has field-specific conventions, and the package has been absorbing them one contributed pull request at a time rather than imposing a single style. The other is keeping the errors class first-class everywhere R users work — vctrs methods for dplyr 1.0, a geom_errors() layer for ggplot2, missing-value and duplicate handling. Both are integration work, which is what a type-extension package mostly is.

◆ Prediction

Expect further formatting conventions to arrive as contributions, following PDG rounding and the decimals option, plus continued upkeep against ggplot2 aesthetic deprecations that have forced two of the last four releases.

Alternatives to cheapr and errors

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 cheapr or errors.

See all cheapr alternatives → · See all errors alternatives →

Recent activity from cheapr and errors

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

  1. 1mo agocheaprrep_len_ crash on shrinking lengths fixed
  2. 4mo agocheaprNon-API R internals removed
  3. 4mo agocheaprParallelised math, thread control, and a C API rewrite
  4. 1y agocheaprSubsetting speedups; sset_col negative-index crash fixed
  5. 1y agoerrorserrors 0.4.4 replaces deprecated geom_errorbarh()
  6. 1y agocheaprdf_modify added; attribute helpers renamed for intent
  7. 1y agocheaprcounts and str_coalesce added; reconstruct renamed to rebuild
  8. 1y agoerrorserrors 0.4.3 supports decimals in parenthesis notation
  9. 2y agoerrorserrors 0.4.2 adds PDG rounding rules
  10. 2y agoerrorserrors 0.4.1 handles missing values, fixes na.rm
  11. 3y agoerrorserrors 0.4.0 adds geom_errors() for automatic errorbars
  12. 5y agoerrorserrors 0.3.6

Frequently asked questions

What is the difference between cheapr and errors?

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

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cheapr and errors 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 cheapr?

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

What are the best alternatives to errors?

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