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ageproR vs fastplyr

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

Shared themes:r-package

ageproR vs fastplyr: at a glance

FeatureageproRfastplyr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfisheries-science, stock-assessment, r-package, file-format-validationdataframe-performance, dplyr-alternative, query-optimization, cran-policy
Last editorial update45m ago2h ago
WebsiteVisit →Visit →

What is ageproR?

ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.

An R interface for building and validating AGEPRO input files — the configuration format for a fisheries stock projection program used in stock assessments. Releases come every few months and are dominated by one recurring problem: keeping up with the AGEPRO input file format, which has moved between VERSION 4.0 and VERSION 4.25 in both directions across this window. The package spends considerable effort on validation, version detection, and clear error messages when a file does not match.

Read the full ageproR trajectory →

What is fastplyr?

A fast dplyr stand-in that keeps finding new places to skip work entirely.

fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.

Read the full fastplyr trajectory →

ageproR vs fastplyr: editorial side-by-side

A
ageproR
ANALYTICS
0.0

ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.

◆ Current state

An R interface for building and validating AGEPRO input files — the configuration format for a fisheries stock projection program used in stock assessments. Releases come every few months and are dominated by one recurring problem: keeping up with the AGEPRO input file format, which has moved between VERSION 4.0 and VERSION 4.25 in both directions across this window. The package spends considerable effort on validation, version detection, and clear error messages when a file does not match.

◆ Where it's heading

The version-format churn is settling. Release 0.7.1 reverted the default back to VERSION 4.0 as a bugfix, and 0.9.0 finally set 4.25 as current while retaining a 4.0 compatibility string and improving the detection messages — a resolution rather than another reversal. With that stabilising, the substantive work has been the recruitment model coverage added in 0.8.0, which brought autocorrelated lognormal error structures into the package for the first time. Naming has been converging too, with output_stock_summary and summary_output_flag renamed to auxiliary variants to match the AGEPRO-GUI specification.

◆ Prediction

Expect the remaining recruitment models to be filled in against the AGEPRO specification, and the version handling to stay on 4.25 now that both formats are supported and validated rather than swapped.

F
fastplyr
ANALYTICS
0.0

A fast dplyr stand-in that keeps finding new places to skip work entirely.

◆ Current state

fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.

◆ Where it's heading

The optimization strategy has shifted from making individual functions fast to reasoning about expressions before evaluating them — 0.9.9 began marking simple operators as group-unaware so expressions built only from them are evaluated across the whole data frame rather than per group. That is a structural bet: the package increasingly inspects what you wrote to decide how much work is actually needed. Running alongside it is a steady tightening of build requirements, with C++17, R 4.5.0 and CRAN's C API rules all landing within a year.

◆ Prediction

Expect the group-unaware classification to widen to more functions, since each addition compounds across every grouped expression, and expect the dependency floors to keep rising as the package tracks CRAN's compiled-code policy.

Alternatives to ageproR and fastplyr

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 ageproR or fastplyr.

See all ageproR alternatives → · See all fastplyr alternatives →

Recent activity from ageproR and fastplyr

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

  1. 2mo agoageproRwrite_inp option flag detection fixed after 0.8.0 dependency changes
  2. 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
  3. 6mo agoageproRAGEPRO VERSION 4.25 becomes the default format, with 4.0 kept compatible
  4. 8mo agofastplyrIn-place sorting arrives with a C++17 requirement
  5. 10mo agofastplyrGroup-unaware expressions evaluated on the whole frame
  6. 1y agoageproRFour recruitment models added, including autocorrelated lognormal error
  7. 1y agofastplyrf_mutate and f_reframe complete the verb set
  8. 1y agoageproRagepro_inp_model initialisation aligned with the other model classes
  9. 1y agofastplyrDynamic argument evaluation and f_pull
  10. 1y agofastplyrf_fill added and grouped joins repaired
  11. 1y agoageproRVersion string read from line 1; invalid recruitment data blocks export
  12. 1y agoageproRInput file format reverted to VERSION 4.0 as a bugfix

Frequently asked questions

What is the difference between ageproR and fastplyr?

Both compete on the same themes — r-package — within Analytics. ageproR and fastplyr 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 ageproR better than fastplyr?

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

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

What are the best alternatives to fastplyr?

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