← Back to home
Comparison · Analytics

gigs vs riem

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

Shared themes:r-packageropensci

gigs vs riem: at a glance

Featuregigsriem
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesgrowth-standards, neonatal-health, r-package, ropensciweather-data, api-client, r-package, ropensci
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is gigs?

gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.

gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.

Read the full gigs trajectory →

What is riem?

A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.

riem pulls observations from the Iowa Environmental Mesonet's weather-station network. Its release history is two threads: successive rewrites of the HTTP and test-mocking stack, and a gradual tightening of function arguments that culminated in 1.0.0 removing convenient-but-dangerous defaults. Contributions come partly from IEM's own maintainer.

Read the full riem trajectory →

gigs vs riem: editorial side-by-side

G
gigs
ANALYTICS
0.0

gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.

◆ Current state

gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.

◆ Where it's heading

The package has moved from vector-in, vector-out conversion helpers to a data.frame-oriented interface with a single classify_growth() entry point that computes whatever outcomes the supplied columns allow. That is a shift from library to tool — the user describes their data rather than picking the right function. The trailing releases suggest the code is settled and the remaining work is packaging and discoverability.

◆ Prediction

With the API rewrite absorbed and hosting moved to rOpenSci, the next substantive release should add growth standards or outcomes rather than reshape the interface again.

R
riem
ANALYTICS
0.0

A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.

◆ Current state

riem pulls observations from the Iowa Environmental Mesonet's weather-station network. Its release history is two threads: successive rewrites of the HTTP and test-mocking stack, and a gradual tightening of function arguments that culminated in 1.0.0 removing convenient-but-dangerous defaults. Contributions come partly from IEM's own maintainer.

◆ Where it's heading

The HTTP thread has moved through httr to httr2, and mocking from vcr to httptest2 — following the broader rOpenSci HTTP-stack reorganisation rather than any need of its own. The API thread runs the other way: 1.0.0 removed defaults for date_start and station and flipped latlon to FALSE, trading convenience for callers being explicit about what they request. New arguments in the same release widened what a query can ask for.

◆ Prediction

With the API stabilised at 1.0.0 and the HTTP stack settled on httr2, the next release is more likely to expose additional IEM query parameters than to change plumbing again.

Alternatives to gigs and riem

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 gigs or riem.

See all gigs alternatives → · See all riem alternatives →

Recent activity from gigs and riem

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

  1. 1y agoriem1.0.0 removes defaults and adds query arguments
  2. 1y agogigsDocs and Zenodo archiving
  3. 1y agogigsDocs-only release; nothing changed internally
  4. 1y agogigsConversion API rewritten around data frames and classify_growth()
  5. 1y agoriemDrops the last vcr usage in favour of httptest2
  6. 2y agoriemTimezone and timestamp-parsing fixes
  7. 2y agogigsDocumentation fixes for autotest compliance
  8. 2y agogigsINTERGROWTH-21st fetal standards and input validation
  9. 2y agogigsPatch release with documentation update
  10. 4y agoriemMoves to httr2 and httptest2
  11. 4y agoriemSwitches to newer IEM metadata web services
  12. 9y agoriemReduces dependencies to tibble alone

Frequently asked questions

What is the difference between gigs and riem?

Both compete on the same themes — r-package, ropensci — within Analytics. gigs and riem 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 gigs better than riem?

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

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

What are the best alternatives to riem?

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