simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of eiaapi and quanteda.textmodels — release velocity, themes, recent moves, and the top alternatives to consider.
A thin EIA energy-data client whose whole story is making bulk queries survive the API's limits.
eiaapi wraps the US Energy Information Administration API: eia_get() issues a single query, and eia_backfill() decomposes a large date range into chunks the API will actually serve. Three releases across two years cover the package's entire history, and the second and third both exist because of eia_backfill().
Split out of quanteda, then quiet - one new classifier since 2020.
quanteda.textmodels holds the scaling and classification models factored out of quanteda's main package. The visible history is thin: a logistic regression classifier and a native C++ rewrite of svmlin in late 2020, an SVM default change in early 2021, and after that only compatibility work. The most recent release fixes a namespace break caused by quanteda 4.1.0 dropping RcppArmadillo.
eiaapi wraps the US Energy Information Administration API: eia_get() issues a single query, and eia_backfill() decomposes a large date range into chunks the API will actually serve. Three releases across two years cover the package's entire history, and the second and third both exist because of eia_backfill().
The package's development is a single problem being worked: pulling more data than one request allows. Version 0.1.2 introduced eia_backfill() for exactly that, and 0.2.0 fixed it for non-hourly frequencies by adding the frequency and data arguments so it matches eia_get()'s interface and by reworking Date handling. That convergence of the two functions' signatures is the visible design direction — one query idiom regardless of range size.
With the two functions now taking aligned arguments, further work most plausibly extends coverage to more EIA endpoints or response shapes. The entries name no specific target.
quanteda.textmodels holds the scaling and classification models factored out of quanteda's main package. The visible history is thin: a logistic regression classifier and a native C++ rewrite of svmlin in late 2020, an SVM default change in early 2021, and after that only compatibility work. The most recent release fixes a namespace break caused by quanteda 4.1.0 dropping RcppArmadillo.
The package now moves when its parent or a dependency moves, not on its own schedule. Four of the six most recent releases exist to track changes in quanteda, Matrix, or CRAN policy. The modelling decisions that were made - defaulting textmodel_svm() to the L2-regularized L2-loss dual solver, reducing svmlin to a single algorithm - have not been revisited since.
The next release most likely follows another upstream change in quanteda or a Matrix and Rcpp dependency rather than adding a model.
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 eiaapi or quanteda.textmodels.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all eiaapi alternatives → · See all quanteda.textmodels alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. eiaapi and quanteda.textmodels 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. eiaapi and quanteda.textmodels 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.
Top eiaapi alternatives in Analytics are ranked by recent ship velocity. Browse the "eiaapi alternatives" section above for the current picks, or visit /alternatives/eiaapi for the full list with editorial commentary on each.
Top quanteda.textmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "quanteda.textmodels alternatives" section above for the current picks, or visit /alternatives/quanteda-textmodels for the full list with editorial commentary on each.