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ojoregex vs sdsfun

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

Shared themes:r-package

ojoregex vs sdsfun: at a glance

Featureojoregexsdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themescriminal-justice, court-data, r-package, text-classificationspatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update5h ago1h ago
WebsiteVisit →Visit →

What is ojoregex?

Oklahoma's court-data nonprofit maintains the regex layer that turns charge text into categories.

ojoregex is Open Justice Oklahoma's pattern library for classifying criminal charge descriptions from court records — the unglamorous translation layer between free-text charge fields and analysable categories. Its entire release history reached this feed as four tags published within three minutes, so the feed order reflects a backfill rather than a shipping cadence. Release notes are merge references rather than descriptions, which limits how much can be read from the changelog alone.

Read the full ojoregex trajectory →

What is sdsfun?

A spatial-statistics utility package exists to be depended on, and is built accordingly.

sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.

Read the full sdsfun trajectory →

ojoregex vs sdsfun: editorial side-by-side

O
ojoregex
ANALYTICS
0.0

Oklahoma's court-data nonprofit maintains the regex layer that turns charge text into categories.

◆ Current state

ojoregex is Open Justice Oklahoma's pattern library for classifying criminal charge descriptions from court records — the unglamorous translation layer between free-text charge fields and analysable categories. Its entire release history reached this feed as four tags published within three minutes, so the feed order reflects a backfill rather than a shipping cadence. Release notes are merge references rather than descriptions, which limits how much can be read from the changelog alone.

◆ Where it's heading

What the notes do show is a package alternating between domain corrections and R tooling upkeep: a fix to property-crime matching in one release, dplyr select semantics in the next. That is the expected shape for a regex catalogue — accuracy work arrives as individual charge types get miscategorised in real analyses, and the rest is keeping the package installable against a moving tidyverse. Contributions come from a small internal team, and the vignette work referenced in the earliest tag suggests the pattern list doubles as documentation for analysts.

◆ Prediction

The visible pattern is incremental match fixes as charge types surface in use; the release notes carry too little detail to predict anything beyond that without reading the underlying pull requests.

S
sdsfun
ANALYTICS
0.0

A spatial-statistics utility package exists to be depended on, and is built accordingly.

◆ Current state

sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.

◆ Where it's heading

This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.

◆ Prediction

Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.

Alternatives to ojoregex and sdsfun

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 ojoregex or sdsfun.

See all ojoregex alternatives → · See all sdsfun alternatives →

Recent activity from ojoregex and sdsfun

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

  1. 1mo agoojoregexPatch for dplyr select semantics
  2. 1mo agoojoregexojoregex v0.10.0
  3. 1mo agoojoregexNamespace prefixes fixed, plus a property-crime match bug
  4. 1mo agoojoregexFirst tagged release, carrying the whole development history
  5. 10mo agosdsfunPackage load stops touching the RNG state
  6. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  7. 1y agosdsfunMissing-value handling added to linear trend removal
  8. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  9. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  10. 1y agosdsfunFast geodetector q-value estimator added

Frequently asked questions

What is the difference between ojoregex and sdsfun?

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

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

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

What are the best alternatives to sdsfun?

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