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assesslite vs sdsfun

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

assesslite vs sdsfun: at a glance

Featureassesslitesdsfun
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themescausal-inference, reproducibility, statistical-auditing, python-r-parityspatial-statistics, geodetector, spatial-clustering, rcpp
Last editorial update5h ago50m ago
WebsiteVisit →Visit →

What is assesslite?

Four releases in fifteen hours take causal assumption-checking from resampling to identification

AssessLite attacks the structural assumptions behind a causal finding and returns three-way verdicts — stable, unstable, or not resolvable — feeding proceed, conditional or abstain decisions, with an auditable JSON record validated against a shared schema. It runs natively in R and Python against one spec, with the Python engine reproducing R's coxph(ties=breslow) exactly. The entire 0.1.0-through-0.4.0 arc landed inside a single day in July 2026.

Read the full assesslite 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 →

assesslite vs sdsfun: editorial side-by-side

A
assesslite
ANALYTICS
0.0

Four releases in fifteen hours take causal assumption-checking from resampling to identification

◆ Current state

AssessLite attacks the structural assumptions behind a causal finding and returns three-way verdicts — stable, unstable, or not resolvable — feeding proceed, conditional or abstain decisions, with an auditable JSON record validated against a shared schema. It runs natively in R and Python against one spec, with the Python engine reproducing R's coxph(ties=breslow) exactly. The entire 0.1.0-through-0.4.0 arc landed inside a single day in July 2026.

◆ Where it's heading

The releases are cumulative, each restating the previous feature set and adding to it, so read them as one launch rather than four. The direction across that launch is clear: it started with resampling attacks (permutation, holdout, temporal split, subgroup), turned toward causal identification with declared DAGs and the backdoor criterion, then reached into genuinely dependent data with spatial and interference checks. The correctness work moves in step — the 0.3.0 Bonferroni adjustment fixed a holdout rule that was flagging roughly m times too often with m variants.

◆ Prediction

The project has repeatedly shipped what it previously listed as future work within days, so the next release most likely converts another declared gap rather than opening a new front.

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 assesslite 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 assesslite or sdsfun.

See all assesslite alternatives → · See all sdsfun alternatives →

Recent activity from assesslite and sdsfun

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

  1. 1mo agoassessliteAssessLite 0.4.0
  2. 1mo agoassessliteAssessLite 0.3.0
  3. 1mo agoassessliteAssessLite 0.2.0
  4. 1mo agoassessliteAssessLite 0.1.0
  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 assesslite and sdsfun?

They serve adjacent needs but don't currently overlap on shipped themes. assesslite 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 assesslite better than sdsfun?

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

Top assesslite alternatives in Analytics are ranked by recent ship velocity. Browse the "assesslite alternatives" section above for the current picks, or visit /alternatives/assesslite 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.