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performance vs PySCF

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

performance vs PySCF: at a glance

FeatureperformancePySCF
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesr-language, model-diagnostics, bayesian, easystatsquantum-chemistry, periodic-systems, coupled-cluster, gpu-acceleration
Last editorial update1h ago1d ago
WebsiteVisit →Visit →

What is performance?

performance keeps adding ways to check a model you have already fitted.

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

Read the full performance trajectory →

What is PySCF?

Quantum chemistry package adding whole method families every release.

PySCF is a Python-based quantum chemistry toolkit, and its release cadence is unusually feature-dense: each version lands multiple new electronic-structure methods rather than polishing existing ones. Recent releases have built out the GW/BSE excited-state stack, k-point RPA for periodic systems, higher-order coupled cluster, and multi-state PDFT with analytical gradients. Platform work runs alongside — Windows DLL compatibility, GPU4PySCF interfacing, and configurable einsum backends.

Read the full PySCF trajectory →

performance vs PySCF: editorial side-by-side

P
performance
ANALYTICS
0.0

performance keeps adding ways to check a model you have already fitted.

◆ Current state

performance is at 0.17.1, which added check_priors() for prior predictive checks on Bayesian models and gave check_overdispersion(), check_model() and check_predictions() arguments to control residual type and plot range. The releases before it are a similar mix: a -2LL criterion column in test_likelihoodratio(), Bayesian predictive checks routed through modelbased, and in 0.16.0 a set of breaking renames including RMSA to the correct RMSR.

◆ Where it's heading

Two consistent habits. Diagnostics keep gaining arguments to narrow what is examined — ppc_range, x_limits, maximum_dots, show_ci — which reads as a package being used on models large and awkward enough that the defaults stopped working. And simulated residuals via DHARMa keep displacing standard ones as the basis for the checks themselves.

◆ Prediction

With check_priors() newly added and Bayesian predictive checks now routed through modelbased, the next release most likely extends the Bayesian diagnostic set rather than reworking the frequentist checks.

P
PySCF
ANALYTICS
2.5

Quantum chemistry package adding whole method families every release.

◆ Current state

PySCF is a Python-based quantum chemistry toolkit, and its release cadence is unusually feature-dense: each version lands multiple new electronic-structure methods rather than polishing existing ones. Recent releases have built out the GW/BSE excited-state stack, k-point RPA for periodic systems, higher-order coupled cluster, and multi-state PDFT with analytical gradients. Platform work runs alongside — Windows DLL compatibility, GPU4PySCF interfacing, and configurable einsum backends.

◆ Where it's heading

Two arcs are visible. The methods arc is pushing toward periodic (PBC) parity with molecular calculations — PBC GW, PBC RPA, SOC-ECP for PBC DFT, QM/MM for periodic systems all landed in this window. The infrastructure arc is about getting PySCF to run where it previously did not: Windows, GPUs, alternative tensor-contraction backends.

◆ Prediction

The PBC catch-up should continue, since each release closes another gap between molecular and periodic implementations of the same method; the entries do not indicate which gap is next.

Alternatives to performance and PySCF

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 performance or PySCF.

See all performance alternatives → · See all PySCF alternatives →

Recent activity from performance and PySCF

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

  1. 24d agoPySCFBethe-Salpeter equation, k-point RPA, and Windows compatibility
  2. 1mo agoperformancecheck_priors() added; overdispersion plots use simulated residuals
  3. 2mo agoPySCFPatch release: missing CP2K basis data in wheels, ECP loading fallback
  4. 2mo agoperformance-2LL criterion column and unified Bayesian predictive checks
  5. 3mo agoPySCFASE band structure interface, SOC-ECP for periodic DFT, PCM surface discretization
  6. 6mo agoperformanceBreaking renames plus point-count and CI controls in check_model()
  7. 6mo agoPySCFNumPy 2.4 compatibility fix and smearing convergence tweak
  8. 6mo agoPySCFHigh-performance CCSDT/CCSDTQ, density-fitted NEVPT2, configurable einsum backend
  9. 8mo agoperformancecheck_autocorrelation() methods for DHARMa objects
  10. 9mo agoPySCFMulti-state PDFT family lands with analytical gradients and QM/MM for periodic systems
  11. 10mo agoperformanceFixes CRAN checks after an rstanarm update
  12. 11mo agoperformancetinytable output format in display()

Frequently asked questions

What is the difference between performance and PySCF?

They serve adjacent needs but don't currently overlap on shipped themes. PySCF is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is performance better than PySCF?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. PySCF is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to performance?

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

What are the best alternatives to PySCF?

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