tidyr
tidyr replaced separate() with a family that says what it does.
Comparison · Analytics
PySCF vs statsmodels
A side-by-side editorial comparison of PySCF and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
PySCF vs statsmodels: at a glance
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.
What is statsmodels?
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
PySCF vs statsmodels: editorial side-by-side
PySCF
2.5ANALYTICS
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.
statsmodels
0.0ANALYTICS
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
◆ Current state
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
◆ Where it's heading
The library is being kept alive rather than developed: each release answers a break introduced upstream, and the interval between them is set by the NumPy, SciPy and pandas release calendars rather than by anything statsmodels is building. Two consecutive releases whose stated purpose was restoring the ability to import the package is the sharpest available signal about maintainer bandwidth. The 0.15 line remains a dev tag with no visible progress toward a release.
◆ Prediction
The next release is most likely another compatibility patch triggered by a NumPy, SciPy or pandas major, and nothing in these entries indicates 0.15 is close.
Alternatives to PySCF and statsmodels
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 PySCF or statsmodels.
modeltime
modeltime built conformal intervals in, then went quiet on features.
performance
performance keeps adding ways to check a model you have already fitted.
cmdstanpy
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
See all PySCF alternatives → · See all statsmodels alternatives →
Recent activity from PySCF and statsmodels
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 24d agoPySCFBethe-Salpeter equation, k-point RPA, and Windows compatibility
- 2mo agoPySCFPatch release: missing CP2K basis data in wheels, ECP loading fallback
- 3mo agoPySCFASE band structure interface, SOC-ECP for periodic DFT, PCM surface discretization
- 6mo agoPySCFNumPy 2.4 compatibility fix and smearing convergence tweak
- 6mo agoPySCFHigh-performance CCSDT/CCSDTQ, density-fitted NEVPT2, configurable einsum backend
- 8mo agostatsmodels0.14.6: restores importing under pandas 3.0
- 9mo agoPySCFMulti-state PDFT family lands with analytical gradients and QM/MM for periodic systems
- 1y agostatsmodels0.14.5: restores importing under SciPy 1.16
- 1y agostatsmodels0.14.4: Pyodide support
- 1y agostatsmodels0.14.3: NumPy 2 environments and corrected macOS builds
- 2y agostatsmodels0.14.2: full NumPy 2 compatibility
- 2y agostatsmodelsRelease 0.14.1
Frequently asked questions
What is the difference between PySCF and statsmodels?
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 PySCF better than statsmodels?
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 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.
What are the best alternatives to statsmodels?
Top statsmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "statsmodels alternatives" section above for the current picks, or visit /alternatives/statsmodels for the full list with editorial commentary on each.