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Comparison · DevOps
pyjanitor vs uproot5
A side-by-side editorial comparison of pyjanitor and uproot5 — release velocity, themes, recent moves, and the top alternatives to consider.
pyjanitor vs uproot5: at a glance
What is pyjanitor?
pyjanitor is folding its verbs into pandas groupby objects, one release at a time.
pyjanitor is at v0.32.23, whose changelog states outright that it contains no new features, no bug fixes and no breaking changes — only two dependency bumps. The work that mattered ran a month or two earlier: an assign method on groupby objects, support for referencing columns with pd.col, the migration of by methods onto groupby objects with deprecation warnings for the old forms, and a pivot_longer refactor for speed.
What is uproot5?
Uproot quietly made RNTuple the default write format — filed under 'chore'.
Uproot ships small, frequent 5.7.x releases in which the RNTuple work dominates and is often buried below the feature list. Since switching the default write format to RNTuple in 5.7.0, the releases have been about making that path complete: entry bounds and report=True for RNTuple.iterate, GPU interpretation of RNTuple data with nvCOMP decompression, support for the v1.0.1.0 format, and the library kwarg finished. Two of the six releases in this window list no new features at all.
pyjanitor vs uproot5: editorial side-by-side
pyjanitor
0.0DEVOPS
pyjanitor is folding its verbs into pandas groupby objects, one release at a time.
◆ Current state
pyjanitor is at v0.32.23, whose changelog states outright that it contains no new features, no bug fixes and no breaking changes — only two dependency bumps. The work that mattered ran a month or two earlier: an assign method on groupby objects, support for referencing columns with pd.col, the migration of by methods onto groupby objects with deprecation warnings for the old forms, and a pivot_longer refactor for speed.
◆ Where it's heading
The direction is convergence with pandas rather than divergence from it. Instead of offering parallel verbs that take a by argument, pyjanitor is attaching its operations to the groupby object pandas already gives you, and adopting pd.col-style column references where they exist. The recent releases suggest that push has paused into dependency maintenance.
◆ Prediction
With by methods migrated and their old forms warning, the next substantive release most likely removes the deprecated groupby entry points rather than adding verbs.
uproot5
0.0DEVOPS
Uproot quietly made RNTuple the default write format — filed under 'chore'.
◆ Current state
Uproot ships small, frequent 5.7.x releases in which the RNTuple work dominates and is often buried below the feature list. Since switching the default write format to RNTuple in 5.7.0, the releases have been about making that path complete: entry bounds and report=True for RNTuple.iterate, GPU interpretation of RNTuple data with nvCOMP decompression, support for the v1.0.1.0 format, and the library kwarg finished. Two of the six releases in this window list no new features at all.
◆ Where it's heading
This is a migration project wearing patch-release clothing. The direction is that RNTuple, ROOT's newer columnar format, becomes what Uproot writes and reads by default, with the older TTree path maintained rather than developed. The GPU decompression work points further out: reading physics data straight into accelerator memory rather than staging it through the CPU. Expect the remaining gaps to keep surfacing as bug fixes in the RNTuple path as more of the field writes in the new format.
◆ Prediction
Continued 5.7.x patches closing RNTuple feature parity with TTree, with the GPU and nvCOMP path the most likely area to gain rather than just get fixed.
Alternatives to pyjanitor and uproot5
Other DevOps 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 pyjanitor or uproot5.
rlang
rlang moved tidyeval off R's private internals and onto official C API.
purrr
purrr finished a decade of deprecations and picked up a parallel backend.
PyTables
PyTables opened a path around HDF5's filter pipeline, then chased Python's runtime.
plumber
R's API framework grew its serializer catalogue, then went quiet on features.
distributed
Dask's scheduler spent the year deleting deprecated API, not adding surface.
See all pyjanitor alternatives → · See all uproot5 alternatives →
Recent activity from pyjanitor and uproot5
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agouproot55.7.5: RNTuple library kwarg finished, byte-swap fix in dtype interpretation
- 3mo agouproot5Version 5.7.4
- 4mo agopyjanitorDependency bumps only; no functional changes
- 4mo agouproot55.7.3: corrupted free_num_bytes and mktree subdirectory fixes
- 4mo agopyjanitorCodecov GitHub Action bumped to v6
- 4mo agopyjanitorpivot_longer refactored for speed on pandas
- 5mo agouproot55.7.2: GPU interpretation of RNTuple data with nvCOMP decompression
- 5mo agopyjanitorby methods migrate to groupby objects, old forms deprecated
- 6mo agopyjanitorpd.col column references supported in DataFrame operations
- 6mo agopyjanitorassign method added to groupby objects
- 6mo agouproot5Version 5.7.1
- 6mo agouproot55.7.0: RNTuple becomes the default write format ⚡
Frequently asked questions
What is the difference between pyjanitor and uproot5?
They serve adjacent needs but don't currently overlap on shipped themes. pyjanitor and uproot5 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 pyjanitor better than uproot5?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. pyjanitor and uproot5 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 DevOps products to evaluate alongside.
What are the best alternatives to pyjanitor?
Top pyjanitor alternatives in DevOps are ranked by recent ship velocity. Browse the "pyjanitor alternatives" section above for the current picks, or visit /alternatives/pyjanitor for the full list with editorial commentary on each.
What are the best alternatives to uproot5?
Top uproot5 alternatives in DevOps are ranked by recent ship velocity. Browse the "uproot5 alternatives" section above for the current picks, or visit /alternatives/uproot for the full list with editorial commentary on each.