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feat: implement caching support for RNTuple reading #1513

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feat: implement caching support for RNTuple reading #1513

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f47c1f6
Implemented reading cache for RNTuples
ariostas Oct 2, 2025
f627c9f
Fixed issue with nonzero entry_start for deferred columns
ariostas Oct 2, 2025
1f56e43
Better test
ariostas Oct 2, 2025
50c2dc8
Reverted granularity of page ranges
ariostas Oct 2, 2025
849d040
Perform all reading operations in place
ariostas Oct 3, 2025
4df0044
A bit of cleanup
ariostas Oct 3, 2025
63a8ebb
Move cache to the cluster level
ariostas Oct 20, 2025
15bb397
Fix cuda tests
ariostas Oct 23, 2025
3202265
Copilot fixes
ariostas Oct 23, 2025
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20 changes: 14 additions & 6 deletions src/uproot/behaviors/RNTuple.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@
import uproot.language.python
import uproot.source.chunk
from uproot._util import no_filter, unset
from uproot.behaviors.TBranch import _regularize_array_cache


def iterate(
Expand Down Expand Up @@ -615,7 +616,7 @@ def arrays(
entry_start=None,
entry_stop=None,
decompression_executor=None, # TODO: Not implemented yet
array_cache="inherit", # TODO: Not implemented yet
array_cache="inherit",
library="ak", # TODO: Not implemented yet
backend="cpu",
interpreter="cpu",
Expand Down Expand Up @@ -659,7 +660,7 @@ def arrays(
is used. (Not implemented yet.)
array_cache ("inherit", None, MutableMapping, or memory size): Cache of arrays;
if "inherit", use the file's cache; if None, do not use a cache;
if a memory size, create a new cache of this size. (Not implemented yet.)
if a memory size, create a new cache of this size.
library (str or :doc:`uproot.interpretation.library.Library`): The library
that is used to represent arrays. Options are ``"np"`` for NumPy,
``"ak"`` for Awkward Array, and ``"pd"`` for Pandas. (Not implemented yet.)
Expand Down Expand Up @@ -725,6 +726,8 @@ def arrays(
[c.num_entries for c in clusters[start_cluster_idx:stop_cluster_idx]]
)

array_cache = _regularize_array_cache(array_cache, self.ntuple._file)

form, field_path = self.to_akform(
filter_name=filter_name,
filter_typename=filter_typename,
Expand All @@ -747,17 +750,22 @@ def arrays(
clusters_datas,
start_cluster_idx,
stop_cluster_idx,
pad_missing_element=True,
)

for key in target_cols:
if "column" in key:
key_nr = int(key.split("-")[1])
# Find how many elements should be padded at the beginning
n_padding = self.ntuple.column_records[key_nr].first_element_index
n_padding -= cluster_starts[start_cluster_idx]
n_padding = max(n_padding, 0)
if interpreter == "cpu":
content = self.ntuple.read_col_pages(
content = self.ntuple.read_cluster_range(
key_nr,
range(start_cluster_idx, stop_cluster_idx),
pad_missing_element=True,
start_cluster_idx,
stop_cluster_idx,
missing_element_padding=n_padding,
array_cache=array_cache,
)
elif interpreter == "gpu" and backend == "cuda":
content = content_dict[key_nr]
Expand Down
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