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diff raises RecursionError when n is around 1000 or more

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  • #11704 by @headtr1ck — merged

Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
72/100
Issue type
Bug
Clarity
Clearly specified
Activity status
Active
Tech stack
python
Domain
data

Research direction

The recursion is in Dataset.diff in xarray/core/dataset.py, where return difference.diff(dim, n - 1) runs once per order of difference (around line 8103 in the traceback). Start there and replace the self-call with a loop that applies the single-order difference n times. Done when da.diff("x", n=1200) on a 3,000-value array returns 1,800 values, matching numpy.diff, and the existing diff tests still pass.

Written by the indexing model from the issue text.

Description

bug
What happened?

While testing an experimental version of Perch, we found the following and figured it was worth a report.

DataArray.diff and Dataset.diff raise RecursionError once n gets near Python's recursion limit (1000 by default). n=900 works and n=1000 fails.

What did you expect to happen?

The same result numpy.diff gives. For 3,000 values and n=1200, that is 1,800 values.

Minimal Complete Verifiable Example
# /// script
# requires-python = ">=3.12"
# dependencies = [
#   "xarray[complete]@git+https://github.com/pydata/xarray.git@main",
# ]
# ///
#
# This script automatically imports the development branch of xarray to check for issues.
# Please delete this header if you have _not_ tested this script with `uv run`!

import numpy as np
import xarray as xr

xr.show_versions()

values = np.arange(3000.0) ** 2
da = xr.DataArray(values, dims="x")

print(np.diff(values, n=1200).shape)  # (1800,)
print(da.diff("x", n=900).shape)      # (2100,)
da.diff("x", n=1200)                  # RecursionError
Steps to reproduce

Save the example as issue.py and run uv run issue.py.

MVCE confirmation
  • Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
  • Complete example — the example is self-contained, including all data and the text of any traceback.
  • Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
  • New issue — a search of GitHub Issues suggests this is not a duplicate.
  • Recent environment — the issue occurs with the latest version of xarray and its dependencies.
Relevant log output
Traceback (most recent call last):
  File "issue.py", line 21, in <module>
    da.diff("x", n=1200)                  # RecursionError
    ~~~~~~~^^^^^^^^^^^^^
  File ".../site-packages/xarray/core/dataarray.py", line 5167, in diff
    ds = self._to_temp_dataset().diff(n=n, dim=dim, label=label)
  File ".../site-packages/xarray/core/dataset.py", line 8103, in diff
    return difference.diff(dim, n - 1)
           ~~~~~~~~~~~~~~~^^^^^^^^^^^^
  File ".../site-packages/xarray/core/dataset.py", line 8103, in diff
    return difference.diff(dim, n - 1)
           ~~~~~~~~~~~~~~~^^^^^^^^^^^^
  [Previous line repeated many more times]
  ...
  File ".../site-packages/xarray/core/indexing.py", line 501, in __init__
    k = as_integer_slice(k)
  File ".../site-packages/xarray/core/indexing.py", line 454, in as_integer_slice
    start = as_integer_or_none(value.start)
RecursionError: maximum recursion depth exceeded
Anything else we need to know?

Dataset.diff handles n > 1 by calling itself with n - 1, so each order of difference adds a stack frame:

if n > 1:
    return difference.diff(dim, n - 1)

A loop doing the same thing n times would avoid the limit.

Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.14.2 (main, Dec  9 2025, 19:29:30) [Clang 21.1.4 ]
python-bits: 64
OS: Darwin
OS-release: 25.2.0
machine: arm64
processor: arm
byteorder: little
LC_ALL: None
LANG: None
LOCALE: ('C', 'UTF-8')
libhdf5: 1.14.6
libnetcdf: 4.9.3

xarray: 2026.9.1.dev52+g07f7270ee
pandas: 3.0.6
numpy: 2.5.3
scipy: 1.18.1
netCDF4: 1.7.4
pydap: 3.5.11
h5netcdf: 1.8.1
h5py: 3.16.0
zarr: 3.4.1
cftime: 1.6.6
nc_time_axis: 1.4.1
iris: None
bottleneck: 1.6.0
dask: 2026.8.0
distributed: 2026.8.0
matplotlib: 3.11.2
cartopy: 0.26.0
seaborn: 0.13.2
numbagg: 0.9.6
fsspec: 2026.9.0
cupy: None
pint: None
sparse: 0.19.2
flox: 0.11.2
numpy_groupies: 0.13.0
setuptools: None
pip: None
conda: None
pytest: None
mypy: None
IPython: None
sphinx: None
Dominant language
Python
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