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Fix Upstream CI NaT issues - #11340

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ianhi:ian/upstream-ci
Jun 3, 2026
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Fix Upstream CI NaT issues#11340
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ianhi:ian/upstream-ci

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@ianhi

@ianhiianhi commented May 15, 2026

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Description

Two separate things:

I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.

cc @dcherian

Checklist

  • [NA] Closes #xxxx
  • [NA] Tests added
  • User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst

AI Disclosure

  • This PR contains AI-generated content.
    • I have tested any AI-generated content in my PR.
    • I take responsibility for any AI-generated content in my PR. Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}

@ianhiianhi mentioned this pull request May 15, 2026
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Comment threadxarray/tests/test_duck_array_ops.py
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LGTM

spencerkclark
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.

I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.

Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit to betolink/icechunk that referenced this pull request May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi added 2 commits May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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🎉

@Illviljan

Illviljan commented May 31, 2026

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Lots of mypy errors, is it because pip is not installed?

Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

@keewiskeewis mentioned this pull request Jun 2, 2026
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I have one question regarding the construction of delta, other wise this looks good to me.

Comment threadxarray/coding/times.py
@keewis
keewis merged commit c3a398e into pydata:mainJun 3, 2026
45 of 47 checks passed
sdiebolt pushed a commit to sdiebolt/xarray that referenced this pull request Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Conversation
@ianhi
@ianhiianhi
commented
May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
@ianhiianhi
mentioned this pull request
May 15, 2026
 Merged

@ianhiianhi
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run-upstream
Run upstream CI
label
May 15, 2026
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Comment threadxarray/tests/test_duck_array_ops.py
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LGTM
spencerkclark
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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May 31, 2026
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🎉
@Illviljan
Illviljan
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May 31, 2026

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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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Jun 2, 2026
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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
keewis
merged commit c3a398e
into
pydata:mainJun 3, 2026

45 of 47 checks passed

sdiebolt pushed a commit
to sdiebolt/xarray
that referenced
this pull request
Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Conversation
@ianhi
@ianhiianhi
commented
May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
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 Merged

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Run upstream CI
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Comment threadxarray/tests/test_duck_array_ops.py
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LGTM
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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May 31, 2026
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🎉
@Illviljan
Illviljan
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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
keewis
merged commit c3a398e
into
pydata:mainJun 3, 2026

45 of 47 checks passed

sdiebolt pushed a commit
to sdiebolt/xarray
that referenced
this pull request
Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
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ianhi:ian/upstream-ci
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@ianhi
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May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
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LGTM
spencerkclark
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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🎉
@Illviljan
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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
keewis
merged commit c3a398e
into
pydata:mainJun 3, 2026

45 of 47 checks passed

sdiebolt pushed a commit
to sdiebolt/xarray
that referenced
this pull request
Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '
Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
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@ianhi
@ianhiianhi
commented
May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
@ianhiianhi
mentioned this pull request
May 15, 2026
 Merged

@ianhiianhi
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run-upstream
Run upstream CI
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Comment threadxarray/tests/test_duck_array_ops.py
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LGTM
spencerkclark
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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May 31, 2026
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🎉
@Illviljan
Illviljan
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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
keewis
merged commit c3a398e
into
pydata:mainJun 3, 2026

45 of 47 checks passed

sdiebolt pushed a commit
to sdiebolt/xarray
that referenced
this pull request
Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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@dcheriandcheriandcherian approved these changes
@kmuehlbauerkmuehlbauerkmuehlbauer approved these changes
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Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Conversation
@ianhi
@ianhiianhi
commented
May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
@ianhiianhi
mentioned this pull request
May 15, 2026
 Merged

@ianhiianhi
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run-upstream
Run upstream CI
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May 15, 2026
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LGTM
spencerkclark
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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May 31, 2026
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🎉
@Illviljan
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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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Jun 2, 2026
 Open

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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
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merged commit c3a398e
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Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
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@ianhi
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May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
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Comment threadxarray/tests/test_duck_array_ops.py
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LGTM
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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🎉
@Illviljan
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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
keewis
merged commit c3a398e
into
pydata:mainJun 3, 2026

45 of 47 checks passed

sdiebolt pushed a commit
to sdiebolt/xarray
that referenced
this pull request
Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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@dcheriandcheriandcherian approved these changes
@kmuehlbauerkmuehlbauerkmuehlbauer approved these changes
@keewiskeewiskeewis left review comments
@spencerkclarkspencerkclarkspencerkclark approved these changes

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Fix Upstream CI NaT issues by ianhi · Pull Request #11340 · pydata/xarray · GitHub
Skip to content
Fix Upstream CI NaT issues - #11340
Merged
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Jun 3, 2026
Merged
Fix Upstream CI NaT issues#11340
keewis merged 4 commits into
pydata:mainfrom 
ianhi:ian/upstream-ci
Conversation
@ianhi
@ianhiianhi
commented
May 15, 2026

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Description
Two separate things:
I ended up consolidating the two methods in code/times by a bit to avoid writing the same fix twice. They had almost exactly the same code path.
cc @dcherian
Checklist
  • [NA] Closes #xxxx
  • [NA] Tests added
  •  User visible changes (including notable bug fixes) are documented in whats-new.rst
  • [NA] New functions/methods are listed in api.rst
AI Disclosure
  •  This PR contains AI-generated content.

    •  I have tested any AI-generated content in my PR.
    •  I take responsibility for any AI-generated content in my PR.
Tools: {e.g., Claude, Codex, GitHub Copilot, ChatGPT, etc.}
@ianhiianhi
mentioned this pull request
May 15, 2026
 Merged

@ianhiianhi
added
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run-upstream
Run upstream CI
label
May 15, 2026
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Comment threadxarray/tests/test_duck_array_ops.py
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LGTM
spencerkclark
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Thanks @ianhi—this looks good to me too. I'm pleased to see that upstream change. It might allow us to eventually simplify some of our overflow-related code.
I have not looked much further, but a bisect indicates the non-upstream test failure is a result of pandas-dev/pandas#64379, which doesn't seem like it was intended to be a breaking change.
Comment threadxarray/tests/test_duck_array_ops.py
betolink pushed a commit
to betolink/icechunk
that referenced
this pull request
May 19, 2026
@ianhi
TEST: fix failing tests (earth-mover#2134)
a83daf2
1. Take more care in not generating rectilinear chunk grids on spec
version 1
2. update our model for shift-array with rectilinear chunks
3. fix the xarray-upstream-backend-tests issue creation
this gets us almost all the way to green. the remaining failures are
actualyl xarray failures and are fixed there:
pydata/xarray#11340
ianhi
added 2 commits
May 29, 2026 12:10
@ianhi
Use explicit ns unit for np.datetime64 in test parametrize
e1be6a4
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
@ianhi
Handle int64 NaT sentinel before timedelta64 multiplication
2501037
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
kmuehlbauer
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May 31, 2026
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🎉
@Illviljan
Illviljan
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Lots of mypy errors, is it because pip is not installed?
Run pixi run -e test-nightly -- python -m mypy --install-types --non-interactive --cobertura-xml-report mypy_report
/home/runner/work/xarray/xarray/.pixi/envs/test-nightly/bin/python: No module named pip
xarray/core/types.py:21: error: Library stubs not installed for "pandas" [import-untyped]
xarray/compat/pdcompat.py:40: error: Library stubs not installed for "pandas" [import-untyped]
xarray/core/utils.py:84: error: Library stubs not installed for "pandas" [import-untyped]
...

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I have one question regarding the construction of delta, other wise this looks good to me.
Comment threadxarray/coding/times.py
@keewis
keewis
merged commit c3a398e
into
pydata:mainJun 3, 2026

45 of 47 checks passed

sdiebolt pushed a commit
to sdiebolt/xarray
that referenced
this pull request
Aug 12, 2026
@ianhi@Illviljan@keewis
Fix Upstream CI NaT issues (pydata#11340)
87dafaf
* Use explicit ns unit for np.datetime64 in test parametrize
numpy >= 2.5 deprecates the 'generic' (unitless) datetime64/timedelta64
dtype. Constructing np.datetime64("2000") or np.datetime64("NaT") in the
parametrize list ran during pytest collection, and with
filterwarnings=error the resulting DeprecationWarning aborted collection
of the whole module on the upstream-dev CI. That in turn produced a
malformed pytest report and silently disabled the
issue-from-pytest-log-action auto-issue filer.
Pin the unit explicitly so collection stays clean on numpy nightly.
* Handle int64 NaT sentinel before timedelta64 multiplication
numpy >= 2.5 (numpy/numpy#31378, merged 2026-05-11) turns
int64.min * timedelta64 from a silent NaT into a hard OverflowError.
The CF time decode path relied on the silent NaT and now raises through
_check_date_for_units_since_refdate and _check_timedelta_range, surfacing
as `ValueError: unable to decode time units '...'` from decode_cf.
Detect the sentinel (and float NaN) up front so the multiplication path
only sees real numeric inputs. Regression coverage already exists via
the existing int64.min parametrizations of test_cf_timedelta and
test_roundtrip_timedelta64_nanosecond_precision.
---------
Co-authored-by: Illviljan <14371165+Illviljan@users.noreply.github.com>
Co-authored-by: Justus Magin <keewis@users.noreply.github.com>
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@dcheriandcheriandcherian approved these changes
@kmuehlbauerkmuehlbauerkmuehlbauer approved these changes
@keewiskeewiskeewis left review comments
@spencerkclarkspencerkclarkspencerkclark approved these changes

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