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Pin pyarrow<26 and pandas<3 for the Ubuntu 24.04 image - #3990
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The Ubuntu 24.04 image (pytorch#3988) pins numpy==1.26.4, because numba 0.59.1 and spacy 3.7.2 need numpy < 2. pyarrow's wheels declare no numpy requirement, so pip installs the latest pyarrow, 26.0.0, which fails at import with "pyarrow requires NumPy 2.0 or newer, found 1.26.4". ray.train reports any failure to import fsspec, pandas, pyarrow or requests as "Can't import ray.train as some dependencies are missing", so beginner_source/distributed_training_with_ray_tutorial.py failed the Build tutorials job on main: https://github.com/pytorch/tutorials/actions/runs/40763826746/job/123082673219 Cap pyarrow below 26. Drop the cap when numpy moves to 2.x. Alternative considered: moving numpy to 2.x. That needs new numba and spacy, which is a much larger change to the tutorial environment. Test Plan: In a Python 3.12 venv with numpy==1.26.4, ray[train]==2.55.0, pandas==3.0.6, fsspec and requests: ``` python -c "import pyarrow" # 26.0.0: ImportError, NumPy 2.0 required python -c "import pyarrow" # 22.0.0 to 25.0.0: ok python -c "import ray.train" # with pyarrow<26: ok ``` The image has not been rebuilt: run the Docker Build workflow on this PR, then the tutorial build, to verify. This change was authored with an AI assistant (Claude Code).
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On the Python 3.12 image nothing caps pandas, so pip installs 3.0.x. pandas
3.0 uses copy-on-write, which makes Series.values and to_numpy() return
read-only arrays. Ax 0.4.3 builds ObservationData.means from
d["mean"].values and then assigns into it in its winsorize transform, so
intermediate_source/ax_multiobjective_nas_tutorial.py fails with
"ValueError: assignment destination is read-only".
Cap pandas below 3. ax-platform<0.5 declares an unbounded pandas
requirement, so pip does not catch this. Drop the cap when the tutorial
moves to an Ax release that works with pandas 3.
Test Plan:
In a Python 3.12 venv with pandas 3.0.6:
```
python -c "import pandas as pd; a=pd.DataFrame({'m':[1.0]})['m'].to_numpy(); a[0]=5.0"
```
fails with "assignment destination is read-only". A resolve of
.ci/docker/requirements.txt with torch 2.14.1 standing in for 2.15:
```
uv pip compile .ci/docker/requirements.txt --python-version 3.12 --python-platform x86_64-manylinux_2_39
```
gives pandas 2.3.3, pyarrow 25.0.1, numpy 1.26.4 and ax-platform 0.4.3. The
Build tutorials run on this PR is the end to end check.
This change was authored with an AI assistant (Claude Code).
atalman
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Follow-up to #3988. Fixes the failing Build tutorials job on
main: https://github.com/pytorch/tutorials/actions/runs/40763826746/job/123082673219 and https://github.com/pytorch/tutorials/actions/runs/40773662620Description
#3988 moved the CI image to Ubuntu 24.04 (Python 3.12) and pinned
numpy==1.26.4. Nothing caps the other packages, so pip resolves newer majors that do not work with it. Two caps in.ci/docker/requirements.txtfix the four failing tutorials:pyarrow<26:pyarrow26.0.0 raisesImportError: pyarrow requires NumPy 2.0 or newer, found 1.26.4. Its wheels declare no numpy requirement, so pip installs it anyway. This brokedistributed_training_with_ray_tutorial,hyperparameter_tuning_tutorialandserving_tutorial.ray.trainandray.tunereport any failure to importfsspec,pandas,pyarroworrequestsas "dependencies are missing", which hides the real error.pandas<3: pandas 3.0 makesSeries.valuesread-only (copy-on-write). Ax 0.4.3 builds its observation means fromd["mean"].valuesand assigns into them in its winsorize transform, soax_multiobjective_nas_tutorialfails withValueError: assignment destination is read-only.Both caps can come out when numpy moves to 2.x (and, for pandas, when the Ax tutorial moves to an Ax release that works with pandas 3).
Alternative: move numpy to 2.x, which needs new numba and spacy and is a much larger change.
Checked in a Python 3.12 venv with numpy 1.26.4:
pyarrow26.0.0 fails to import and 22.0.0 to 25.0.0 import fine,import ray.trainpasses with the cap, andto_numpy()is read-only under pandas 3.0.6. A resolve ofrequirements.txtgives pandas 2.3.3, pyarrow 25.0.1, numpy 1.26.4. On the first run of this PR thepyarrowshards (1 and 9) passed and the Ax shard (4) failed; the second commit adds the pandas cap for it.Not verified: the Build tutorials run on the latest commit of this PR.
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