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add support for pyarrow string view in features #7718

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add support for pyarrow string view in features #7718

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4 changes: 2 additions & 2 deletions .github/conda/meta.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@ requirements:
- python
- pip
- numpy >=1.17
- pyarrow >=15.0.0
- pyarrow >=16.0.0
- python-xxhash
- dill
- pandas
Expand All @@ -30,7 +30,7 @@ requirements:
- python
- pip
- numpy >=1.17
- pyarrow >=15.0.0
- pyarrow >=16.0.0
- python-xxhash
- dill
- pandas
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2 changes: 1 addition & 1 deletion .github/workflows/ci.yml
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Expand Up @@ -64,7 +64,7 @@ jobs:
run: uv pip install --system --upgrade pyarrow huggingface-hub "dill<0.3.9"
- name: Install dependencies (minimum versions)
if: ${{ matrix.deps_versions != 'deps-latest' }}
run: uv pip install --system pyarrow==15.0.0 huggingface-hub==0.24.7 transformers dill==0.3.1.1
run: uv pip install --system pyarrow==16.0.0 huggingface-hub==0.24.7 transformers dill==0.3.1.1
- name: Test with pytest
run: |
python -m pytest -rfExX -m ${{ matrix.test }} -n 2 --dist loadfile -sv ./tests/
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4 changes: 2 additions & 2 deletions setup.py
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Expand Up @@ -110,8 +110,8 @@
# We use numpy>=1.17 to have np.random.Generator (Dataset shuffling)
"numpy>=1.17",
# Backend and serialization.
# Minimum 15.0.0 to be able to cast dictionary types to their underlying types
"pyarrow>=15.0.0",
# Minimum 16.0.0 to support string views
"pyarrow>=16.0.0",
# For smart caching dataset processing
"dill>=0.3.0,<0.3.9", # tmp pin until dill has official support for determinism see https://github.com/uqfoundation/dill/issues/19
# For performance gains with apache arrow
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7 changes: 7 additions & 0 deletions src/datasets/features/features.py
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Expand Up @@ -110,6 +110,8 @@ def _arrow_to_datasets_dtype(arrow_type: pa.DataType) -> str:
return "string"
elif pyarrow.types.is_large_string(arrow_type):
return "large_string"
elif pyarrow.types.is_string_view(arrow_type):
return "string_view"
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pa.string_view exists, so in the complementing functionstring_to_arrow("string_view") will return pa.StringView correctly

elif pyarrow.types.is_dictionary(arrow_type):
return _arrow_to_datasets_dtype(arrow_type.value_type)
else:
Expand Down Expand Up @@ -508,6 +510,7 @@ class Value:
- `large_binary`
- `string`
- `large_string`
- `string_view`

Args:
dtype (`str`):
Expand Down Expand Up @@ -548,6 +551,10 @@ def encode_example(self, value):
return float(value)
elif pa.types.is_string(self.pa_type):
return str(value)
elif pa.types.is_large_string(self.pa_type):
return str(value)
elif pa.types.is_string_view(self.pa_type):
return str(value)
else:
return value

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