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https://api.github.com/repos/huggingface/datasets/issues/8393 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8393/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8393/comments | https://api.github.com/repos/huggingface/datasets/issues/8393/events | https://github.com/huggingface/datasets/issues/8393 | 5,057,788,029 | I_kwDODunzps8AAAABLXe4fQ | 8,393 | CPU Bottleneck in `IterableDataset.state_dict()` when shuffling multiple shards | {
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} | **Describe the bug**
There is a significant CPU bottleneck in `IterableDataset` dataloading when `buffer_size` and `max_buffer_input_shards` are greater than 1 (i.e. highly parallelized streaming with a shuffle buffer).
Currently, `_BaseExamplesIterable.state_dict()` falls back to performing a full recursive `copy.dee... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8392 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8392/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8392/comments | https://api.github.com/repos/huggingface/datasets/issues/8392/events | https://github.com/huggingface/datasets/pull/8392 | 5,057,387,644 | PR_kwDODunzps76YcK8 | 8,392 | Add Spark Connect support for Spark datasets | {
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Adds Spark Connect support to `Dataset.from_spark` and `IterableDataset.from_spark` by replacing client-side RDD and `SparkContext` calls with DataFrame APIs supported by Spark Connect.
- discovers partitions with `spark_partition_id()` for streaming datasets
- runs the shared-cache probe wit... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8391 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8391/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8391/comments | https://api.github.com/repos/huggingface/datasets/issues/8391/events | https://github.com/huggingface/datasets/issues/8391 | 5,057,110,196 | I_kwDODunzps8AAAABLW1gtA | 8,391 | Nanosecond timestamps are silently truncated even when Value("timestamp[ns]") is requested | {
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} | ### Describe the bug
`Dataset.from_dict` / `from_list` / `map` silently drop sub-microsecond precision, even when the user explicitly declares a nanosecond feature type. The resulting dataset reports `timestamp[ns]` but the data has already been truncated to microseconds.
### Steps to reproduce the bug
```python
imp... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8390 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8390/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8390/comments | https://api.github.com/repos/huggingface/datasets/issues/8390/events | https://github.com/huggingface/datasets/issues/8390 | 5,057,108,509 | I_kwDODunzps8AAAABLW1aHQ | 8,390 | to_json cannot round-trip temporal columns: all timestamps written as epoch milliseconds | {
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} | ### Describe the bug
`Dataset.to_json()` serializes every temporal column as a bare epoch integer at a single fixed resolution (pandas' `date_unit="ms"` default), with no unit recorded in the output. Timestamps therefore do not survive a `to_json` → `from_json` round trip: they either come back silently wrong or raise... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8389 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8389/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8389/comments | https://api.github.com/repos/huggingface/datasets/issues/8389/events | https://github.com/huggingface/datasets/pull/8389 | 5,057,105,324 | PR_kwDODunzps76XicZ | 8,389 | Keep the id of List and LargeList features when visiting them | {
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"followers_url": "https://api.github.com/users/LeSingh1/... | [] | open | false | [] | null | [] | 2026-08-04T05:35:23 | 2026-08-04T05:35:23 | null | null | NONE | [] | null | null | null | null | `_visit()` and `_visit_with_path()` rebuild `List` / `LargeList` in order to recurse into the inner feature, but they don't carry `id` over, so it is silently reset to `None`. Every other feature type is passed through untouched and keeps its `id`.
`Features.__init__` runs `_visit()` on every column (to convert the le... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8388 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8388/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8388/comments | https://api.github.com/repos/huggingface/datasets/issues/8388/events | https://github.com/huggingface/datasets/pull/8388 | 5,057,105,180 | PR_kwDODunzps76Xiab | 8,388 | Allow to_iterable_dataset() on a dataset with no rows | {
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"followers_url": "https://api.github.com/users/LeSingh1/... | [] | open | false | [] | null | [] | 2026-08-04T05:35:21 | 2026-08-04T05:35:21 | null | null | NONE | [] | null | null | null | null | `Dataset.to_iterable_dataset()` defaults to `num_shards=1`, but the guard rejects any `num_shards > len(self)`, so it always raises on an empty dataset:
```python
>>> Dataset.from_dict({"a": []}).to_iterable_dataset()
ValueError: Unable to shard a dataset of size 0 into 1 shards (the number of shards exceeds the numbe... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8387 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8387/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8387/comments | https://api.github.com/repos/huggingface/datasets/issues/8387/events | https://github.com/huggingface/datasets/pull/8387 | 5,057,055,820 | PR_kwDODunzps76XYVI | 8,387 | Fix `deepcopy` bottleneck in state_dict() | {
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This PR significantly resolves a major CPU bottleneck in `IterableDataset` dataloading when `buffer_size` and `max_buffer_input_shards` are > 1.
**The Bug:**
Currently, `_BaseExamplesIterable.state_dict()` falls back to performing a full recursive `copy.deepcopy(self._state_dict)`.
In nested iterator... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8386 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8386/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8386/comments | https://api.github.com/repos/huggingface/datasets/issues/8386/events | https://github.com/huggingface/datasets/issues/8386 | 5,056,333,190 | I_kwDODunzps8AAAABLWGFhg | 8,386 | map(batched=True, drop_last_batch=True) returns the input unchanged when the dataset is smaller than batch_size | {
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} | ### Describe the bug
When `drop_last_batch=True` and the dataset is smaller than `batch_size`, `Dataset.map(batched=True, ...)` returns the **input unchanged** instead of an empty dataset. The mapped function is never called, but the original rows are passed through with the original (unbatched) schema.
The iterable ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8385 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8385/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8385/comments | https://api.github.com/repos/huggingface/datasets/issues/8385/events | https://github.com/huggingface/datasets/pull/8385 | 5,056,320,016 | PR_kwDODunzps76VCkY | 8,385 | Fix save_to_disk writing no shard for a dataset with no rows | {
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```python
num_shards = min(len(self.data), num_shards)
```
For a dataset with no rows that gives `0` shards. No `.arrow` file is written, `state.json` gets an empty `"_data_files"`, and load... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8384 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8384/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8384/comments | https://api.github.com/repos/huggingface/datasets/issues/8384/events | https://github.com/huggingface/datasets/pull/8384 | 5,056,316,898 | PR_kwDODunzps76VB6Y | 8,384 | Fix IterableDataset.remove_columns when a single column name is passed | {
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```python
ds = Dataset.from_dict... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8383 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8383/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8383/comments | https://api.github.com/repos/huggingface/datasets/issues/8383/events | https://github.com/huggingface/datasets/pull/8383 | 5,056,314,094 | PR_kwDODunzps76VBUb | 8,383 | Apply the indices mapping in Dataset.unique | {
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```python
if self._indices is not None and self._indices.num_rows != self._data.num_rows:
```
An indices mapping can also repeat some rows and drop others while keeping the same length. In th... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8382 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8382/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8382/comments | https://api.github.com/repos/huggingface/datasets/issues/8382/events | https://github.com/huggingface/datasets/pull/8382 | 5,053,067,850 | PR_kwDODunzps76KnWs | 8,382 | Fix IterableDataset.to_dict() and to_polars() returning an empty generator | {
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`IterableDataset.to_dict()` and `IterableDataset.to_polars()` each contain a bare `yield` in their `batched=True` branch. A bare `yield` anywhere in a function body makes the whole function a generator function, so both methods return a generator on every call, including the `batched=False` default. That g... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8381 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8381/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8381/comments | https://api.github.com/repos/huggingface/datasets/issues/8381/events | https://github.com/huggingface/datasets/issues/8381 | 5,053,065,106 | I_kwDODunzps8AAAABLS-nkg | 8,381 | IterableDataset.to_dict() and to_polars() return an empty generator instead of the data | {
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"#take"
] | 2026-08-03T18:35:13 | 2026-08-03T18:35:25 | null | null | CONTRIBUTOR | [] | null | null | {
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`IterableDataset.to_dict()` and `IterableDataset.to_polars()` each have a bare `yield` in their `batched=True` branch, which makes the whole method a generator function. Calling either one the way its docstring shows returns a generator that yields nothing, and the value the `else` branch returns ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8380 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8380/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8380/comments | https://api.github.com/repos/huggingface/datasets/issues/8380/events | https://github.com/huggingface/datasets/pull/8380 | 5,035,622,149 | PR_kwDODunzps75T9aA | 8,380 | Speed up default Python row extraction | {
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"Thanks for catching this. The row fast path was bypassing `ArrayExtensionArray.to_pylist()`, which owns ArrayXD shape and null conversion.\n\nI updated `extract_row` to use `to_pylist()[0]` only for ArrayXD columns. Standard columns still use `col[0].as_py()`, so the ordinary fast path is unchanged. I also added a... | 2026-08-01T06:13:11 | 2026-08-01T08:27:47 | null | null | NONE | [] | null | null | null | null | ## Problem
`PythonArrowExtractor.extract_row` runs once per row on the default read path (every `for row in ds` and every `ds[i]`), and it does more work than it needs to:
```python
def extract_row(self, pa_table: pa.Table) -> dict:
return _unnest(pa_table.to_pydict())
```
`pa_table` here is always a one-row tab... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8379 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8379/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8379/comments | https://api.github.com/repos/huggingface/datasets/issues/8379/events | https://github.com/huggingface/datasets/pull/8379 | 5,033,796,787 | PR_kwDODunzps75OPzP | 8,379 | Preserve features after IterableDataset.add_column | {
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"Closing this as a duplicate of #8316, which is already tracking the same `IterableDataset.add_column` feature preservation change and the 2D ndarray inference concern. Better to keep the discussion in one place."
] | 2026-07-31T22:19:06 | 2026-08-03T22:06:30 | 2026-08-03T22:06:30 | null | NONE | [] | null | null | null | null | ## Summary
- preserve known `IterableDataset` features when `add_column` appends a streaming column
- infer the appended column feature from the provided column values
- add a regression test for `add_column` after resolving iterable dataset features
Fixes #5752.
## Testing
- local repro with `IterableDataset.from_... | {
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https://api.github.com/repos/huggingface/datasets/issues/8378 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8378/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8378/comments | https://api.github.com/repos/huggingface/datasets/issues/8378/events | https://github.com/huggingface/datasets/pull/8378 | 5,029,934,393 | PR_kwDODunzps75Bwbf | 8,378 | feat: add return_file_name option to JSON loader | {
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Adds a `return_file_name` option to the JSON loader. When enabled, the resulting dataset includes a `file_name` column indicating the source file of each row.
## Motivation
When training is interrupted and resumed, it's useful to know which file each row came from so already-trained sh... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8377 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8377/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8377/comments | https://api.github.com/repos/huggingface/datasets/issues/8377/events | https://github.com/huggingface/datasets/pull/8377 | 5,027,590,302 | PR_kwDODunzps746K85 | 8,377 | Fix PandasArrayExtensionDtype._metadata: must be a tuple, not a string | {
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"This is a copy of a PR I have already created: https://github.com/huggingface/datasets/pull/8376",
"Thanks for flagging, @kohankhaki — closing this in favor of #8376 since it's the same fix."
] | 2026-07-31T07:47:13 | 2026-08-02T15:55:12 | 2026-08-02T15:55:12 | null | NONE | [] | null | null | null | null | ## Summary
Fixes #8375 — `PandasArrayExtensionDtype._metadata` is a plain string instead of a tuple, causing `AttributeError: 'PandasArrayExtensionDtype' object has no attribute 'v'` whenever pandas compares two instances of this dtype (e.g. during a boolean-mask filter on a DataFrame with an array-feature column read ... | {
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https://api.github.com/repos/huggingface/datasets/issues/8376 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8376/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8376/comments | https://api.github.com/repos/huggingface/datasets/issues/8376/events | https://github.com/huggingface/datasets/pull/8376 | 5,025,670,677 | PR_kwDODunzps740EFW | 8,376 | Fix PandasArrayExtensionDtype._metadata to use a tuple | {
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`PandasArrayExtensionDtype` set `_metadata = "value_type"` (a string), but pandas expects a tuple of attribute names, e.g. `("value_type",)`.
When pandas compares dtypes (during things like `df[mask]`), it loops over `_metadata` and looks up each entry as an attribute. With a string, it iterates ove... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8375 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8375/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8375/comments | https://api.github.com/repos/huggingface/datasets/issues/8375/events | https://github.com/huggingface/datasets/issues/8375 | 5,025,604,085 | I_kwDODunzps8AAAABK4yh9Q | 8,375 | `PandasArrayExtensionDtype._metadata` should be a tuple, not a string | {
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} | ### Describe the bug
There's a small typo in `PandasArrayExtensionDtype` (`src/datasets/features/features.py`):
```python
_metadata = "value_type"
```
Pandas expects `_metadata` to be a tuple of attribute names, like `("value_type",)`, not a plain string ([API documentation ref](https://pandas.pydata.org/docs/refer... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8374 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8374/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8374/comments | https://api.github.com/repos/huggingface/datasets/issues/8374/events | https://github.com/huggingface/datasets/pull/8374 | 5,020,005,801 | PR_kwDODunzps74hvA5 | 8,374 | feat: Qdrant Search Index | {
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"The test case issue you mentioned is covered."
] | 2026-07-30T13:04:05 | 2026-07-31T13:33:11 | null | null | NONE | [] | null | null | null | null | Resolves #5698
## Description
This PR adds Qdrant as a vector search backend alongside FAISS and Elasticsearch. Associated documentation and tests are also included. The Qdrant client dependency is marked optional and installed on demand.
[Qdrant](https://qdrant.tech/) is an open-source vector search engine b... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8373 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8373/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8373/comments | https://api.github.com/repos/huggingface/datasets/issues/8373/events | https://github.com/huggingface/datasets/issues/8373 | 5,010,686,962 | I_kwDODunzps8AAAABKqkD8g | 8,373 | TypeError in _dill.py _batch_setitems with Python 3.14 | {
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"Hey Mates, this works: In src/datasets/utils/_dill.py, starting around line 71, update the _batch_setitems overriding to pass the obj argument downstream.\n\n def _batch_setitems(self, items, obj=None):\n if self._legacy_no_dict_keys_sorting:\n return super()._batch_setitems(items,... | 2026-07-29T15:00:19 | 2026-08-01T19:30:07 | null | null | NONE | [] | null | null | {
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} | ### Describe the bug
When using `load_dataset` on Python 3.14, a `TypeError` is raised during the fingerprinting process inside the bundled `_dill.py`. This happens because Python 3.14 changed the signature of the internal C-level `_Pickler._batch_setitems` to require 3 arguments (`self, items, obj`), while `datasets/... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8372 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8372/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8372/comments | https://api.github.com/repos/huggingface/datasets/issues/8372/events | https://github.com/huggingface/datasets/pull/8372 | 5,001,648,344 | PR_kwDODunzps73mRCJ | 8,372 | docs: make repository structure guide prominent in quickstart (#5971) | {
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### Summary of Documentation Improvements:
- **\docs/source/create_dataset.mdx\**: Added a callout link in the introductory **Note** block pointing to the \
epository_structure\ guide so users creating a dataset can easily find guidance on organizing files, splits, and formats.
- **\docs/source/index.mdx\*... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8368 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8368/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8368/comments | https://api.github.com/repos/huggingface/datasets/issues/8368/events | https://github.com/huggingface/datasets/pull/8368 | 4,983,366,989 | PR_kwDODunzps72rBVf | 8,368 | Reject duplicate column names in Dataset.select_columns | {
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`Dataset.select_columns` checks that every requested column exists, but never checks that the request is free of duplicates:
```python
missing_columns = set(column_names) - set(self._data.column_names)
if missing_columns:
raise ValueError(...)
```
Passing the same name twice then produces a datas... | null | {
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] | 2026-07-26T07:48:59 | 2026-07-28T10:01:47 | 2026-07-28T10:01:47 | null | CONTRIBUTOR | [] | null | null | null | null | Pushing a `DatasetDict` that drops a split leaves the repo unloadable:
```python
DatasetDict({"train": ds_train, "test": ds_test}).push_to_hub("user/repo")
DatasetDict({"train": ds_train}).push_to_hub("user/repo") # "test" is gone
load_dataset("user/repo")
# ValueError: Couldn't infer the same data file format for ... | {
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"The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_8366). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.",
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`Dataset.to_json`, `to_csv` and `to_sql` write a nullable integer column as floating point rather than integers.
Fixes #8365.
### Root cause
The three writers build a pandas frame with a bare `batch.to_pandas()`:
- `io/json.py` `_batch_json`
- `io/csv.py` `_batch_csv`
- `io/sql.py` `_batch_sql`... | {
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} | ### Describe the bug
`Dataset.to_json`, `to_csv`, and `to_sql` write a nullable integer column as floating point rather than integers. All three writers (`io/json.py`, `io/csv.py`, `io/sql.py`) call `batch.to_pandas()` with pyarrow's default `integer_object_nulls=False`, which casts any integer column containing a nul... | {
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] | 2026-07-24T04:32:47 | 2026-07-25T12:11:31 | 2026-07-24T11:59:11 | null | CONTRIBUTOR | [] | null | null | null | null | ## What does this PR do?
Fixes #8362.
A fixed-shape `ArrayXD` column (`Array2D(shape=(1, 2), dtype="int64")`, and so on) that contains a `None` row is silently cast to float on the python read path: `to_dict()` / `to_pylist()` return every value as a float, and integers above 2**53 are altered, because an unrelated r... | {
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} | ### Describe the bug
A fixed-shape `ArrayXD` column (for example `Array2D(shape=(1, 2), dtype="int64")`) that contains at least one `None` row is silently cast to float on the python read path. `to_dict()` / `to_pylist()` return every value as a float, and integers above 2**53 lose precision, purely because an unrelat... | {
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## What
Changes the type annotation of `path_or_paths` from `Union[PathLike, list[PathLike]]`
to `Union[PathLike, Sequence[PathLike]]` in:
- `Dataset.from_csv`
- `Dataset.from_json`
- `Dataset.from_parquet`
- `Dataset.from_text`
## Why
`list` is invariant in mypy, so passing a `List[Union[str, ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8360 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8360/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8360/comments | https://api.github.com/repos/huggingface/datasets/issues/8360/events | https://github.com/huggingface/datasets/pull/8360 | 4,964,933,053 | PR_kwDODunzps71rB6x | 8,360 | Rebatch arrow source before formatting in IterableDataset.filter to fix resume data loss | {
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] | 2026-07-24T03:36:42 | 2026-07-25T12:11:30 | 2026-07-24T12:06:19 | null | CONTRIBUTOR | [] | null | null | null | null | ## Root cause
`IterableDataset.filter()` wraps the Arrow source in `FormattedExamplesIterable` but, unlike `map()`, does not first wrap it in `RebatchedArrowExamplesIterable(batch_size=1)`. `FormattedExamplesIterable.__iter__` takes the Arrow branch and pulls a whole table from `ArrowExamplesIterable`, advancing `shar... | {
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} | ### Describe the bug
Resuming a streaming `IterableDataset.filter()` from a `state_dict()` checkpoint silently drops rows: the remainder of the in-flight Arrow table is skipped. For a single-shard dataset this loses up to a full row group per checkpoint, and for a single-table shard it can drop every unconsumed row.
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] | 2026-07-24T00:14:48 | 2026-07-25T12:11:29 | 2026-07-24T11:54:35 | null | CONTRIBUTOR | [] | null | null | null | null | ### Bug
`CsvConfig.pd_read_csv_kwargs` silently drops `on_bad_lines` and `encoding_errors` on pandas 2.0, 2.1, and 2.2, so `load_dataset("csv", ..., on_bad_lines="skip")` (or `"warn"`, or a non-default `encoding_errors`) is ignored and a malformed row raises `ParserError` instead of being skipped.
The version guard e... | {
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] | 2026-07-23T12:19:14 | 2026-07-24T11:51:41 | 2026-07-24T11:51:41 | null | CONTRIBUTOR | [] | null | null | null | null | Four fixes on the `buckets/...` read/write paths, hit by `push_to_hub` → `load_dataset`. The loader one crashes on any dataset with a README; the writer ones corrupt uploaded metadata.
## Key Changes
- **Bucket card loading** (`src/datasets/load.py`)**:** passed the card object instead of its `.data`, crashing on loa... | {
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