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https://api.github.com/repos/huggingface/datasets/issues/8451 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8451/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8451/comments | https://api.github.com/repos/huggingface/datasets/issues/8451/events | https://github.com/huggingface/datasets/pull/8451 | 5,100,493,580 | PR_kwDODunzps78iW3q | 8,451 | Use the documented default batch_size in the batched IterableDataset exports | {
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} | `IterableDataset.to_dict()`, `to_pandas()` and `to_polars()` all document `batch_size` as:
> batch_size (`int`, *optional*): The size (number of rows) of the batches if `batched` is `True`. Defaults to `datasets.config.DEFAULT_MAX_BATCH_SIZE`.
but the default is never applied. `batch_size` (`None`) is passed straight... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8450 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8450/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8450/comments | https://api.github.com/repos/huggingface/datasets/issues/8450/events | https://github.com/huggingface/datasets/pull/8450 | 5,100,489,505 | PR_kwDODunzps78iWGV | 8,450 | Raise a clear error for values that cannot be encoded as an image | {
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} | Putting an unsupported value in an `Image()` column fails with an error from deep inside the encoder rather than a message about the image:
```python
from datasets import Dataset, Features, Image
Dataset.from_dict({"im": [123]}, features=Features({"im": Image()}))
```
```
AttributeError: 'int' object has no attribut... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8449 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8449/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8449/comments | https://api.github.com/repos/huggingface/datasets/issues/8449/events | https://github.com/huggingface/datasets/pull/8449 | 5,100,489,395 | PR_kwDODunzps78iWE_ | 8,449 | Check the per-split arguments of DatasetDict | {
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} | `DatasetDict.map`, `filter`, `flatten_indices`, `sort` and `shuffle` take per-split arguments — `cache_file_names`, `indices_cache_file_names`, `seeds`, `generators` — documented as *"You have to provide one ... per dataset in the dataset dictionary"*. None of them checks that, they just index the dict:
```python
from... | null | {
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} | `IterableDataset.cast_column()` writes the feature straight into the features dict:
```python
feature = _fix_for_backward_compatible_features(feature)
info = self._info.copy()
info.features[column] = feature
```
There is no check that `column` is actually a column of the dataset, so a typo doesn't fail — it **invents... | null | {
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} | `concatenate_datasets()` documents `axis` as `{0, 1}`, but does not check it. Any other value silently returns **only the first dataset**:
```python
from datasets import Dataset, concatenate_datasets
a = Dataset.from_dict({"a": [1, 2, 3]})
b = Dataset.from_dict({"b": [4, 5, 6]})
concatenate_datasets([a, b], axis=2).... | null | {
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} | All the `Dataset.to_*` exports batch with `range(0, len(self), batch_size)`. A negative `batch_size` makes that range empty, so the data is silently dropped — including when writing to a file:
```python
from datasets import Dataset
ds = Dataset.from_dict({"col_1": [0, 1, 2]})
len(list(ds.to_dict(batch_size=-1, batch... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8445 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8445/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8445/comments | https://api.github.com/repos/huggingface/datasets/issues/8445/events | https://github.com/huggingface/datasets/pull/8445 | 5,100,469,112 | PR_kwDODunzps78iST2 | 8,445 | Fix jax formatting of temporal and decimal columns | {
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} | Temporal columns are either rejected or **silently corrupted** by the jax format.
### 1. Timestamps, dates, times and decimals raise
```python
import datetime
from datasets import Dataset
ds = Dataset.from_dict({"t": [datetime.datetime(2020, 1, 1)]})
ds.with_format("jax")[0]["t"]
```
```
TypeError: Error interpreti... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8444 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8444/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8444/comments | https://api.github.com/repos/huggingface/datasets/issues/8444/events | https://github.com/huggingface/datasets/pull/8444 | 5,100,467,810 | PR_kwDODunzps78iSDy | 8,444 | Fix StopIteration when the JSON data files are empty | {
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} | Feature inference in `json.py` did `next(iter(...))` catching only `FullReadDisallowed`, so an empty `.jsonl` leaked a bare `StopIteration` out of `load_dataset` (the PEP 479 hazard).
This brings `json.py` in line with its neighbours rather than adding a special case: `arrow.py` and `parquet.py` already infer with a `... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8443 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8443/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8443/comments | https://api.github.com/repos/huggingface/datasets/issues/8443/events | https://github.com/huggingface/datasets/pull/8443 | 5,100,459,074 | PR_kwDODunzps78iQZs | 8,443 | Validate by_column and fix the error message in Dataset.batch | {
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} | Two small problems in `Dataset.batch()`.
**1. The error names the wrong class.**
```python
ds.batch()
# ValueError: IterableDataset.batch() misses `batch_size` or `by_column` argument.
```
`IterableDataset.batch()` has its own copy of the same check, so this occurrence in `arrow_dataset.py` is just a copy-paste that... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8442 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8442/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8442/comments | https://api.github.com/repos/huggingface/datasets/issues/8442/events | https://github.com/huggingface/datasets/pull/8442 | 5,100,454,767 | PR_kwDODunzps78iPlj | 8,442 | Accept numpy integers as train_size / test_size in train_test_split | {
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} | `Dataset.train_test_split()` uses `isinstance(..., int)` / `isinstance(..., float)` to tell "a number of rows" from "a fraction", and rejects everything else:
```python
if train_size is not None and not isinstance(train_size, (int, float)):
raise ValueError(f"Invalid value for train_size: {train_size} of type {typ... | null | {
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} | `IterableDataset.shuffle()` doesn't check `buffer_size`, and the two bad values fail in very different ways.
## A negative buffer_size buffers the whole dataset
`BufferShuffledExamplesIterable.__iter__` fills the buffer with an equality test:
```python
for x in self.ex_iterable:
if len(mem_buffer) == buffer_size... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8440 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8440/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8440/comments | https://api.github.com/repos/huggingface/datasets/issues/8440/events | https://github.com/huggingface/datasets/pull/8440 | 5,100,449,140 | PR_kwDODunzps78iOgu | 8,440 | Don't crash when formatting temporal and decimal columns to torch | {
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} | A dataset with a temporal or decimal column cannot be used with the torch format at all:
```python
import datetime
from datasets import Dataset
ds = Dataset.from_dict({"t": [datetime.datetime(2020, 1, 1)]})
ds.with_format("torch")[0]["t"]
```
```
TypeError: can't convert np.ndarray of type numpy.datetime64.
The only... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8439 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8439/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8439/comments | https://api.github.com/repos/huggingface/datasets/issues/8439/events | https://github.com/huggingface/datasets/pull/8439 | 5,100,448,909 | PR_kwDODunzps78iOeF | 8,439 | Don't include writer_batch_size in the fingerprint | {
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} | `writer_batch_size` is documented as
> Number of rows per write operation for the cache file writer. This value is a good trade-off between memory usage during the processing, and processing speed.
It cannot change the data of the resulting dataset — only how it is written. Yet it is part of the fingerprint of `map`,... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8438 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8438/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8438/comments | https://api.github.com/repos/huggingface/datasets/issues/8438/events | https://github.com/huggingface/datasets/pull/8438 | 5,100,439,854 | PR_kwDODunzps78iMyJ | 8,438 | Validate rank and world_size in split_dataset_by_node for IterableDataset | {
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} | `split_dataset_by_node()` behaves differently on the two dataset types for invalid `rank` / `world_size`. The map-style version delegates to `Dataset.shard()`, which rejects them:
```python
def _split_by_node_map_style_dataset(dataset, rank, world_size):
return dataset.shard(num_shards=world_size, index=rank, cont... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8437 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8437/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8437/comments | https://api.github.com/repos/huggingface/datasets/issues/8437/events | https://github.com/huggingface/datasets/pull/8437 | 5,100,431,684 | PR_kwDODunzps78iLQV | 8,437 | Raise when a batched filter function returns the wrong number of values | {
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} | `Dataset.filter(..., batched=True)` builds the kept indices with a `zip`:
```python
indices_array = [i for i, to_keep in zip(indices, mask) if to_keep]
```
`zip` stops at the shorter of its arguments, so a `function` that does not return exactly one value per example is not an error — it silently changes the result:
... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8436 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8436/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8436/comments | https://api.github.com/repos/huggingface/datasets/issues/8436/events | https://github.com/huggingface/datasets/pull/8436 | 5,100,424,782 | PR_kwDODunzps78iKAc | 8,436 | Validate seed and generator in Dataset.train_test_split | {
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} | `Dataset.shuffle()` validates its two randomness parameters:
```python
if seed is not None and generator is not None:
raise ValueError("Both `seed` and `generator` were provided. Please specify just one of them.")
if generator is not None and not isinstance(generator, np.random.Generator):
raise ValueError("T... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8435 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8435/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8435/comments | https://api.github.com/repos/huggingface/datasets/issues/8435/events | https://github.com/huggingface/datasets/pull/8435 | 5,100,420,317 | PR_kwDODunzps78iJJ0 | 8,435 | Validate num_shards in Dataset.to_iterable_dataset | {
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} | `Dataset.to_iterable_dataset(num_shards=0)` (or any negative value) returns an `IterableDataset` that silently yields **nothing**:
```python
from datasets import Dataset
ds = Dataset.from_dict({"col_1": [1, 2, 3]})
list(ds.to_iterable_dataset(num_shards=0)) # [] -- no error
list(ds.to_iterable_dataset(num_shards=... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8434 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8434/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8434/comments | https://api.github.com/repos/huggingface/datasets/issues/8434/events | https://github.com/huggingface/datasets/pull/8434 | 5,100,419,066 | PR_kwDODunzps78iI6a | 8,434 | Fix exporting an IterableDataset that has no examples | {
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} | Every conversion/export method of `IterableDataset` materializes the dataset with `pa.concat_tables()` over its Arrow batches:
```python
table = pa.concat_tables(list(self.with_format("arrow").iter(batch_size=1000)))
return Dataset(table, fingerprint="unset").to_list()
```
If the dataset doesn't yield any example the... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8433 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8433/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8433/comments | https://api.github.com/repos/huggingface/datasets/issues/8433/events | https://github.com/huggingface/datasets/pull/8433 | 5,100,416,653 | PR_kwDODunzps78iIcD | 8,433 | Validate num_shards in Dataset.save_to_disk | {
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} | `Dataset.save_to_disk()` accepts `num_shards`, but never checks that it is positive. With `num_shards=0` (or a negative value) it reports success while writing **no data file at all**:
```python
from datasets import Dataset, load_from_disk
ds = Dataset.from_dict({"col_1": [1, 2, 3]})
ds.save_to_disk("dir", num_shards... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8432 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8432/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8432/comments | https://api.github.com/repos/huggingface/datasets/issues/8432/events | https://github.com/huggingface/datasets/pull/8432 | 5,100,407,352 | PR_kwDODunzps78iGpt | 8,432 | Fix numpy formatting of a list column whose first row is null | {
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} | Formatting a list column to numpy or torch crashes when the **first** row is null:
```python
from datasets import Dataset, Features, List, Value
ds = Dataset.from_dict({"c": [None, [3, 4]]}, features=Features({"c": List(Value("int64"))}))
ds.with_format("numpy")[:]["c"]
```
```
AttributeError: 'NoneType' object has ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8431 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8431/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8431/comments | https://api.github.com/repos/huggingface/datasets/issues/8431/events | https://github.com/huggingface/datasets/pull/8431 | 5,100,394,795 | PR_kwDODunzps78iEQi | 8,431 | Fix the archive member path check against a sibling output directory | {
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} | The `safemembers()` guards that implement the CVE-2007-4559 mitigation compare the resolved member path to the output directory with a plain `str.startswith()`:
```python
def badpath(path: str, base: str) -> bool:
# joinpath will ignore base if path is absolute
return not resolved(os.path.join(base, path)).sta... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8430 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8430/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8430/comments | https://api.github.com/repos/huggingface/datasets/issues/8430/events | https://github.com/huggingface/datasets/pull/8430 | 5,100,363,245 | PR_kwDODunzps78h-bS | 8,430 | Fix Dataset.flatten with max_depth <= 1 | {
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} | `Dataset.flatten()` accepts a `max_depth` argument (also exposed through `DatasetDict.flatten()`), but any value `<= 1` crashes:
```python
from datasets import Dataset
Dataset.from_dict({"a": [{"b": {"c": 1}}]}).flatten(max_depth=1)
# UnboundLocalError: cannot access local variable 'depth' where it is not associated ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8429 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8429/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8429/comments | https://api.github.com/repos/huggingface/datasets/issues/8429/events | https://github.com/huggingface/datasets/pull/8429 | 5,100,349,360 | PR_kwDODunzps78h720 | 8,429 | Reject a non-positive batch_size in Dataset.iter | {
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} | `Dataset.iter(0)` never returns on a dataset without an indices mapping:
```python
from datasets import Dataset
ds = Dataset.from_dict({"i": list(range(5))})
next(ds.iter(0)) # hangs forever
```
The fast path calls `table_iter(self.data, batch_size=0)`, which asks pyarrow for chunks of `max_chunksize=0`; every chu... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8428 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8428/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8428/comments | https://api.github.com/repos/huggingface/datasets/issues/8428/events | https://github.com/huggingface/datasets/pull/8428 | 5,100,348,873 | PR_kwDODunzps78h7ww | 8,428 | Keep the column order in Features.flatten() | {
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} | `Features.flatten()` and `Dataset.flatten()` disagree on the resulting column order:
```python
from datasets import Dataset, Features, Value
features = Features({"a": Value("int64"), "s": {"x": Value("string")}, "l": Value("int64")})
ds = Dataset.from_dict({"a": [1], "s": [{"x": "q"}], "l": [2]}, features=features)
... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8427 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8427/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8427/comments | https://api.github.com/repos/huggingface/datasets/issues/8427/events | https://github.com/huggingface/datasets/pull/8427 | 5,100,334,562 | PR_kwDODunzps78h5C5 | 8,427 | Validate the arguments of IterableDataset.shard | {
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} | `IterableDataset.shard()` doesn't validate its arguments, so invalid calls either return the wrong data silently or crash with a low-level error from an internal helper. `Dataset.shard()` already validates the index.
```python
ds = Dataset.from_dict({"a": range(20)}).to_iterable_dataset(num_shards=4)
ds.shard(num_sha... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8426 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8426/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8426/comments | https://api.github.com/repos/huggingface/datasets/issues/8426/events | https://github.com/huggingface/datasets/pull/8426 | 5,100,333,579 | PR_kwDODunzps78h42r | 8,426 | Fix casting a chunked array that has no chunk | {
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} | A batched `map` on an arrow-formatted dataset crashes when the function filters out every row of a batch and the output features are given explicitly:
```python
import pyarrow.compute as pc
from datasets import Dataset, Features, Value
ds = Dataset.from_dict({"a": [1, 2, 3, 4]}).with_format("arrow")
ds.map(
lambd... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8425 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8425/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8425/comments | https://api.github.com/repos/huggingface/datasets/issues/8425/events | https://github.com/huggingface/datasets/pull/8425 | 5,100,317,104 | PR_kwDODunzps78h1xs | 8,425 | Return a new Dataset when transforming a dataset with no rows | {
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} | `Dataset.map`, `.filter`, `.select`, `.sort`, `.shuffle` and `.train_test_split` short-circuit when the dataset has no rows and return `self` — the very same object. `train_test_split` even returns that same object as *both* splits.
Because `set_format` / `set_transform` / `reset_format` / `add_faiss_index` mutate a d... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8424 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8424/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8424/comments | https://api.github.com/repos/huggingface/datasets/issues/8424/events | https://github.com/huggingface/datasets/pull/8424 | 5,100,302,571 | PR_kwDODunzps78hzF4 | 8,424 | Encode the column in Dataset.add_column when a feature is given | {
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} | `Dataset.add_column()` takes a `feature` argument documented as the "column datatype", but it is passed directly as the arrow schema of `InMemoryTable.from_pydict()`. That only works when the raw Python values already match the feature's *storage* type, so any feature that encodes its values fails:
```python
from data... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8423 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8423/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8423/comments | https://api.github.com/repos/huggingface/datasets/issues/8423/events | https://github.com/huggingface/datasets/pull/8423 | 5,100,294,829 | PR_kwDODunzps78hxqF | 8,423 | Fix keep_in_memory=True in Dataset.sort and Dataset.train_test_split | {
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} | `Dataset.sort()` and `Dataset.train_test_split()` raise as soon as `keep_in_memory=True` is used on a dataset that has cache files — i.e. on anything returned by `load_dataset()` or `load_from_disk()`:
```python
from datasets import Dataset
Dataset.from_dict({"col_1": [3, 1, 2]}).save_to_disk("ds")
ds = Dataset.load_... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8422 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8422/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8422/comments | https://api.github.com/repos/huggingface/datasets/issues/8422/events | https://github.com/huggingface/datasets/pull/8422 | 5,100,293,775 | PR_kwDODunzps78hxcW | 8,422 | Fix to_pandas() on a dataset with no rows and an ArrayXD column | {
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} | Converting a dataset that has no rows and an `ArrayXD` column to pandas raises:
```python
import datasets
from datasets import Dataset, Features, Array2D
features = Features({"foo": Array2D(shape=(2, 2), dtype="float32")})
ds = Dataset.from_dict({"foo": []}, features=features)
ds.to_pandas()
```
```
pyarrow.lib.Arro... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8421 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8421/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8421/comments | https://api.github.com/repos/huggingface/datasets/issues/8421/events | https://github.com/huggingface/datasets/pull/8421 | 5,100,293,456 | PR_kwDODunzps78hxYV | 8,421 | Validate the columns in IterableDataset.rename_columns | {
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} | `IterableDataset.rename_columns()` doesn't check the column names it is given, so when `info.features` is known it can return a dataset whose `features` contradict the examples it yields. The error is only raised much later, by `_rename_columns_fn()`, when the dataset is iterated.
```python
ds = Dataset.from_dict({"a"... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8420 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8420/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8420/comments | https://api.github.com/repos/huggingface/datasets/issues/8420/events | https://github.com/huggingface/datasets/pull/8420 | 5,100,282,369 | PR_kwDODunzps78hvMN | 8,420 | Keep the dtype of an empty column when formatting to numpy or torch | {
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} | An empty column silently changes dtype when formatted to numpy or torch:
```python
from datasets import Dataset
ds = Dataset.from_dict({"a": [1, 2, 3]}).with_format("torch")
print(ds[:]["a"].dtype) # torch.int64
print(ds.filter(lambda x: False)[:]["a"].dtype) # torch.float32 <-- expected to... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8419 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8419/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8419/comments | https://api.github.com/repos/huggingface/datasets/issues/8419/events | https://github.com/huggingface/datasets/pull/8419 | 5,100,271,993 | PR_kwDODunzps78htLy | 8,419 | Fix label inference for folder-based builders on archives | {
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} | `imagefolder` / `audiofolder` / `videofolder` datasets whose media files live inside a ZIP archive get the wrong labels, and usually fail to build at all.
## The bug
In `_split_generators()` the entries of `files` have two different shapes:
```python
# loose files: (original_file, None, downloaded_file)
files = tup... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8418 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8418/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8418/comments | https://api.github.com/repos/huggingface/datasets/issues/8418/events | https://github.com/huggingface/datasets/pull/8418 | 5,100,259,233 | PR_kwDODunzps78hq0h | 8,418 | Fix DataFrame masking on ArrayXD columns with an integer value type | {
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} | Selecting rows with a boolean mask on a `DataFrame` that has an `Array2D`/`Array3D`/... column with an integer value type raises:
```python
import datasets, numpy as np
features = datasets.Features({"id": datasets.Value("int64"), "foo": datasets.Array2D(dtype="int32", shape=(2, 2))})
ds = datasets.Dataset.from_dict({... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8417 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8417/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8417/comments | https://api.github.com/repos/huggingface/datasets/issues/8417/events | https://github.com/huggingface/datasets/pull/8417 | 5,098,273,405 | PR_kwDODunzps78brrn | 8,417 | Shutdown ThreadPoolExecutor in CyclingMultiSourcesExamplesIterable | {
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} | Add missing executor.shutdown(wait=True) call in the finally block of _iter_arrow(), matching the behavior in __iter__ to ensure threads are shut down before cleanup and sleep. | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8416 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8416/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8416/comments | https://api.github.com/repos/huggingface/datasets/issues/8416/events | https://github.com/huggingface/datasets/pull/8416 | 5,097,697,849 | PR_kwDODunzps78Z-OF | 8,416 | Fix cryptic TypeError from ClassLabel.int2str on a string input | {
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} | `ClassLabel.int2str("1")` raises a cryptic `TypeError: '<=' not supported between instances of 'int' and 'str'` instead of a clear error.
`int2str` guards its input with `isinstance(values, Iterable)`, but a `str` is iterable, so a string is not wrapped as a single value; the code then iterates over the string's chara... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8415 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8415/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8415/comments | https://api.github.com/repos/huggingface/datasets/issues/8415/events | https://github.com/huggingface/datasets/pull/8415 | 5,091,230,885 | PR_kwDODunzps78Fm6_ | 8,415 | Add initial devcontainer configuration | {
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https://api.github.com/repos/huggingface/datasets/issues/8414 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8414/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8414/comments | https://api.github.com/repos/huggingface/datasets/issues/8414/events | https://github.com/huggingface/datasets/pull/8414 | 5,090,218,572 | PR_kwDODunzps78CWen | 8,414 | Fix offline simulation with huggingface_hub 1.27 | {
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"merged_at": "2026-08-10T19:31... | ## Summary
Surfaced by the `huggingface_hub` v1.27.0.rc0 RC test branch, where 6 tests in `tests/test_load.py` fail: [ci-test-huggingface-hub-1.27.0.rc0-release](https://github.com/huggingface/datasets/compare/main...ci-test-huggingface-hub-1.27.0.rc0-release).
They're all offline-simulation tests, and the failures a... | {
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https://api.github.com/repos/huggingface/datasets/issues/8412 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8412/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8412/comments | https://api.github.com/repos/huggingface/datasets/issues/8412/events | https://github.com/huggingface/datasets/pull/8412 | 5,084,411,761 | PR_kwDODunzps77v1RT | 8,412 | Fix IndexError on negative list indices for datasets with an indices mapping | {
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} | ## Summary
In `src/datasets/formatting/formatting.py`, `_query_table_with_indices_mapping`'s iterable branch passes each index directly to `indices.fast_slice(i, 1)`:
```python
return _query_table(table, [indices.fast_slice(i, 1).column(0)[0].as_py() for i in key])
```
`fast_slice` raises `IndexError("Offset must be... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8411 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8411/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8411/comments | https://api.github.com/repos/huggingface/datasets/issues/8411/events | https://github.com/huggingface/datasets/pull/8411 | 5,083,951,373 | PR_kwDODunzps77uYL- | 8,411 | Restore the _legacy_no_dict_keys_sorting branch in Pickler._batch_setitems | {
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} | ### Root cause
`Pickler._legacy_no_dict_keys_sorting` lost its only reader in #7817. That PR rewrote `_batch_setitems` to accept the argument Python 3.14 passes, and in the same hunk dropped the early return:
```diff
- def _batch_setitems(self, items):
- if self._legacy_no_dict_keys_sorting:
- re... | {
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https://api.github.com/repos/huggingface/datasets/issues/8410 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8410/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8410/comments | https://api.github.com/repos/huggingface/datasets/issues/8410/events | https://github.com/huggingface/datasets/issues/8410 | 5,083,948,009 | I_kwDODunzps8AAAABLwbj6Q | 8,410 | _legacy_no_dict_keys_sorting has no reader since #7817, so the 2.15.0 legacy cache lookup computes the wrong config_id | {
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`Pickler._legacy_no_dict_keys_sorting` has a definition and a writer, but since #7817 it has no reader, so the flag does nothing.
`DatasetBuilder._check_legacy_cache2` patches it on to recompute the `config_id` that 2.15.0 would have produced, because 2.15.0 hashed dicts without sorting their ite... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8409 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8409/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8409/comments | https://api.github.com/repos/huggingface/datasets/issues/8409/events | https://github.com/huggingface/datasets/pull/8409 | 5,083,087,639 | PR_kwDODunzps77roh- | 8,409 | docs: fix broken audio link in mapstyle vs iterable guide | {
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} | The "map-style vs iterable" guide links the four loading guides on one line, but the `audio` link has a stray `]` inside its target (`./audio_load]`), which makes the Markdown link malformed and breaks it.
The three sibling links on the same line are correct (`./tabular_load`, `./nlp_load`, `./image_load`), and the ta... | {
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https://api.github.com/repos/huggingface/datasets/issues/8408 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8408/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8408/comments | https://api.github.com/repos/huggingface/datasets/issues/8408/events | https://github.com/huggingface/datasets/pull/8408 | 5,080,309,439 | PR_kwDODunzps77ilJy | 8,408 | Save the shuffle buffer content in the state dict so resuming is exact | {
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} | ## Overview
There are two problems when resuming a shuffled iterable dataset. The known one from the warning and the discussion in #7901 is that the shuffle buffer content isn't saved in the state dict so you lose roughly `buffer_size` examples every resume.
The second is you can get an example twice. The `Rebatc... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8407 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8407/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8407/comments | https://api.github.com/repos/huggingface/datasets/issues/8407/events | https://github.com/huggingface/datasets/pull/8407 | 5,077,929,707 | PR_kwDODunzps77a8Eg | 8,407 | Optimize PyArrow block shuffling with dynamic rebatched chunk interleaving | {
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"merged_at": "2026-09-07T14:03... | When streaming PyArrow datasets with shuffling enabled (`buffer_size > 0`), the `BufferShuffledExamplesIterable._iter_arrow()` method historically relied on a Python-level `list` to maintain the shuffle buffer, replacing elements one-by-one. In a multi-worker `DataLoader` environment, this per-row generator approach ca... | {
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https://api.github.com/repos/huggingface/datasets/issues/8406 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8406/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8406/comments | https://api.github.com/repos/huggingface/datasets/issues/8406/events | https://github.com/huggingface/datasets/pull/8406 | 5,076,886,721 | PR_kwDODunzps77XnBU | 8,406 | Preserve nanosecond precision in Python dataset construction | {
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} | ## What it is
Preserves exact nanosecond precision for pandas timestamps and timedeltas when users declare `Value("timestamp[ns]")` or `Value("duration[ns]")`.
Previously, `Dataset.from_dict`, `Dataset.from_list`, and `Dataset.map` reported a nanosecond feature while silently storing values truncated to microseconds.... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8405 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8405/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8405/comments | https://api.github.com/repos/huggingface/datasets/issues/8405/events | https://github.com/huggingface/datasets/pull/8405 | 5,074,026,078 | PR_kwDODunzps77OaCx | 8,405 | Match Dataset.map's on_mixed_types default in DatasetDict.map | {
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} | ### Problem
`Dataset.map` defaults `on_mixed_types` to `"use_json"`, so a mapped column with no
predefined schema becomes a `Json()` feature instead of failing type inference.
`DatasetDict.map` defaults the same parameter to `None` and forwards it to every split
unconditionally, so wrapping the splits in a `DatasetDic... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8404 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8404/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8404/comments | https://api.github.com/repos/huggingface/datasets/issues/8404/events | https://github.com/huggingface/datasets/pull/8404 | 5,070,831,360 | PR_kwDODunzps77EBK8 | 8,404 | Fix broken links in documentation | {
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} | Several documentation pages link to URLs that now return 404. This PR updates them to their current locations.
| File | Old (404) | New |
|------|-----------|-----|
| `object_detection.mdx` | `albumentations.ai/docs/examples/example_bboxes/` | `albumentations.ai/docs/examples/example-bboxes/` |
| `image_dataset.mdx` |... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8403 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8403/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8403/comments | https://api.github.com/repos/huggingface/datasets/issues/8403/events | https://github.com/huggingface/datasets/pull/8403 | 5,064,557,555 | PR_kwDODunzps76v2d3 | 8,403 | Fix pandas formatting when a decodable column is excluded by columns= | {
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} | The pandas decoder builds its transform map from all of `self.features`, but the frame has already been projected to the format's `columns`:
```python
ds.with_format("pandas", columns=["label"])[0]
# KeyError: "Label(s) ['image'] do not exist"
```
Scoped to pandas — `None`, `numpy`, `torch` and `arrow` all handle a c... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8402 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8402/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8402/comments | https://api.github.com/repos/huggingface/datasets/issues/8402/events | https://github.com/huggingface/datasets/pull/8402 | 5,064,555,950 | PR_kwDODunzps76v2Jl | 8,402 | Fix PolarsFeaturesDecoder.decode_row | {
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} | `PolarsFeaturesDecoder.decode_row` is a verbatim copy of the pandas implementation, but polars' `map_rows` takes a callable rather than a dict of column transforms:
```python
ds.with_format("polars")[0]
# TypeError: 'dict' object is not callable
```
So `with_format("polars")` is unusable on any dataset with an `Image... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8401 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8401/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8401/comments | https://api.github.com/repos/huggingface/datasets/issues/8401/events | https://github.com/huggingface/datasets/pull/8401 | 5,064,554,167 | PR_kwDODunzps76v1yt | 8,401 | Allow reading a split with no examples | {
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} | `make_file_instructions` skips every file whose take is 0, so `BaseReader.read` receives an empty file list and raises — which means one empty split makes the entire `DatasetDict` unloadable:
```python
load_dataset("json", data_files={"train": [...], "test": []})
# ValueError: Instruction "test" corresponds to no data... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8400 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8400/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8400/comments | https://api.github.com/repos/huggingface/datasets/issues/8400/events | https://github.com/huggingface/datasets/pull/8400 | 5,064,552,446 | PR_kwDODunzps76v1cs | 8,400 | Fix align_labels_with_mapping on a list of ClassLabel | {
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} | #7634 dropped `Sequence` from the `.features` import but left two references in `align_labels_with_mapping`, so every non-plain-`ClassLabel` column raises:
```python
ds.align_labels_with_mapping({"O": 0, "LOC": 1, "PER": 2}, "ner_tags")
# NameError: name 'Sequence' is not defined
```
That covers the token-classificat... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8399 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8399/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8399/comments | https://api.github.com/repos/huggingface/datasets/issues/8399/events | https://github.com/huggingface/datasets/pull/8399 | 5,064,550,459 | PR_kwDODunzps76v1Cv | 8,399 | Fix interleave_datasets with all_exhausted when a dataset is empty | {
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} | With `stopping_strategy="all_exhausted"` and no `probabilities`, the indices come from `np.arange(max(lengths)) % lengths`. A zero-length input makes that a modulo by zero, which yields index 0; after the source offset is added it is either out of range or a valid index into a *different* dataset:
```python
interleave... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8398 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8398/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8398/comments | https://api.github.com/repos/huggingface/datasets/issues/8398/events | https://github.com/huggingface/datasets/pull/8398 | 5,064,548,613 | PR_kwDODunzps76v0qb | 8,398 | Fix casting a sliced list array to a fixed size list | {
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} | `array_cast` and `cast_array_to_feature` build the child window for a fixed-size list as `array.values[array.offset * length : ...]`. But `.values` is the **unsliced** child array, so that arithmetic is only correct when every earlier row holds exactly `length` items. `Dataset.cast` slices into batches, so this fires w... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8397 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8397/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8397/comments | https://api.github.com/repos/huggingface/datasets/issues/8397/events | https://github.com/huggingface/datasets/pull/8397 | 5,064,546,506 | PR_kwDODunzps76v0P0 | 8,397 | Support empty input shards in ArrowBasedBuilder | {
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} | `ArrowBasedBuilder._prepare_split_single` assumes every input shard yields at least one table, so `original_shard_lengths` is indexed out of range when a shard yields nothing:
```python
load_dataset("json", data_files=["00.jsonl", "01.jsonl"]) # 00.jsonl is empty
# DatasetGenerationError
# cause: IndexError: list ... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8396 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8396/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8396/comments | https://api.github.com/repos/huggingface/datasets/issues/8396/events | https://github.com/huggingface/datasets/pull/8396 | 5,063,822,443 | PR_kwDODunzps76teEZ | 8,396 | Fix malformed audio link in mapstyle vs iterable docs | {
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} | # What does this PR do?
Fixes a malformed link in `docs/source/about_mapstyle_vs_iterable.mdx`.
The audio guide link was written as `[audio](./audio_load])` (a stray closing parenthesis inside the link target), so it resolved to a non-existent path. This PR removes the stray `)` so the link points to the actual `audi... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8395 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8395/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8395/comments | https://api.github.com/repos/huggingface/datasets/issues/8395/events | https://github.com/huggingface/datasets/pull/8395 | 5,060,759,129 | PR_kwDODunzps76jdoX | 8,395 | Forward iter_arrow, is_typed and features from RepeatExamplesIterable | {
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"merged_at": "2026-08-31T09:38... | `RepeatExamplesIterable` never forwarded `iter_arrow`, `is_typed` or `features` to the iterable it wraps, so `.repeat()` stranded an Arrow-capable child behind a non-Arrow parent: iteration fell back to the per-example path and the dtypes were re-inferred from Python objects.
This copies the three-property block and t... | {
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https://api.github.com/repos/huggingface/datasets/issues/8394 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8394/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8394/comments | https://api.github.com/repos/huggingface/datasets/issues/8394/events | https://github.com/huggingface/datasets/issues/8394 | 5,060,755,332 | I_kwDODunzps8AAAABLaT_hA | 8,394 | IterableDataset.repeat() drops the Arrow fast path and widens numpy dtypes | {
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`RepeatExamplesIterable` is the only wrapper in `iterable_dataset.py` that does not forward `iter_arrow`, `is_typed` and `features` to the iterable it wraps. Two things follow from that: `.repeat()` drops the Arrow fast path, and under `numpy` format it silently widens the declared dtypes.
`SkipE... | {
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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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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... | {
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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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} | ## What does this PR do?
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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`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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`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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} | `_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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} | `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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"merged_at": "2026-09-04T13:33... | Fix #8393
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... | {
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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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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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} | `save_to_disk` computes the number of shards from the estimated size and then clamps it to the number of rows (added in #7912):
```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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} | `IterableDataset.remove_columns` accepts either a single column name or a list, but it only ever tests `col in column_names`. When a string is passed, that becomes a substring test, so any existing column whose name is contained in the one being removed is dropped from `info.features`:
```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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} | `Dataset.unique` only takes the indices mapping into account when it has a different number of rows than the underlying table:
```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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} | ### The bug
`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... | {
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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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`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 ... | {
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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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} | ## 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/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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} | ## What does this PR do?
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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} | ## 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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} | ## What was wrong
`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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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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} | 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... | {
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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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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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} | Fixes #5971
### 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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} | ### The problem
`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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"merged_at": "2026-07-28T10:01... | 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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"merged_at": "2026-07-28T10:29... | ### What this fixes
`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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`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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https://api.github.com/repos/huggingface/datasets/issues/8363 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8363/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8363/comments | https://api.github.com/repos/huggingface/datasets/issues/8363/events | https://github.com/huggingface/datasets/pull/8363 | 4,965,204,642 | PR_kwDODunzps71r4lE | 8,363 | Keep integers on the python read path for fixed-shape ArrayXD columns with nulls | {
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"merged_at": "2026-07-24T11:59... | ## 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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https://api.github.com/repos/huggingface/datasets/issues/8362 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8362/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8362/comments | https://api.github.com/repos/huggingface/datasets/issues/8362/events | https://github.com/huggingface/datasets/issues/8362 | 4,965,203,691 | I_kwDODunzps8AAAABJ_L-6w | 8,362 | ArrayXD fixed-shape integer column with a null row is silently cast to float on the python read path | {
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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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https://api.github.com/repos/huggingface/datasets/issues/8361 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8361/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8361/comments | https://api.github.com/repos/huggingface/datasets/issues/8361/events | https://github.com/huggingface/datasets/pull/8361 | 4,965,086,196 | PR_kwDODunzps71rhT8 | 8,361 | Use Sequence instead of list for path_or_paths typing | {
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} | Fixes #5354
## 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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"merged_at": "2026-07-24T12:06... | ## 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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https://api.github.com/repos/huggingface/datasets/issues/8359 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8359/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8359/comments | https://api.github.com/repos/huggingface/datasets/issues/8359/events | https://github.com/huggingface/datasets/issues/8359 | 4,964,932,317 | I_kwDODunzps8AAAABJ-7a3Q | 8,359 | IterableDataset.filter() checkpoint/resume silently drops the rest of the in-flight Arrow table | {
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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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"merged_at": "2026-07-24T11:54... | ### 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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https://api.github.com/repos/huggingface/datasets/issues/8354 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8354/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8354/comments | https://api.github.com/repos/huggingface/datasets/issues/8354/events | https://github.com/huggingface/datasets/pull/8354 | 4,958,731,939 | PR_kwDODunzps71XABh | 8,354 | Fix bucket dataset card handling and push metadata accounting | {
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"merged_at": "2026-07-24T11:51... | 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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https://api.github.com/repos/huggingface/datasets/issues/8353 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8353/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8353/comments | https://api.github.com/repos/huggingface/datasets/issues/8353/events | https://github.com/huggingface/datasets/pull/8353 | 4,957,611,182 | PR_kwDODunzps71TVV3 | 8,353 | Add file_name column option in JSON processing | {
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} | Fixes #5806
Adds an optional `return_file_name` parameter to the JSON loader (load_dataset).
When set to True, a `file_name` column is added with the source file path,
useful for resuming training from checkpoints by skipping already-used shards. | {
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"merged_at": "2026-07-23T17:32... | Fixes #8351
## Root cause
`NumpyArrowExtractor._arrow_array_to_numpy` decides `dtype=object` with:
```python
if any(
(isinstance(x, np.ndarray) and (x.dtype == object or x.shape != array[0].shape))
or (isinstance(x, float) and np.isnan(x))
for x in array
):
```
The second clause was added in #3195 to ha... | {
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`NumpyArrowExtractor._arrow_array_to_numpy` (used by `Dataset.with_format("numpy")`) promotes a flat, homogeneous numeric column to `dtype=object` when the column contains nulls, but only for `float64`/`int64` columns. A `float32` column is returned as a numeric array. The result is a silent wrong... | {
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https://api.github.com/repos/huggingface/datasets/issues/8350 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8350/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8350/comments | https://api.github.com/repos/huggingface/datasets/issues/8350/events | https://github.com/huggingface/datasets/pull/8350 | 4,946,198,947 | PR_kwDODunzps70uU75 | 8,350 | fix: validate Arrow IPC record batches | {
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"merged_at": "2026-07-22T13:26... | ## Summary
- fully validate each Arrow IPC record batch before converting it to a table
- reject malformed array offsets at the ingestion boundary
- add a safe regression fixture that is accepted by structural validation but rejected by full validation
`pa.Table.from_batches` does not perform full record batch valida... | {
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https://api.github.com/repos/huggingface/datasets/issues/8349 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8349/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8349/comments | https://api.github.com/repos/huggingface/datasets/issues/8349/events | https://github.com/huggingface/datasets/pull/8349 | 4,941,260,112 | PR_kwDODunzps70eZSn | 8,349 | Fix require_storage_embed recursing into require_storage_cast | {
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"merged_at": "2026-07-22T18:37... | ### Summary
`require_storage_embed` decides whether a (possibly nested) feature needs its data embedded into storage. For nested features it dispatches to the wrong helper and can report the wrong answer.
### Root cause
The recursive branches call `require_storage_cast` instead of recursing into `require_storage_emb... | {
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