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https://api.github.com/repos/huggingface/datasets/issues/8714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8714/comments | https://api.github.com/repos/huggingface/datasets/issues/8714/events | https://github.com/huggingface/datasets/issues/8714 | 5,647,821,325 | I_kwDODunzps8AAAABUKLqDQ | 8,714 | Casting mixed JSON and plain strings to Json depends on row order and batch size | {
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"#self-assign\n\nI have reproduced this on current main and prepared a focused fix using the existing per-value encoding rule, with regression tests for both row orders and multiple batch sizes."
] | 2026-09-30 14:11:42 | 2026-09-30 14:12:11 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Casting a string column containing both JSON-encoded values and plain strings to `Json()` gives different results depending on row order and `batch_size`. A plain string among the first five rows makes valid JSON values decode as strings; a plain string after those rows is left unencoded and raise... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8709 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8709/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8709/comments | https://api.github.com/repos/huggingface/datasets/issues/8709/events | https://github.com/huggingface/datasets/issues/8709 | 5,627,431,520 | I_kwDODunzps8AAAABT2vKYA | 8,709 | string_to_dict maps fields to unrelated regex capture groups | {
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{
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"#self-assign"
] | 2026-09-29 08:17:13 | 2026-09-29 08:19:03 | null | {
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"followers_url": "https://api.github.c... | NONE | [] | null | null | null | null | ## Problem
`string_to_dict` creates named groups for format fields, but builds the result by zipping field names with every regex capture. An unrelated capturing group shifts the values.
## Reproduction
```python
from datasets.utils.py_utils import string_to_dict
print(string_to_dict("train/alice", "(train|test)/{na... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8675 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8675/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8675/comments | https://api.github.com/repos/huggingface/datasets/issues/8675/events | https://github.com/huggingface/datasets/issues/8675 | 5,560,824,749 | I_kwDODunzps8AAAABS3NzrQ | 8,675 | load_dataset("json") fails on mixed-shape JSONL when a chunksize boundary separates the shapes | {
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"Hi, I'd like to work on this issue.\n\nI'll first reproduce the failure with a focused test, then investigate how schemas are inferred and aligned across JSONL chunks in `Json._generate_tables`.\n\nMy initial approach is to make chunked loading consistent with single-chunk loading by unifying the columns and filli... | 2026-09-23 23:31:51 | 2026-09-24 00:46:12 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`load_dataset("json")` raises `DatasetGenerationError` ("column names don't match") on a valid JSONL file that mixes two record shapes, whenever the default 10MB `chunksize` splits the file so that different chunks see different sets of columns.
The JSON loader reads the file in `chunksize` batch... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8637 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8637/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8637/comments | https://api.github.com/repos/huggingface/datasets/issues/8637/events | https://github.com/huggingface/datasets/issues/8637 | 5,492,155,234 | I_kwDODunzps8AAAABR1ujYg | 8,637 | FileLock wrapper drops timeout and every other constructor argument | {
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"Correction to the environment section above, found while testing a change that touches this wrapper.\n\nThis is filelock-version dependent, and filelock 4.0.0 already fixes it. Same probe, same `datasets` commit, only the filelock version differing:\n\n| filelock | `FileLock(p, timeout=5).timeout` | second `FileLo... | 2026-09-17 20:04:06 | 2026-09-24 07:24:10 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`datasets.utils._filelock.FileLock` silently discards every keyword argument except `lock_file`. Passing `timeout=` has no effect, and `is_singleton=True` raises instead of returning the cached lock.
The wrapper declares a variadic signature:
```python
# src/datasets/utils/_filelock.py
def __ini... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8617 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8617/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8617/comments | https://api.github.com/repos/huggingface/datasets/issues/8617/events | https://github.com/huggingface/datasets/issues/8617 | 5,448,559,498 | I_kwDODunzps8AAAABRMJrig | 8,617 | `SplitDict.copy()` crashes when `dataset_name` is not set | {
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"I'd like to take this one.\n\nReproduced on datasets 5.0.1 with the snippet above. `SplitDict.from_split_dict()` reads `dataset_name` via `split_infos[0].get(...)`, which assumes a raw dict, while the loop just below it already handles both dicts and `SplitInfo` objects. I'll branch the lookup the same way and cov... | 2026-09-14 11:12:15 | 2026-09-24 09:07:48 | null | null | NONE | [] | null | null | null | null | ## Description
`SplitDict.copy()` (and `SplitDict.from_split_dict`) crashes with
`AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the split
dict contains `SplitInfo` objects and `dataset_name` is `None`.
## Reproduction
```python
from datasets import SplitDict, SplitInfo
split_dict = SplitDict({... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8714 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8714/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8714/comments | https://api.github.com/repos/huggingface/datasets/issues/8714/events | https://github.com/huggingface/datasets/issues/8714 | 5,647,821,325 | I_kwDODunzps8AAAABUKLqDQ | 8,714 | Casting mixed JSON and plain strings to Json depends on row order and batch size | {
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"#self-assign\n\nI have reproduced this on current main and prepared a focused fix using the existing per-value encoding rule, with regression tests for both row orders and multiple batch sizes."
] | 2026-09-30 14:11:42 | 2026-09-30 14:12:11 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Casting a string column containing both JSON-encoded values and plain strings to `Json()` gives different results depending on row order and `batch_size`. A plain string among the first five rows makes valid JSON values decode as strings; a plain string after those rows is left unencoded and raise... | null | {
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"html_url": "https://github.com/charan-rathore",
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"#self-assign"
] | 2026-09-29 08:17:13 | 2026-09-29 08:19:03 | null | {
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`string_to_dict` creates named groups for format fields, but builds the result by zipping field names with every regex capture. An unrelated capturing group shifts the values.
## Reproduction
```python
from datasets.utils.py_utils import string_to_dict
print(string_to_dict("train/alice", "(train|test)/{na... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8675 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8675/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8675/comments | https://api.github.com/repos/huggingface/datasets/issues/8675/events | https://github.com/huggingface/datasets/issues/8675 | 5,560,824,749 | I_kwDODunzps8AAAABS3NzrQ | 8,675 | load_dataset("json") fails on mixed-shape JSONL when a chunksize boundary separates the shapes | {
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"Hi, I'd like to work on this issue.\n\nI'll first reproduce the failure with a focused test, then investigate how schemas are inferred and aligned across JSONL chunks in `Json._generate_tables`.\n\nMy initial approach is to make chunked loading consistent with single-chunk loading by unifying the columns and filli... | 2026-09-23 23:31:51 | 2026-09-24 00:46:12 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`load_dataset("json")` raises `DatasetGenerationError` ("column names don't match") on a valid JSONL file that mixes two record shapes, whenever the default 10MB `chunksize` splits the file so that different chunks see different sets of columns.
The JSON loader reads the file in `chunksize` batch... | null | {
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`datasets.utils._filelock.FileLock` silently discards every keyword argument except `lock_file`. Passing `timeout=` has no effect, and `is_singleton=True` raises instead of returning the cached lock.
The wrapper declares a variadic signature:
```python
# src/datasets/utils/_filelock.py
def __ini... | null | {
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`SplitDict.copy()` (and `SplitDict.from_split_dict`) crashes with
`AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the split
dict contains `SplitInfo` objects and `dataset_name` is `None`.
## Reproduction
```python
from datasets import SplitDict, SplitInfo
split_dict = SplitDict({... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8596 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8596/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8596/comments | https://api.github.com/repos/huggingface/datasets/issues/8596/events | https://github.com/huggingface/datasets/issues/8596 | 5,413,314,229 | I_kwDODunzps8AAAABQqietQ | 8,596 | load_dataset silently accepts out-of-range ClassLabel indices when the source dtype already matches | {
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"Hi! I’d like to work on this issue.\n\nI can reproduce the inconsistent behavior between `from_dict()` and `from_json()` / `from_parquet()`, and I’d like to add regression coverage for out-of-range `ClassLabel` indices while keeping the existing fast path intact where possible.\n\nWould you be okay with me working... | 2026-09-10 14:15:14 | 2026-09-16 08:05:39 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
Loading a file whose parsed Arrow dtype already matches a declared `ClassLabel`'s storage type (`int64`) skips the range check entirely. Out-of-range indices load with no error and no warning, and only surface later at `int2str` time or as silently wrong labels during training.
```python
from dat... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8590 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8590/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8590/comments | https://api.github.com/repos/huggingface/datasets/issues/8590/events | https://github.com/huggingface/datasets/issues/8590 | 5,391,094,167 | I_kwDODunzps8AAAABQVWRlw | 8,590 | record_checksums default changed True -> False in 4.8.5, not in the release notes | {
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"I'm adding it to the release notes, thx !",
"Looks like the default for `record_checksums` was switched from True to False in 4.8.5, but it wasn't mentioned in the release notes. This could impact users relying on checksums for data verification.\n"
] | 2026-09-08 19:36:25 | 2026-09-16 23:00:38 | null | null | NONE | [] | null | null | null | null | ### What changed
Between 4.8.4 and 4.8.5, checksum recording flipped from on to off by default in two places. From the sdists:
```
4.8.4 src/datasets/download/download_manager.py:80 record_checksums=True
4.8.5 src/datasets/download/download_manager.py:80 record_checksums=False
4.8.4 src/datasets/utils/info_ut... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8543 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8543/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8543/comments | https://api.github.com/repos/huggingface/datasets/issues/8543/events | https://github.com/huggingface/datasets/issues/8543 | 5,308,784,806 | I_kwDODunzps8AAAABPG2gpg | 8,543 | xPath.glob passes double-wrapped storage options to url_to_fs | {
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"#self-assign\n",
"#self-assign"
] | 2026-09-01 06:58:36 | 2026-09-01 08:48:03 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`xPath.glob` adds a second protocol key to the storage options before passing them to `url_to_fs`, so fsspec receives `https={'https': {...}}` instead of `https={...}`.
`_prepare_path_and_storage_options` already returns them protocol keyed, and the docstring of `_prepare_single_hop_path_and_stor... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8537 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8537/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8537/comments | https://api.github.com/repos/huggingface/datasets/issues/8537/events | https://github.com/huggingface/datasets/issues/8537 | 5,291,992,964 | I_kwDODunzps8AAAABO21nhA | 8,537 | JPEG XL support | {
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"I think we just need to make sure Pillow can load such images, and if we need a plugin of some sort or no.\n\nIn the Viewer images will appear on browsers that support JXL",
"For Pillow you have e.g. https://pypi.org/project/pillow-jxl-plugin/\n\nFor the Dataset Viewer and the Data Studio I don't see any images,... | 2026-08-30 12:13:56 | 2026-09-02 18:34:32 | null | null | NONE | [] | null | null | null | null | It seems that the dataset don't support JXL natively in the same ways as e.g. PNG and JPEG are supported. A JPEG XL is supported by an international ISO standard, gives great compression ratios, finally supports lossless for JPEG and the browser support is now starting to get wide spread (safari has it for some time ->... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8522 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8522/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8522/comments | https://api.github.com/repos/huggingface/datasets/issues/8522/events | https://github.com/huggingface/datasets/issues/8522 | 5,277,366,650 | I_kwDODunzps8AAAABOo45eg | 8,522 | Docs proposal: relabel left/right segmentation classes during horizontal flips | {
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"Hi! Opening a PR for this docs request.\n\nAdded a section that flips image/mask together and swaps the directional label pairs on the human parsing dataset, plus an optional AlbumentationsX mapping for folks who already use that stack.\n\n#self-assign"
] | 2026-08-28 10:39:42 | 2026-09-02 03:48:31 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Feature request
Would you be open to a self-contained documentation recipe showing how to relabel directional semantic classes during a horizontal flip? It could be a separate section in [`docs/source/semantic_segmentation.mdx`](https://github.com/huggingface/datasets/blob/main/docs/source/semantic_segmentation.md... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8507 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8507/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8507/comments | https://api.github.com/repos/huggingface/datasets/issues/8507/events | https://github.com/huggingface/datasets/issues/8507 | 5,228,485,367 | I_kwDODunzps8AAAABN6Ra9w | 8,507 | ArrayXD silently reshapes inputs with incompatible nested dimensions | {
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"#self-assign"
] | 2026-08-23 18:42:56 | 2026-08-23 18:43:58 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`Array2D` and the other `ArrayXD` features accept nested input whose dimensions do not match the declared shape when the total number of values happens to match.
For example, data shaped like `(2, 2)` can be created from rows of lengths `3` and `1`. When the value is read back, the rows are silen... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8499 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8499/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8499/comments | https://api.github.com/repos/huggingface/datasets/issues/8499/events | https://github.com/huggingface/datasets/issues/8499 | 5,192,173,564 | I_kwDODunzps8AAAABNXpH_A | 8,499 | TsFile format filter uses an inconsistent URL and is not available initially | {
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"# `tsfile` facet — neither URL names a format\n\nFindings only; no request for action. Figures carry their date. Retracted claims are kept.\n\n`?format=tsfile` and `?format=format:tsfile` are not two spellings of the same filter. They are not two routes to a `format:` facet either: `tsfile` is not in the Hub forma... | 2026-08-19 11:35:39 | 2026-09-01 04:16:37 | null | null | NONE | [] | null | null | null | null |
## Summary
There appear to be two related issues with the `TsFile` format filter on the Hugging Face Datasets page:
1. The URL parameter for `TsFile` is inconsistent with other formats.
2. `TsFile` is not initially shown in the format filter and only appears after visiting a TsFile-specific URL.
## 1. Inconsistent... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8491 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8491/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8491/comments | https://api.github.com/repos/huggingface/datasets/issues/8491/events | https://github.com/huggingface/datasets/issues/8491 | 5,168,815,070 | I_kwDODunzps8AAAABNBXb3g | 8,491 | `Dataset.map(num_proc=N)` worker crashes with `ValueError: I/O operation on closed file` when `finalize()` is interrupted | {
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"Reference: \n\n1. https://github.com/boostorg/beast/issues/1445\n2. `man 2 close`:\n```\n Dealing with error returns from close()\n A careful programmer will check the return value of close(), since it is quite possible that errors on a previous write(2) operation are reported only on the final close() that re... | 2026-08-17 06:05:58 | 2026-09-29 22:49:46 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
We hit this while running Megatron-LM training through ms-swift, which uses `datasets` under the hood for preprocessing. Our preprocessing step calls `Dataset.map()` with a fairly aggressive `num_proc=512` on a ~25k-example JSONL file:
```bash
swift --dataset_num_proc 512 --dataset large.jsonl --... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8483 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8483/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8483/comments | https://api.github.com/repos/huggingface/datasets/issues/8483/events | https://github.com/huggingface/datasets/issues/8483 | 5,160,294,983 | I_kwDODunzps8AAAABM5PaRw | 8,483 | Dataset.take(n) raises IndexError when n > len(dataset), but IterableDataset.take(n) returns what it has | {
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"I'll work on this. Could you assign it to me?\n\nI'll reproduce from the report, fix the failure path, and add a test so it stays fixed.\n",
"Just checking in. I've started working on reproducing the issue and will proceed with the fix as discussed. Let me know if there are any changes in direction or additional... | 2026-08-15 16:32:03 | 2026-09-08 10:02:39 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`Dataset.take(n)` raises when asked for more elements than the dataset has, while `IterableDataset.take(n)` returns the elements it has. Both are documented identically as "Create a new [...] with only the first `n` elements".
```python
>>> from datasets import Dataset
>>> ds = Dataset.from_dict(... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8481 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8481/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8481/comments | https://api.github.com/repos/huggingface/datasets/issues/8481/events | https://github.com/huggingface/datasets/issues/8481 | 5,158,540,024 | I_kwDODunzps8AAAABM3kS-A | 8,481 | ClassLabel.str2int and int2str do not validate the elements of an iterable | {
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"Thanks for weighing in, but one correction so the report stays accurate: `int2str` does **not** return `None` for an unknown class id. It raises, both for a bare value and inside a list — that path is already covered by the `0 <= v < num_classes` check:\n\n```python\n>>> cl = ClassLabel(names=[\"neg\", \"pos\"])\n... | 2026-08-15 08:43:11 | 2026-08-17 06:13:32 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`ClassLabel.str2int` and `ClassLabel.int2str` both validate the *container* they're given, but never the elements inside it. Two of the resulting cases fail silently and return wrong labels rather than raising.
`str2int` accepts ints and hands them straight back, so a column of integer labels rou... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8472 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8472/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8472/comments | https://api.github.com/repos/huggingface/datasets/issues/8472/events | https://github.com/huggingface/datasets/issues/8472 | 5,128,543,479 | I_kwDODunzps8AAAABMa9c9w | 8,472 | batch(0) silently returns one batch with the whole dataset instead of raising | {
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"Hi @shashvat-singham i did also try and reproduced it and got the same results described :\n\n```text\nIterableDataset.batch(0/-1) → [5]\nDataset.batch(0/-1) → 1 batch\nbatch(2) → [2, 2, 1] / 3 batches\n```\n\nI’d like to give this a try\n\nThanks\n\n#self-assign"
] | 2026-08-12 07:52:28 | 2026-08-16 15:56:35 | null | null | NONE | [] | null | null | null | null | ### Describe the bug
`Dataset.batch()` and `IterableDataset.batch()` accept `batch_size=0` and negative sizes, and quietly return **one batch holding the whole dataset**. Asking for a zero-sized batch produces the largest possible batch, which is as close to the opposite of the request as the API can get.
### Steps o... | null | {
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https://api.github.com/repos/huggingface/datasets/issues/8458 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8458/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8458/comments | https://api.github.com/repos/huggingface/datasets/issues/8458/events | https://github.com/huggingface/datasets/issues/8458 | 5,110,353,136 | I_kwDODunzps8AAAABMJnM8A | 8,458 | Replace httpx with httpx2 | {
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"Hi @lhoestq can I work on this",
"I think if we would have to discuss in a https://github.com/huggingface/huggingface_hub/ issue about it and `datasets` could align with what's decided there"
] | 2026-08-10 13:01:44 | 2026-08-16 15:56:33 | null | null | NONE | [] | null | null | null | null | ### Feature request
Replace the httpx library with the [httpx2](https://github.com/pydantic/httpx2) fork, maintained by Pydantic.
### Motivation
Httpx has not been released since December 2024, and has closed all public access to Issues / Discussions / PRs, this raises questions about the actual state of maintenance... | 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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"#self-assign"
] | 2026-08-04 05:36:19 | 2026-08-06 02:08:27 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### 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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"#self-assign\n\nOpened a fix in #8459."
] | 2026-08-04 05:36:00 | 2026-08-10 23:10:37 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### 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/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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"Confirmed on current `main` (`3e2c1a6c3`), and the `Dataset.batch()` half is worse than the title suggests: it hands back the **unbatched** input, so both the row count and the schema are wrong while `IterableDataset.batch()` correctly yields nothing.\n\nExecuted against `3e2c1a6c3` (3-row dataset, `batch_size=5`,... | 2026-08-04 03:21:59 | 2026-09-18 16:59:48 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### 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/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",
"@ebarkhordar i checked #8381 on current main and both default exports still return generators. i saw you kept the branch for #8382. are you planning to reopen it? lmk if i can help refresh the tests, or pick it up if you've moved on.\n",
"Take it. I closed #8382 because it sat a month without a review... | 2026-08-03 18:35:13 | 2026-09-15 06:18:13 | null | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
`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/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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"#self-assign"
] | 2026-07-31 01:50:02 | 2026-08-12 06:30:29 | null | null | NONE | [] | null | null | null | null | ### 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/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,... | 2026-07-29 15:00:19 | 2026-08-29 21:30:28 | null | null | NONE | [] | null | null | null | null | ### 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/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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"#self-assign"
] | 2026-07-24 03:36:32 | 2026-07-24 12:06:21 | 2026-07-24 12:06:21 | null | CONTRIBUTOR | [] | null | null | null | null | ### 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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https://api.github.com/repos/huggingface/datasets/issues/8341 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/8341/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/8341/comments | https://api.github.com/repos/huggingface/datasets/issues/8341/events | https://github.com/huggingface/datasets/issues/8341 | 4,917,723,283 | I_kwDODunzps8AAAABJR6Akw | 8,341 | concatenate_datasets(axis=1) with Arrow format drops the first source's columns | {
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"#self-assign"
] | 2026-07-18 09:41:43 | 2026-07-22 18:35:31 | 2026-07-22 18:35:31 | null | CONTRIBUTOR | [] | null | null | null | null | ### Describe the bug
The Arrow fast path of horizontal concatenation (`concatenate_datasets([...], axis=1)` consumed through `.with_format("arrow")`, or any Arrow/tensor consumer) drops the columns of the first source. The plain-Python path is correct; only the Arrow path diverges.
`HorizontallyConcatenatedMultiSourc... | {
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