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value:### 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 `dat...
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value:docs: make repository structure guide prominent in quickstart (#5971)
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value: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...
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value:Reject duplicate column names in Dataset.select_columns
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value:### 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...
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value:Fix DatasetDict.push_to_hub leaving removed splits in the dataset card
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value: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 forma...
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value:Preserve nullable integer columns in to_json/to_csv/to_sql
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value:### 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` `_batc...
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value:to_json/to_csv/to_sql cast nullable integer columns to float, corrupting values past 2**53
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value:### Describe the bug `Dataset.to_json`, `to_csv`, and `to_sql` write a nullable integer column as floating point rather than integers. All three writers (`io/json.py`, `io/csv.py`, `io/sql.py`) call `batch.to_pandas()` with pyarrow's default `integer_object_nulls=False`, which casts any integer column containing...
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value:## 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 unrel...
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value:ArrayXD fixed-shape integer column with a null row is silently cast to float on the python read path
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value:### Describe the bug A fixed-shape `ArrayXD` column (for example `Array2D(shape=(1, 2), dtype="int64")`) that contains at least one `None` row is silently cast to float on the python read path. `to_dict()` / `to_pylist()` return every value as a float, and integers above 2**53 lose precision, purely because an u...
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value:Use Sequence instead of list for path_or_paths typing
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value: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...
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value:Rebatch arrow source before formatting in IterableDataset.filter to fix resume data loss
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value:## 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...
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value:IterableDataset.filter() checkpoint/resume silently drops the rest of the in-flight Arrow table
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value:### 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 ...
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value:Fix CSV loader dropping on_bad_lines/encoding_errors on pandas 2.0-2.2
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value:### 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 g...
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value: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 ...
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value:Add file_name column option in JSON processing
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value: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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value:Keep flat numeric columns with nulls numeric in numpy format
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value: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...
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value:with_format('numpy') promotes flat float64/int columns with nulls to dtype=object (float32 stays numeric)
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value:### Describe the bug `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...
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value:fix: validate Arrow IPC record batches
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value:## 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 ...
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value:Fix require_storage_embed recursing into require_storage_cast
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value:### 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_stora...
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value:Optimize dataset loading by reusing metadata in `data_files.py`
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value:Fix #8197 This PR addresses the performance overhead during the data files pattern resolution phase by reusing the filesystem metadata that is already fetched by `fs.glob(..., detail=True)`. Previously, this metadata was discarded, requiring a subsequent and redundant `fs.info()` network call in `_get_single_o...
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value:fix: correct typos and improve exception handling patterns
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value:## Summary This PR fixes two types of code quality issues: 1. **Typo fixes**: Correct "simulatenous" to "simultaneous" in 2 places in iterable_dataset.py 2. **Exception handling**: Replace `raise error`/`raise e` with bare `raise` to preserve original stack trace (2 places) ## Changes - `src/datasets/iterable_d...
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value:Fix casting a nullable LargeList to a different inner type
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value:## What's the bug `_combine_list_array_offsets_with_mask` (in `src/datasets/table.py`) rebuilds a list array's offsets with the null bitmap applied, using an `int32` null-fill: ```python offsets = array.offsets if array.null_count > 0: offsets = pa.concat_arrays( [ pc.replace_with_mask(o...
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value:Include archive path in WebDataset TAR read errors
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value:Part of #7280 (WebDataset TAR read errors). The broader `_iter_from_urlpath` part of the issue is left for a follow-up. WebDataset now re-raises `tarfile.ReadError` with the archive path (`{tar_path!r}`) in the message and the original error on `__cause__`, both while advancing the archive iterator and while rea...
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value:Decode Json() columns in Dataset.to_pandas()
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value:## What does this PR do? `Dataset.to_pandas()` returned the raw Arrow storage strings for `Json()` feature columns, while every other in-memory export path decodes them. `to_dict()`, `to_list()`, `to_json()` and `with_format("pandas")` all apply `get_json_field_paths_from_feature` + `json_decode_field`; `to_pand...
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value:Dataset.to_pandas() returns raw JSON strings for Json() columns instead of decoded objects
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value:### Describe the bug `Dataset.to_pandas()` returns the raw Arrow storage strings for `Json()` feature columns, while every other in-memory export path decodes them to Python objects. `to_dict()`, `to_list()`, `to_json()` and `with_format("pandas")` all run `get_json_field_paths_from_feature` + `json_decode_field...
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value:Fix column drop in Arrow path of axis=1 concatenation
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value:Fixes #8341 ### Root cause `HorizontallyConcatenatedMultiSourcesExamplesIterable._iter_arrow` accumulates the concatenated batch with: ```python for name, col in zip(table.column_names, table.columns): new_pa_table = pa_table.append_column(name, col) ``` `pa_table` here is the loop variable that leaked fr...
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value:concatenate_datasets(axis=1) with Arrow format drops the first source's columns
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value:### 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. `HorizontallyConcatenatedMult...
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value:Make Dataset generic to allow specifying column types in typehints
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value:Closes #7719 ## What does this PR do? Makes `Dataset` optionally generic so its column types can be specified in a typehint, similar to how `torch.utils.data.DataLoader[T]` works today (as requested in the issue). Before, the only way to document a dataset's columns was a docstring comment: ```python from dat...
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value:Make the dataset fingerprint independent of Arrow chunking
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value:Fixes #8327. As discussed in the issue, the OOM in `Dataset.from_pandas` comes from `generate_fingerprint`, not from the Arrow conversion. Fingerprinting hashes `dataset.__dict__`, and the underlying `pa.Table` (and the `InMemoryTable` wrapping it) pickles chunk-by-chunk, so the serialized size and the hashing...
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value:Include file size in dataset fingerprint
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value:### Motivation Currently, the dataset cache fingerprints rely entirely on the `ETag`/`etag`/`mtime` metadata fetched during `fs.info()`. If a file's byte size changes on the remote end—and the remote backend fails to reliably update the ETag—the dataset fingerprint stays improperly static. This leads to insidiou...
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value:Bump fsspec and simpler wds compr
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value:this will fix errors in the viewer for webdatasets
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value:docs: add WebDataset example for multiple media files of the same type
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value:Fixes #7413 The WebDataset section of `video_dataset.mdx` only shows one media file per sample. This adds an example where a sample has several files of the same type, such as a base video and a pose video in a sign-language dataset. As confirmed in the issue, a period-separated name before the extension keeps e...
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value:Fix column loss in horizontal concatenation of arrow-backed IterableDatasets
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value:## Bug `concatenate_datasets([...], axis=1)` over arrow-backed `IterableDataset`s (e.g. from `.to_iterable_dataset()`) silently drops the **first** dataset's columns and duplicates the **last** dataset's column. In `HorizontallyConcatenatedMultiSourcesExamplesIterable._iter_arrow`, the merged table is built by ...
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value:This PR updates the type hint for the `path_or_paths` argument in dataset loading methods (`from_parquet`, `from_csv`, `from_json`, and `from_text`) in `src/datasets/arrow_dataset.py`. It replaces `list[PathLike]` with `Sequence[PathLike]`. Since `list` is invariant and `Sequence` is covariant, this prevents u...
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value:Support batched=True in Dataset.to_dict
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value:## What does this do? `Dataset.to_dict(batch_size=..., batched=True)` silently ignores both arguments and always returns the full dict, even though its signature, docstring ("Set to `True` to return a generator that yields the dataset as batches"), and `-> Union[dict, Iterator[dict]]` return type all promise bat...
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value:Raise on length mismatch in batched IterableDataset.map
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value:## Problem `IterableDataset.map(fn, batched=True)` can silently drop or misalign rows when the mapping function changes the batch's row count but does not re-emit every retained input column. In `MappedExamplesIterable._iter`, `prepare_outputs` merges the batch with `transformed_inputs = {**inputs, **processed_...
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value:### Describe the bug The entire datasets-server.huggingface.co backend (the dataset-viewer API) is returning 503 Service Temporarily Unavailable on every route I've tried, not just one endpoint. It reproduces on public datasets with no auth token, so it doesn't appear to be account- or dataset-specific. huggingf...
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value:### Describe the bug Hello! I want to report a bug on the datasets viewer and data studio pages. I have attempted to access it on various datasets from various devices and it will not let me view the dataset this way. I have tried restarting, login in and out but to no success. I use Hugging Face as a reposit...
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value:fix: replace list/List with Sequence in function parameter annotations
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value:Fixes #5354 Replaces `list[T]` with `Sequence[T]` in function parameter type annotations across `arrow_dataset.py`, `dataset_dict.py`, and `iterable_dataset.py`. The built-in `list` is invariant in its type parameter, so passing a `List[str]` where `list[PathLike]` is expected causes a mypy error. `Sequence` i...
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value:Streaming datasets fail with 403 SignatureError: invalid key pair id from xet-bridge-us (Colab, latest libraries)
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value:### Describe the bug I'm unable to stream datasets from the Hugging Face Hub. The issue affects both public datasets (e.g. beans) and gated datasets (ILSVRC/imagenet-1k). The failure occurs before any examples are yielded. The request is redirected to the Xet CDN (xet-bridge-us) and fails with: ``` 403 Forbidd...
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value:`Dataset.from_pandas` allocates ~1 MB per Arrow chunk, Out of Memory errors
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value:### Describe the bug `Dataset.from_pandas` memory usage scales with the chunk count of the backing Arrow array (around 1 MB per chunk). `Dataset.shuffle()` followed by `to_pandas()` produces string columns with one chunk per row, so a 25k-row DataFrame holding ~32 MB of text allocates ~30 GB on the way back th...
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value:docs: replace AutoFeatureExtractor with AutoImageProcessor in image preprocessing docs
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value:Fixes #8199 Replaces deprecated with the modern in the image preprocessing example in .
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value:Fix path traversal via metadata file_name in folder-based builders
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value:Fix #8324 ### Vulnerability The folder-based builders (`imagefolder`, `audiofolder`, `videofolder`, `pdffolder`) resolve each metadata row's `file_name` by joining it to the metadata file's directory with no containment check. A malicious dataset can set `file_name` to a `../`-traversal path or an absolute path...
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value:Path traversal / arbitrary file read via the `file_name` metadata field in `*folder` dataset builders (no `trust_remote_code`)
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value:### Describe the bug reported via email on 9 June 2026 - no acknowledgement or response: Package: datasets (PyPI). Affected file: src/datasets/packaged_modules/folder_based_builder/folder_based_builder.py Affected Versions: confirmed on 5.0.0 (PyPI) and HEAD 63e103e. CVSS: CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I...
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value:Raise on Dataset.rename_columns name collision with an existing column
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value:### What `Dataset.rename_column` (singular) already rejects a new column name that collides with an existing column: ```python >>> ds.rename_column("foo", "bar") # "bar" already exists ValueError: New column name bar already in the dataset. ... ``` `Dataset.rename_columns` (plural, dict-based) has no equivale...
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value:feat: use `ListLike` instead of `list` in path type hints
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value:--- ## Description Changed type annotations from `list[PathLike]` to `ListLike[PathLike]` in `from_csv`, `from_json`, `from_parquet`, and `from_text`. `list` type hints are invariant — passing a `tuple` of paths fails mypy even though it works fine at runtime. `ListLike` (defined in `src/datasets/utils/typing.p...
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value:Fix: Resolve Sequence type hints and add from_jsonl alias (#5354)
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value:Fixes #5354 ## Proposed Changes - Updates features typing to use Sequence instead of List/Tuple in from_json and from_parquet parsing functions. - Adds from_jsonl as an explicit wrapper to from_json for dataset creation, providing API symmetry with to_jsonl. - Includes dedicated tests for the new from_jsonl alia...
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value:docs: add community health files (CHANGELOG.md)
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value:## Summary Adds missing open-source community health files: - **CHANGELOG.md** — Keep a Changelog format, Semantic Versioning - **README.md** — contributor profile link ### Why These files help contributors understand how to participate and set community expectations. --- *[Mukller](https://github....
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value:Cast multi-dimensional numpy arrays when inferring IterableDataset features
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value:## Summary `IterableDataset._resolve_features()` crashes when a `map` function yields multi-dimensional numpy arrays: ```python from datasets import Dataset import numpy as np ds = Dataset.from_dict({"a": [[[1, 2, 3], [1, 2, 3]]]}).to_iterable_dataset().map(lambda x: {"a": [np.array(x["a"])]}) ds._resolve_featu...
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value:Vectorize interleave_datasets index generation (probabilities + first/all_exhausted)
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value:## What `_interleave_map_style_datasets` (used by `interleave_datasets` for map-style `Dataset`s) builds the output index list in a **pure-Python `for`-loop, one iteration per output row**, when `probabilities` is given: ```python for source_idx in iter_random_indices(): if bool_strategy_func(is_exhausted):...
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value:fix(json): produce valid JSON when lines=False spans multiple batches (#7037)
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value:## Summary Fixes #7037. `Dataset.to_json(lines=False)` raised `NotImplementedError` (and before the guard was added, silently produced _invalid_ JSON) whenever `batch_size < num_rows` — i.e., the default case for any dataset larger than `DEFAULT_MAX_BATCH_SIZE` (1000 rows). **Root cause:** Each batch was seria...
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value:Preserve features after IterableDataset.add_column
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value:## What `IterableDataset.add_column` delegates to `map` but never propagates the schema. After the call, `dataset.features` is `None` even when the original dataset had a typed schema, silently breaking all downstream code that inspects features. ## Root cause The implementation is a one-liner: ```python retur...
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value:Fix size_str(0) returning "Unknown size" instead of "0 bytes"
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value:`size_str` uses `if not size_in_bytes:` to return `"Unknown size"`, which also catches `0`. But `0` is a valid size (0 bytes), and the docstring states that only `None` means "Unknown size". So a 0-byte size (e.g. an empty split) currently renders as "Unknown size": ```python >>> from datasets.utils.py_utils ...
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value:Fix to_json(lines=False) producing invalid JSON for multi-batch datasets
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value:Fixes #7037. to_json(lines=False) concatenated batch JSON arrays directly (like [...][...][...]), which is invalid JSON. Fixed by stripping outer brackets from each batch with orient=records and wrapping in a single array.
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value:Fix crash on millisecond-scale started_at in hermes agent traces
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value:## Summary Parsing a hermes-format agent trace whose `started_at` is expressed in milliseconds crashes with `OSError: [Errno 22] Invalid argument`. ## The bug `src/datasets/packaged_modules/json/json.py` normalizes `started_at` before feeding it to `datetime.fromtimestamp` (which expects **seconds**), using a ...
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value:Fix Dataset.take raising IndexError when taking more elements than available
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value:### Description `Dataset.take(n)` is implemented as `self.select(range(n))`, so when `n` is larger than the dataset length it raises `IndexError: Index N out of range for dataset of size M` instead of returning the whole dataset. This is inconsistent with `IterableDataset.take`, which clamps and returns all avail...
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value:Fix silent dataset truncation in batched map with mismatched empty column (#6879)
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value:## What does this PR do? Fixes #6879. `Dataset.map(fn, batched=True)` silently truncates the dataset to **0 rows** (instead of raising) when the mapping function empties an *existing* column while another column stays non-empty. ### Reproducer (from the issue) ```python import datasets data = datasets.Dataset...
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value:Make patch_submodule robust to __builtins__ being a module (PyPy / __main__)
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value:Closes #7636. ### Problem `patch_submodule` reads the builtins through `globals()["__builtins__"]`: ```python elif target_attr in globals()["__builtins__"]: # if it's a builtin like "open" self.original[target_attr] = globals()["__builtins__"][target_attr] ``` The value of a module's `__builtins__` globa...
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value:Streaming IterableDataset state stops advancing after first resume — second resume restarts from the beginning
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value: ## Description For a streaming `IterableDataset`, calling `load_state_dict()` and then continuing to iterate leaves `state_dict()` frozen at the initial position (`shard_idx=0`, `shard_example_idx=0`). Reading resumes correctly the first time, but the tracked state never advances again. This causes a second co...
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value:Improve missing tsfile dependency error
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value:Related to #8256 This PR improves the error message when the optional `tsfile` dependency is unavailable. Currently, loading a TSFile dataset without `tsfile` installed raises a raw: ModuleNotFoundError: No module named 'tsfile' This change raises a clearer ImportError instead: ImportError: To supp...
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value:Fix `add_column` parameter order so `feature` precedes `new_fingerprint`
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value:### What `Dataset.add_column`'s signature is `(name, column, new_fingerprint=None, feature=None)`, but: - its own docstring documents the third argument as `feature` (not `new_fingerprint`), and - every sibling `@fingerprint_transform` method keeps `new_fingerprint` as the **last** parameter (e.g. `cast_column(...
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value:Extractor.extract() called shutil.rmtree(output_path, ignore_errors=True) before extracting. Since Python 3.8, shutil.rmtree() raises OSError on a symlink pointing to a directory, which ignore_errors=True silently swallows. An attacker with write access to a shared cache directory could pre-plant a symlink at the...
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value:Turkish DIK-style Syntactic Structure Benchmark Dataset
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value:### Feature request A structured dataset proposal introducing a Turkish syntactic structure benchmark designed for evaluating LLMs on fine-grained grammatical reasoning in a morphologically rich language. Current NLP datasets in Hugging Face focus heavily on surface-level semantic tasks or English-centric bench...
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value:Fix lance auth
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value:fix two bugs - `TypeError: argument 'storage_options': 'None' is not an instance of 'str'` because "token": None is not supported in storage_options - download_config.storage_options was empty and therefore the token for private datasets was not passed to lance
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value:Fix MetadataConfigs dropping parquet shards for non-consecutive configs
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value:Fixes #8269 ## Problem `MetadataConfigs._from_exported_parquet_files_and_dataset_infos()` groups the exported parquet files with `itertools.groupby(exported_parquet_files, itemgetter("config"))`. `groupby` only groups **consecutive** equal keys, but the result is built as a dict keyed by config name: ```python...
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value:Replace distutils.util.strtobool in tests with a local helper
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value:## What this fixes `tests/utils.py` imports `strtobool` from `distutils.util`: ```python from distutils.util import strtobool ``` `distutils` was removed from the standard library in **Python 3.12** ([PEP 632](https://peps.python.org/pep-0632/)). `tests/utils.py` is imported (via `from .utils import ...`) by *...
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value:Fix: preserve features after IterableDataset.add_column (GH#5752)
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value:## Problem After calling `.add_column()` on a streaming `IterableDataset`, accessing `.features` returns `None`: ```python from datasets import load_dataset ds = load_dataset("...", streaming=True) print(ds.features) # {'text': Value('string'), ...} ds2 = ds.add_column("new_column", ["val"] * len(ds)) print(...
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value:[security] Symlink-Following Arbitrary File Write via Archive Extraction in huggingface/datasets
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value:### Describe the bug ## Summary A symlink-following vulnerability exists in the archive extraction subsystem of `huggingface/datasets` that allows a local attacker with write access to a shared HuggingFace cache directory to write arbitrary files with the victim's privileges, by pre-planting a symlink at a pred...
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value:Bug Fix: Resuming Twice Resets the Dataloader
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value:## Summary For a streaming `IterableDataset`, calling `load_state_dict()` and then continuing to iterate leaves `state_dict()` at the initial position (`shard_idx=0`, `shard_example_idx=0`). Reading resumes from the correct place, but the the state never advances again. The practical consequence shows up o...
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value:docs(py_utils): add missing docstrings to 5 public utility functions
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value:## What does this PR do? Adds missing docstrings to five public utility functions in `src/datasets/utils/py_utils.py`. Each docstring follows the HuggingFace documentation style with `Args`, `Returns`, `Raises`, and `Example` sections. **Functions documented:** | Function | What it does | |---|---| | `glob_pat...
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value:Support concatenating multiple streaming datasets while preserving the sum of shards
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value:### Feature request It would be useful if concatenating multiple `IterableDataset`s could preserve the shard information from each input dataset, so that: - the total number of shards equals the sum of the input shards; - `split_dataset_by_node()` and worker sharding continue to work efficiently; - downstream d...
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value:SuperCompress: Cut LLM token costs by ~65% with open-source prompt compression
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value:## SuperCompress: Open-Source Prompt Compression [SuperCompress](https://github.com/arjunkshah/supercompress) is a learned prompt compression library that reduces LLM token usage by ~65% using a ~5K parameter neural policy. **Why this matters for ML development:** - Practical ML deployment: a tiny model (~5K pa...
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value:Add `skip_origin_metadata` flag to optimize streaming startup time
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value:Fix #8197 This PR introduces the `skip_origin_metadata` kwarg to skip costly origin metadata fetching (ETags/mtime) when it's not needed, improving streaming initialization latency. This saves number of files `fs.info` calls per `load_dataset` call. ### Changes - **Kwarg Plumbing**: Routes the `skip_origin_m...
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value:Fix docstring example for select_columns in IterableDatasetDict
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value:Fix docstring example for select_columns in IterableDatasetDict. This PR updates the usage example for selecting columns in a streaming dataset. The example now correctly uses the `select_columns` method instead of the outdated `select` method. ### Changes - **Documentation update:** * Updated the exa...
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value:Add regression test suite for datasets (QA)
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value:## What does this PR do? Adds a data-driven manual/semi-automated **regression test suite** for `datasets` at `tests/regression/regression_suite.md` (128 test cases). The suite was built by mining 984 historical issues (2020-04 → 2021-09) to find the bug categories that keep repeating, cross-checking the curren...
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value:Fix duplicate word in HubBucketDatasetModuleFactory docstring
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value:Removes a duplicated "a" in the `HubBucketDatasetModuleFactory` docstring in `src/datasets/load.py`: "...data files of a a Storage Bucket." → "...data files of a Storage Bucket." Documentation-only change; no code behavior affected.
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value:docs(video_load): fix typos 'effiently' and 'whithin'
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value:Fixes two typos in `docs/source/video_load.mdx`: - "effiently" -> "efficiently" in the description of `get_frames_in_range` - "whithin" -> "within" in the description of `get_frames_played_in_range` Both flagged by `typos` (typos-cli 1.47.2) and verified by reading the surrounding context. ## AI assistance Thi...
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value:Share fsspec filesystem across threads when resolving data files
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value:## What does this PR do? Fixes #8149. `_get_origin_metadata` resolves each data file in a `ThreadPoolExecutor` and every worker builds its own filesystem via `url_to_fs` since fsspec caches filesystem instances per thread. For cloud backends like `s3://` or `gcs://` this re-resolves credentials and opens a ...
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value:fix: pass hub token when embedding external files during push_to_hub
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value:## Summary - Fixes gated-repo failures when `Dataset.push_to_hub(..., embed_external_files=True)` embeds `hf://` image/audio paths into Parquet shards. - `_push_parquet_shards_to_hub_single` now builds a `token_per_repo_id` map from shard paths (and destination repo metadata) and passes it to `embed_table_storage...
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value:Hash frozensets deterministically
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value:While looking at how transforms get fingerprinted I noticed `frozenset` isn't hashed deterministically, unlike `set`. `set` has a custom reducer (`_save_set`) that pickles its elements sorted, so the fingerprint is stable across runs. `frozenset` has no such reducer and falls back to the default one, which keeps...
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value:Fix CI: commit operation equality (hfh 1.20.0) and pytest parametrize collection error
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value:Fixes two unrelated CI failures (seen e.g. in the `huggingface_hub` 1.21.0.rc0 test run, but **the first one already affects `main` with the latest stable `huggingface_hub`**). ## 1. `tests/test_hub.py::test_delete_from_hub` Since `huggingface_hub` 1.20.0 (introduced in https://github.com/huggingface/huggin...
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value:Fix Mypy typing invariance by updating List to Sequence in dataset loading functions (#5354)
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value:## Description This PR addresses issue #5354. The standard `typing.List` (or built-in `list`) is invariant in Python, meaning static analyzers like Mypy will complain if a user tries to pass a tuple or another valid sequence into the dataset loading parameters (e.g. `data_files`). By refactoring these type hints...
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value:Fix fixed size binary
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value:The original issue is a crash in _arrow_to_datasets_dtype because the miss of support of fixed_size_binary: ``` Exception: SplitsNotFoundError Message: The split names could not be parsed from the dataset config. Traceback: Traceback (most recent call last): File "/usr/local/lib/...
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value:fix: ensure to_json(lines=False) produces valid JSON
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value:Fixes #7037: when lines=False, multi-batch writes produced invalid concatenated JSON arrays. Now forces a single batch.
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value:requires https://github.com/TeichAI/teich/pull/12 as well
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value:## What does this PR do? Fixes ~20 typos in docstrings, comments, and messages (no functional changes). Examples: `informations`→`information`, `simulatenous`→`simultaneous`, `acculumation`→`accumulation`, `ambigious`→`ambiguous`, `conveniant`→`convenient`, `unstructred`→`unstructured`, `lenth`→`length`, `compre...
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value:fix(json): write valid JSON array when lines=False with batching
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value:## Summary - Fix `Dataset.to_json(lines=False, orient="records")` when the dataset is larger than `batch_size` - Previously each batch wrote a separate top-level JSON array (`[...][...]`), producing invalid JSON (`JSONDecodeError: Extra data`) - Merge batched pandas outputs into one array by stripping per-batch b...
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value:aFixes a handful of spelling typos across the docs and source comments/docstrings. This is a documentation/comment-only change; no functional code is affected. Changes: docs/source/process.mdx: colums -> columns docs/source/video_load.mdx: effiently -> efficiently; whithin -> within src/datasets/arrow...
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value:Docs: Fix dataset link in access tutorial
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value:Actual link returns 404. Updated the URL to the new dataset location
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value:fix: report the correct variable type in fingerprint_transform ignore_kwargs validation error
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value:The `ignore_kwargs` validation branch in `fingerprint_transform` builds its error from `type(use_kwargs)` instead of `type(ignore_kwargs)`, so an invalid `ignore_kwargs` is reported with the wrong type while `use_kwargs` is at its default. The preceding `use_kwargs` branch already uses `type(use_kwargs)` correctl...
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value:fix(dataset): accept pathlib.Path in save_to_disk and load_from_disk
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value:Fixes #8269 `groupby()` on unsorted exported parquet rows dropped earlier shards when the same config reappeared later in the list. Sort by `(config, split)` first. Regression test: `test_non_consecutive_config_rows_are_merged_in_metadata_configs_from_exported_parquet_files` ``` rootdir: /tmp/datasets configfi...
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value:## Bug `_from_exported_parquet_files_and_dataset_infos()` uses `itertools.groupby()` on unsorted `exported_parquet_files`. If the same `config` appears again after another config, the earlier shard URLs are lost. ## Repro ```python from itertools import groupby from operator import itemgetter exported = [ ...
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value:2026-06-14T04:07:09Z
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