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value:Fix Dataset.select OverflowError on negative indices
value:2026-09-24T14:40:00Z
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value:## Description `Dataset.__getitem__` accepts Python negative indices (`ds[-1]`, `ds[[-1]]`), and `_check_valid_indices_value` already allows them in `select`. Building the indices mapping still passed those values to `pa.array(..., type=uint64)`, which raised `OverflowError`. Resolve negatives to absolute posit...
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value:Bump huggingface_hub upper bound to <3.0 (datasets)
value:2026-09-24T12:24:34Z
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value:2026-10-05T14:00:33Z
value:### Requires `transformers` release for CI to pass (i.e. https://github.com/huggingface/transformers/pull/49083) --- Allow `huggingface_hub` 2.x by bumping the upper bound to `<3.0` (lower bound unchanged). `huggingface_hub` 2.0 was just released ([release notes](https://github.com/huggingface/huggingfac...
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value:Fix inverted span for minus-strand multi-exon GenBank locations
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value:## What was wrong `GenBank._parse_location_node` computes the aggregate span of a `join`/`order` location from the *positional* first and last parts: ```python location["start"] = located[0]["start"] location["end"] = located[-1]["end"] ``` This assumes the parts are listed in ascending genomic order. They are...
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value:Fix JSON loader when mixed-shape JSONL chunks differ by keys
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value:Fixes #8675. `load_dataset("json")` inferred each JSONL chunk on its own, then cast later chunks onto the first chunk's columns. When `chunksize` split sorted mixed shapes, a later shape with new keys failed that cast. Before taking the schema from the first table, cast every chunk table to the union schema (`p...
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value:load_dataset("json") fails on mixed-shape JSONL when a chunksize boundary separates the shapes
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value:### 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`...
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value:Key parquet column options by leaf path so nested columns get compressed
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value:Fixes #8671 ## Summary `pq.ParquetWriter` matches per-column `compression` / `use_dictionary` / `column_encoding` against the leaf column paths (`train.list.element.input...`), but both `ParquetWriter._build_writer` and `ParquetDatasetWriter._write` keyed them by top-level feature name. Nested list/struct colum...
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value:Pin GitHub Actions to commit SHAs
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value:2026-09-23T13:45:25Z
value:## Workflow hardening ### Actions pinned to commit SHAs A version tag is mutable. Whoever controls an action's repository can move `v4` to different code, and every workflow referencing `@v4` picks that up on the next run with nothing to review. That is how `tj-actions/changed-files` shipped a credential dumper...
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value:Scope GITHUB_TOKEN permissions per job
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value:## Workflow hardening ### `GITHUB_TOKEN` permissions scoped per job A workflow with no `permissions:` block inherits whatever the repository or the organization hands out, which is commonly write access to everything. Any step in that job — including one inside a third-party action — can then push commits, open...
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value:push_to_hub() / to_parquet() leave nested list/struct columns uncompressed
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value:### Describe the bug `push_to_hub()` and `to_parquet()` silently write nested (list/struct) columns UNCOMPRESSED, while flat columns get snappy. Measured impact: ~30x size inflation for nested-column datasets (a 114 MB JSONL with list/struct columns pushes as a 215 MB shard; the same data with compression applie...
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value:`IterableDataset.shuffle()` currently interleaves the source shards before node and DataLoader worker sharding. With 19 source shards and the default settings, the resulting dataset reports one shard, leaving three of four DataLoader workers idle. This adds a dedicated iterable that preserves the source shard co...
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value:`IterableDataset.shuffle()` in 5.0 reports `num_shards = min(files per source)`, leaving DataLoader workers and distributed nodes without data
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value:### Describe the bug I recently updated an env to datasets 5.0.1 and ended up with several of my DataLoader workers spinning. Spinning issue is on my end, and there is a viable workaround, but there's a change on the datasets side that triggered and may be unexpected / sub-optimal in common use cases. Since 5....
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value:Fix from_spark(working_dir=...) failing to move its shards
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value:`Dataset.from_spark(..., working_dir=...)` cannot work today: the shard-move step raises `NameError`. `Spark._prepare_split_single` writes each worker's shards into `working_dir` and then moves them into the cache directory: ```python if working_fpath != fpath: for file in os.listdir(os.path.dirname(working...
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value:Fix ClassLabel.int2str rejecting numpy integer labels
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value:`ClassLabel.int2str()` rejected numpy integer scalars (`np.int64`, `np.int32`) with `ValueError: Values 0 should be an integer`. That is the type `Dataset.set_format("numpy")` returns for a ClassLabel column, so this public call crashed: ```python ds.set_format("numpy") ds.features["label"].int2str(ds[0]["label...
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value:Fix broken internal anchor link in share.mdx
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value:2026-09-30T15:13:53Z
value:## What Fixed an outdated internal anchor link in docs/source/share.mdx pointing to repository_structure.mdx#define-your-splits-in-yaml (404) instead of the current heading anchor #define-your-splits-and-subsets-in-yaml. ## Why A small, objectively-verifiable improvement (broken-link) found during a daily open-s...
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value:Batch in arrow when the source is arrow-backed, and let `_consolidate` type numpy scalars
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value:2026-10-05T12:51:00Z
value:Fixes #8663 **1. `IterableDataset.batch()` takes arrow-backed data out of arrow for no reason** (`iterable_dataset.py`). It regroups via a Python transpose, `_batch_fn`, which converts arrow to Python examples and transposes them back. #8126 already added an arrow path for this, gated on `self._formatting....
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value:Keep the declared numpy dtype when a batch is regrouped from formatted rows
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value:2026-10-12T16:48:28Z
value:## Summary `NumpyFormatter._consolidate` only stacks a column when every element is an `np.ndarray`. Numpy scalars are `np.generic`, not `np.ndarray`, so any path that hands the formatter a list of scalars falls into the `dtype=object` branch: - `IterableDataset.batch()` regroups with a python transpose (`{k: [...
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value:### Describe the bug `NumpyFormatter._consolidate` builds a typed array only when every element is an `np.ndarray`. numpy **scalars** are `np.number`, not `np.ndarray`. ### Face 1 — `IterableDataset.batch()` on an arrow-backed dataset `.batch()` regroups via a Python transpose (`_batch_fn = lambda unbatched: {...
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value:Speed up JSON export of indexed datasets
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value:Fixes the remaining indexed-export slowdown described in #3419. Non-contiguous selections and shuffles still leave an indices mapping. Querying a JSON export batch then produces one Arrow chunk per selected row, making conversion to pandas expensive. Combine the queried batch before conversion, while keeping the...
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value:Validate a split name against the whole string
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value:## Summary Eight checks in the library validate a split name with `re.match(_split_re, name)` and, when it fails, raise `Split name should match '^\w+(\.\w+)*$' but got '<name>'`. The message promises a full match, but `"$"` also matches right before a newline at the end of the string, so a name such as `"train\...
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value:Fix empty translations with declared languages
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value:Fixes #8659. With declared languages, `TranslationVariableLanguages` raises a `ValueError` for `{}`, `{"en": []}`, and other inputs containing no translations. Return `{"language": [], "translation": []}` when normalization produces no translation pairs, after validating the language names. Regression tests cov...
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value:TranslationVariableLanguages crashes on empty translations with declared languages
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value:## Describe the bug With an explicit language list, `TranslationVariableLanguages.encode_example()` raises `ValueError: not enough values to unpack (expected 2, got 0)` for `{}`, `{"en": []}`, or `{"en": [], "fr": []}`. The same inputs also prevent `Dataset.from_dict()` from constructing a dataset. The equivale...
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value:Fix push_to_hub for IterableDataset with unknown features
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value:An IterableDataset can have unknown features (features=None), e.g. when built with IterableDataset.from_generator() without `features=`, or when streaming CSV files (or JSON files that require a full read) without declared features. IterableDataset._push_parquet_shards_to_hub() then crashed at the decodable-co...
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value:[docs] Fix legacy hf CLI references (datasets)
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value:The docs and a few docstrings still use commands that are no longer the recommended `huggingface_hub` usage in 1.x: `hf` replaced `huggingface-cli`, `hf repos` replaced `hf repo`, and `--organization` was replaced by a namespaced repo id. - `docs/source/share.mdx`: `huggingface-cli login` → `hf auth login`, `hug...
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value:Fix EXIF orientation for in-memory PIL image inputs
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value:Serializing an in-memory PIL image through `Image` drops its EXIF orientation before decoding can apply the transpose added in #6739. The same JPEG with orientation 6 is decoded as `(4, 8)` when supplied as bytes, but `(8, 4)` when supplied as `PIL.Image.open(BytesIO(...))`. This also reproduces on the 5.0.1 rele...
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value:Format a zero size as "0 bytes" instead of "Unknown size"
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value:`size_str()` documents that it returns `"Unknown size"` when `size_in_bytes` is `None`: ```python def size_str(size_in_bytes): """Returns a human readable size string. If size_in_bytes is None, then returns "Unknown size". ... """ if not size_in_bytes: return "Unknown size" ``` The ...
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value:Fix mutual exclusion for long lock filenames across processes
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value:Fixes #8653. Long lock filenames are shortened with Python's process-randomized string hash. Independent processes can therefore acquire different lock files for the same original path, bypassing mutual exclusion. This can affect the cache-directory lock in `DatasetBuilder`, where the directory path is flattened...
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value:### Describe the bug `FileLock.hash_filename_if_too_long()` uses Python's `hash(filename)` to shorten long lock filenames. String hashes vary between independently started Python processes, so two processes given the same long lock path can lock different files and both enter the protected section. This affects...
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value:Read JSON floats exactly in the pandas fallback
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value:`pandas_read_json()` in `packaged_modules/json/json.py` calls `pd.read_json()` with pandas' default float parser, which is fast but not round-trip exact: ```python >>> import io, pandas as pd >>> pd.read_json(io.StringIO('{"v": 0.7}\n'), lines=True)["v"][0] np.float64(0.7000000000000001) >>> pd.read_json(io.Stri...
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value:Fix Python 3.14 dict pickling compatibility
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value:Closes #8373. ## Summary - passes the new Python 3.14 `_batch_setitems` object argument when the custom datasets pickler is called through the old two-argument path - keeps the existing key sorting behavior for stable fingerprints - adds a regression test that simulates the Python 3.14 parent pickler sign...
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value:## Summary When datasets are stored in nested remote directories, loading a child directory first can make loading its parent fail with `FileNotFoundError` for `state.json`. Reloading a remote dataset after its contents change can also return the previous rows. Each load now gets a fresh directory inside the ma...
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value:Apply the bit-to-byte conversion to binary units too
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value:`convert_file_size_to_int` already distinguishes bits from bytes: a unit ending in a lowercase `b` is read as bits and divided by 8. That check is only applied to the decimal branches, though, so the binary ones return a bit size as if it were bytes, eight times larger than asked for: ```python >>> from datasets...
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value:Pin UTF-8 encoding when reading eval sample logs
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value:## Problem The `eval` packaged module reads sample log JSON files with the locale's preferred encoding: ```python for sample_file in sample_files: with open(sample_file) as f: sample = json.load(f) ``` On Windows with a non-UTF-8 locale (e.g. cp936/GBK), any sample containing non-ASCII text — CJK p...
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value:Fix IterableDataset.filter() with no function
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value:`list(dataset.filter())` raises `TypeError` because the iterator tries to call `None`. The documented default is to keep all rows. Return a new dataset wrapper when no function is supplied. Returning a new object, rather than `self`, keeps changes to its epoch from affecting the input dataset. Tests cover t...
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value:Fix map(drop_last_batch=True) returning the input unchanged when all batches are dropped
value:2026-09-20T03:18:53Z
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value:Fixes #8386. When `drop_last_batch=True` and a shard is smaller than `batch_size`, `_map_single` iterates zero batches, so the map function never runs and `update_data` stays `None`. The final branch then yielded the original shard back unchanged (3 rows instead of 0), disagreeing with `IterableDataset.batch` an...
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value:Support class encoding list-valued columns
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value:Fixes #6267 class_encode_column currently rejects list-valued columns even when the feature is List(Value(...)). That makes multi-label datasets fall back to manually collecting labels and calling cast_column. This change accepts List(Value(...)) columns, collects class names from the list elements, and maps ea...
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value:fix(py_utils): save/restore NPU RNG state in temp_seed
value:2026-09-18T13:24:23Z
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value:## Description When `set_pytorch=True` is passed to `temp_seed`, the context manager saves and restores the PyTorch CPU and CUDA RNG states. On non-CUDA accelerators (e.g. Ascend NPU), the device RNG state is silently left unseeded during the context, breaking reproducibility across seeded dataset transforms. T...
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value:Forward Dataset.cast arguments from DatasetDict.cast
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value:## What `DatasetDict.cast` now accepts the same processing arguments as `Dataset.cast` (`batch_size`, `keep_in_memory`, `load_from_cache_file`, `writer_batch_size`, `num_proc`) plus `cache_file_names` as a per-split dict, and forwards them to each split. ## Why `Dataset.cast` runs through `map` and exposes the...
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value:Do not rebuild a finalized ArrowWriter, so a failing stream close is not masked
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value:Follows the discussion on #8558. Separate PR because that one fixes call sites in the builders and this fixes the writer itself, so they can be reviewed or reverted independently. @lhoestq happy to fold them together if you would rather have one change. Line numbers below are against `main`. ## The problem `fi...
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value:Convert a dense ArrayXD column in one pass instead of per row
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value:Towards #4964. This reduces the construction overhead rather than removing it, and the numbers below say by how much. ### What is slow Building a `Dataset` from a whole ndarray converts it row by row and then concatenates. On this machine, 3200 rows of 64x64 float32, a 50 MB payload: | | peak RSS over baseline...
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value:Name the column in map() type mismatch errors and restore the overflow hint
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value:Closes #4352. ### The problem When a `map()` function returns values that do not match the declared features, the error never says which column is at fault. On a wide dataset that leaves you bisecting your own function to find it. Measured on `main`, all four mismatch shapes: | case | before | |---|---| | dec...
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value:Document the formatter dtype coercion and pin it with tests
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value:Closes #5517. ### What users hit A column stored as `float64` comes back as `float32`: ```python >>> ds = Dataset.from_dict({"v": [[3.141592653589793, 1e300]]}, ... features=Features({"v": List(Value("float64"))})) >>> ds.with_format("numpy")[0]["v"] array([3.1415927e+00, inf],...
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value:Add HF_DATASETS_USE_SOFT_FILELOCK for filesystems without OS-level locking
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value:Closes #6744. ### The problem `load_dataset` takes cache locks through `filelock`, which uses `flock`/`fcntl`. Some network filesystems do not implement those calls, so the lock fails and the dataset never loads. The reporter hit this on an NFS-mounted Weka mount. Moving `cache_dir` to local disk is not a way o...
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value:FileLock wrapper drops timeout and every other constructor argument
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value:### 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...
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value:Automated hardening of the workflow files flagged on #8635. > [!WARNING] > **This narrows what the workflow can reach.** Job permissions were declared in `.github/workflows/ci.yml`, `.github/workflows/release-conda.yml`. Each job now gets only the scopes its steps were read to need — if one of them does somethin...
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value:Bump the actions group with 7 updates
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value:Bumps the actions group with 7 updates: | Package | From | To | | --- | --- | --- | | [huggingface/doc-builder/.github/workflows/build_main_documentation.yml](https://github.com/huggingface/doc-builder) | `90b4ee2c10b81b5c1a6367c4e6fc9e2fb510a7e3` | `47c6b5880f408881e68ca60fed8c1de1e454eb01` | | [huggingface/doc...
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value:fix: accept pathlib.Path in load_from_disk, save_to_disk, and DatasetInfo
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value:Fixes #6829. ### Problem Calls passing `pathlib.Path` objects (e.g. `ds.save_to_disk(Path(...))`, `Dataset.load_from_disk(Path(...))`, `DatasetDict.load_from_disk(Path(...))`, `DatasetInfo.from_directory(Path(...))`) fail with `TypeError: argument of type 'PosixPath' is not iterable` from `fsspec` because `url_t...
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value:url_to_fs expects a str and raises an error when given a pathlib.Path. This was a regression introduced in #6704, which changed load_from_disk and save_to_disk to use url_to_fs directly without converting Path to str. Fix: wrap dataset_path with str() before passing to url_to_fs in both load_from_disk and save...
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value:fix default iterable dataset dict and polars exports
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value:Fixes #8381. Picks up #8382 after [the original author handed it over](https://github.com/huggingface/datasets/issues/8381#issuecomment-5675668289). The original fix is by @ebarkhordar. `to_dict()` and `to_polars()` return generators even with `batched=False`, because both methods contain a `yield` in their batc...
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value:Fixes #8596. Validate `ClassLabel` values during table casts while keeping the metadata-only path for other features.
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value:Make two test comparisons actually assert
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value:Two tests evaluate a comparison and throw the result away, so those checks can never fail. **`tests/test_builder.py::test_builder_as_dataset`**: `dataset.column_names == ["text"]` is missing its `assert`. **`tests/commands/test_test.py::test_test_command`**: the loop over `DatasetInfo._INCLUDED_INFO_IN_YAML` en...
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value:`Dataset.map()` creates an event loop for an async callback but never closes it. When a callback fails, gathering the cancelled tasks can also propagate the first failure before sibling callbacks finish their asynchronous cleanup. Move task cleanup into `finally`, wait for all tracked tasks with `return_except...
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value:Skip tar-symlink extraction test when symlinks are unavailable
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value:## What `tests/test_extract.py::test_tar_extract_insecure_files` errors in setup on an unprivileged Windows machine: ``` OSError: [WinError 1314] A required privilege is not held by the client ``` The `tar_file_with_sym_link` fixture calls `os.symlink(...)` unconditionally, and the test requests all three tar ...
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value:Fix probabilistic interleave of empty sources without replacement
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value:Fixes #8626. When probabilistic `interleave_datasets` uses `all_exhausted_without_replacement`, an empty source starts as not exhausted. Its first draw appends an invalid source offset, producing a duplicate row from the next dataset or an `IndexError` when the empty source is last. Mark empty sources exhausted...
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value:### Describe the bug With probabilities and `stopping_strategy="all_exhausted_without_replacement"`, an empty map-style input can add a duplicate row from another source or cause an out-of-range index. This can happen when filtering one of the datasets before mixing them. ### Steps to reproduce ```python from ...
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value:Refactor README.md by removing HTML elements
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value:Removed HTML content and updated the README structure.
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value:Fix docstring argument names that don't match the signatures
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value:Five public docstrings document parameters under names the functions don't accept, so code written from the docs fails with `TypeError: got an unexpected keyword argument`: | Function | Docstring says | Signature has | |---|---|---| | `Dataset.train_test_split` | `train_cache_file_name`, `test_cache_file_name` |...
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value:Keep origin_metadata aligned in DataFilesList.filter
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value:## Summary Fixes #8618. `DataFilesList.filter()` returns a filtered list of data files but reuses the original, unfiltered `origin_metadata`. `origin_metadata` is parallel to the file list (one entry per file describing where the file was resolved from), so after filtering it no longer lines up with the files i...
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value:Fix SplitDict.copy() crashing when dataset_name is None
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value:## Summary Fixes #8617. `SplitDict.copy()` crashes with `AttributeError: 'SplitInfo' object has no attribute 'get'` whenever the `SplitDict` holds `SplitInfo` objects (the normal case after construction) and `dataset_name` is not passed explicitly. In `SplitDict.from_split_dict`, the `dataset_name` fallback un...
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value:`DataFilesList.filter()` leaves `origin_metadata` misaligned with the filtered files
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value:## Description `DataFilesList` keeps `origin_metadata`, a list parallel to the file list where each entry describes the origin of the file at the same index (e.g. the data files pattern it was resolved from). After `filter()` removes some files, the returned `DataFilesList` keeps the *unfiltered* `origin_metadat...
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value:`SplitDict.copy()` crashes when `dataset_name` is not set
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value:## 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 = Split...
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value:test(utils): add unit test suite for dataset repository path and name sanitization
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value:2026-10-10T22:21:54Z
value:### Summary Adds focused unit tests in `tests/test_dataset_name_invariants.py` verifying repository path identifier parsing: - Confirms organization namespace and dataset name separation. - Validates clean fallback handling for unnamespaced identifiers. - Non-invasive, test-only addition.
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value:Publish extraction caches atomically so concurrent jobs never read partial output
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value:Resolves #4661 ## Root cause `ExtractManager.extract` decided "already extracted" (output file exists, or output directory non-empty) **before** `Extractor.extract` took the per-output `FileLock`, and the extractor wrote straight into the final path. With two jobs sharing a cache directory, job B saw job A's ha...
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value:Fingerprint functions from the user's own modules by value
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value:`Hasher.hash` builds the `map()` fingerprint from `_dill.dumps`, and dill dumps a function it can import as a module-qualified name. For a mapping function imported from the user's own module the dump is 35 bytes of module and qualname with no code object in it, so editing the body leaves the fingerprint unchange...
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value:Resolve a legacy dataset name to its canonical repo id
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value:`load_dataset("imdb")` dies with an `HfUriError` about a `.huggingface.yaml` nobody asked for, and so do `squad`, `glue`, `rotten_tomatoes`, `ag_news`, `cnn_dailymail`, `mnist` and `wikitext`. The Hub still redirects these names, so the first half of the load works: `hf_hub_download(repo_id="imdb", ...)` returns...
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value:load_dataset on a dataset name with no namespace raises HfUriError
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value:`load_dataset` on a dataset name with no namespace fails at HEAD and on 5.0.1: ```python >>> from datasets import load_dataset >>> load_dataset("imdb", split="train[:5]") ... File "src/datasets/load.py", line 609, in get_module standalone_yaml_path = cached_path( File "src/datasets/utils/file_utils.py", ...
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value:Send map workers only their shard's rows instead of the whole table
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value:Resolves #1992 ## Root cause `Dataset.map(num_proc>1)` shards the table with Arrow slices (`table.slice`), and Arrow slices share their parent buffers. When a shard is pickled for a worker, `InMemoryTable.__getstate__` serializes the sliced arrays' full buffers, so every worker receives the whole table. A 2-pro...
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value:Pickle nonimportable Enums so Dataset.map(num_proc>1) and hashing work
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value:Resolves #2643 ## Root cause `dill` serializes a class it cannot import by its module path through `_create_type`, which rebuilds the class from `type(name, bases, dict)`. That path cannot rebuild an `Enum`: the members, `_value2member_map_`, aliases, Flag boundary and slot descriptors are produced by `EnumMeta...
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value:Write pushed features to card when re-pushing a split
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value:Fixes #8608. `_get_updated_dataset_card` updates the splits and sizes of the existing `dataset_info` when a config is re-pushed, but never assigns the pushed `features` to it. Re-pushing a dataset's only split with different columns therefore leaves the card declaring the previous schema while the shards ho...
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value:`push_to_hub()` keeps stale `dataset_info.features` when re-pushing a single split with different columns
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value:### Describe the bug Re-pushing a dataset's only split with different columns updates the shards and the split sizes in the README, but silently keeps the **old** `dataset_info.features`. The card then declares a schema the parquet files no longer have, and the dataset viewer fails on the first batch with `CastE...
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value:docs: remove duplicate 'to' in push_to_hub instructions
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value:Tiny docs fix: remove duplicate `to` in the Dataset push_to_hub save instructions.
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value:Fix PandasArrayExtensionDtype comparison against strings
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value:## Summary Implement `construct_from_string` on `PandasArrayExtensionDtype`: parse `array[<dtype>]` into a `PandasArrayExtensionDtype`, and raise `TypeError` for anything else (how pandas spells "not my dtype" in `__eq__`). Provenance: pandas extension-dtype docs, and the reproduction on `main` in #8467 (pandas ...
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value:Restore `_legacy_no_dict_keys_sorting` so `_check_legacy_cache2` can find 2.15.0 caches.
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value:## Summary Restore the early return in `Pickler._batch_setitems` that honours `_legacy_no_dict_keys_sorting`, keeping the `*args` / `**kwargs` passthrough from `#7817`. `#7817` updated `Pickler._batch_setitems` for Python 3.14's extra argument and, in the same hunk, dropped that return. `_check_legacy_cache2` st...
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value:Recover from invalid list offsets produced by the pyarrow JSON reader
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value:Resolves #5531 ## Root cause The invalid Arrow data comes from pyarrow's JSON reader, not from `datasets`: when a list column's first non-empty value in a block starts with `null` (e.g. `{"a": [null, 1]}`), type inference can drop the leading null while the offsets still count it, so the table's list offsets sp...
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value:Add a Tensor feature for arrays with fixed or dynamic shapes
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value:Resolves #7738. Closes #887 (dynamic leading dimensions, e.g. `Tensor(shape=(None, 137, 2))`, with `to_pandas` and `map` covered by the tests). This adds a `Tensor(shape, dtype)` feature for multi-dimensional arrays whose dimensions can vary from row to row, following the direction discussed in the issue: fixed ...
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value:Key the doc build concurrency group on the pull request number
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value:## What does this PR do? `build_pr_documentation.yml` keys its concurrency group on `github.head_ref`, which is the head branch name without the fork owner. Two open PRs from different forks whose branches share a name therefore land in the same group, and a push on one cancels the in-flight doc build on the oth...
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value:Add append=True to push_to_hub for incremental dataset updates
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value:Resolves #6290. `push_to_hub` replaced every shard of a split on each call, so growing a dataset meant re-uploading all of it. This adds `append=True` to `Dataset.push_to_hub` and `DatasetDict.push_to_hub`, following the approach discussed in the issue: download the last Parquet shard of the target split, copy i...
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value:Decode BioSequence and BioStructure records with universal newlines
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value:`BioSequence.decode_example` and `BioStructure.decode_example` wrap the stored bytes in `StringIO` with its default newline handling, which only splits on `\n`. A record with bare-CR line endings therefore reaches Biopython as one line: FASTQ fails with "Unexpected end of file", FASTA decodes to an empty sequence...
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value:[httpx migration] Import httpx from huggingface_hub, require huggingface_hub>=1.31.0
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value:Direct httpx imports will break when huggingface_hub migrates to httpx2. This updates them to use the compatibility re-export introduced in https://github.com/huggingface/huggingface_hub/pull/4803, following the migration plan in https://github.com/huggingface/huggingface_hub/issues/4802. Goal is to make datasets...
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value:Fix decode(num_threads) busy-poll: bridge ThreadPool results to asyncio with callbacks
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value:Fixes #8595. `_apply_async` polled `future.ready()` in an `await asyncio.sleep(0)` loop. With the in-flight cap at `2 * num_threads`, that many hot loops keep the event loop thread holding the GIL, starving the ThreadPool threads it is waiting on — in stack dumps a pool worker took 45+ seconds to get through `ss...
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value:load_dataset silently accepts out-of-range ClassLabel indices when the source dtype already matches
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value:### 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 fr...
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value:IterableDataset.decode(num_threads) busy-polls its ThreadPool futures, starving the decode threads — 0 rows on remote audio; callback-based bridging restores the intended 20x
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value: ### Describe the bug `decode(num_threads=N)` (added in #7450, "speeds up streaming up to 20 times") schedules the sync `decode_example` calls onto a `multiprocessing.pool.ThreadPool` and bridges them into the async map machinery with a busy-poll (`iterable_dataset.py`): ```python async def _apply_async(pool, f...
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value:Forward max_buffer_input_shards from IterableDatasetDict.shuffle
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value:## What breaks `load_dataset(..., streaming=True)` without a split returns an `IterableDatasetDict`, and shuffling it cannot reach the shard-interleaving control: ```python ds = load_dataset("HuggingFaceFW/fineweb", streaming=True) ds = ds.shuffle(seed=42, buffer_size=10_000, max_buffer_input_shards=4) # TypeEr...
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value:Preserve dataset metadata when map recombines shards
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value:Fixes #5967. When `Dataset.map()` recombines multiple shards, it drops the source split. It also loses metadata such as `config_name` when the shards infer different compatible features (for example, a new column is null throughout the first shard and integer-valued in the second). Pass a copy of the source inf...
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value:fix(typing): Use Sequence instead of List for path_or_paths type annotations
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value:This fixes mypy errors when passing list of paths to `Dataset.from_parquet()`, `from_csv()`, `from_json()`, `from_text()`, and `IterableDataset` equivalents. **Problem**: `List` is invariant while `Sequence` is covariant, so passing a `List[str]` to a function expecting `Union[PathLike, List[PathLike]]` fails ty...
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value:Better error when a column written as null gets values in a later batch
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value:On #2831 the map still fails at HEAD, as `TypeError: Couldn't cast array of type double to null` now rather than `ArrowInvalid`. Your 2021 comment on that issue has the mechanism and both workarounds; the error itself says none of it. So this does not change what the writer accepts. Before the cast, `ArrowWriter...
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value:record_checksums default changed True -> False in 4.8.5, not in the release notes
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value:### 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/i...
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value:Advance the user-supplied generator in Dataset.shuffle even on cache hits
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value:Fixes #7127. When a `np.random.Generator` is passed to `Dataset.shuffle`, the indices cache lookup returns before `generator.permutation(...)` is called, so the caller's generator never advances on a cache hit. Because the fingerprint is derived from the generator's state, the next call recomputes the same fin...
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value:Let TranslationVariableLanguages encode without declared languages
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value:### What is wrong `TranslationVariableLanguages` declares `languages` as optional, but building one without it makes every example fail to encode. ```python >>> from datasets import Dataset, Features >>> from datasets.features.translation import TranslationVariableLanguages >>> TranslationVariableLanguages().en...
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value:Preserve formatting selections when flattening nested columns
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value:## What this changes I've fixed `flatten()` losing a selected struct's formatted columns. Its old name stays in the selection after flattening, so indexing can return an empty batch instead of the selected values. The fix flattens the selected features alongside the schema. It keeps unselected descendants exclu...
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value:Accept a single string for metadata_filenames in folder builders
value:2026-09-08T06:42:35Z
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value:### The bug `metadata_filenames` is only ever used as a membership test: ```python metadata_filenames = self.config.metadata_filenames or self.METADATA_FILENAMES ... elif os.path.basename(original_file) in metadata_filenames: ``` If it is a bare string rather than a list, `in` becomes a **substring** test: ``...
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value:Reject a non-callable generator in GeneratorConfig
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value:### The bug `GeneratorConfig` checks that `generator` is not `None`, but not that it is callable. A wrong type is only discovered during generation: ```python Dataset.from_generator([{"a": 1}]) ``` ``` DatasetGenerationError: An error occurred while generating the dataset caused by TypeError: 'list' object i...
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value:Fix the xml loader, which cannot load any file
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value:### The bug `load_dataset("xml", ...)` fails for **every** input: ```python open("a.xml", "w").write("<root><a>1</a></root>") load_dataset("xml", data_files="a.xml", split="train") ``` ``` DatasetGenerationError: An error occurred while generating the dataset caused by FileNotFoundError: [Errno 2] No such fi...
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value:Keep every value of nested columns in Dataset.to_csv()
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value:`to_csv()` hands the Arrow batch to pandas, and pandas renders a list cell with numpy's repr. So it comes out space separated, and past numpy's summarization threshold of 1000 the middle is elided: a 1500-element list is written as `[ 0 1 2 ... 1497 1498 1499]` and 1494 values are gone. Struct columns and...
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value:fix(benchmarks): rename misspelled read_unformated* helpers to read_unformatted*
value:2026-09-07T17:46:53Z
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value:`benchmarks/benchmark_array_xd.py` defines `read_unformated` / `read_batch_unformated` / `read_col_unformated` (all call sites internal to the file). Renamed to `read_unformatted` / `read_batch_unformatted` / `read_col_unformatted`.
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value:docs: drop duplicated 'a' in the HubBucketDatasetModuleFactory docstring
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value:`src/datasets/load.py`: "dataset loaded from data files of **a a** Storage Bucket" → "of a Storage Bucket". Docs-only.
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value:docs: point #map anchor links at the process guide
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value:`docs/source/about_map_batch.mdx` and `docs/source/stream.mdx` both link an in-page `#map` anchor, but neither file has a Map heading — the "Map" section lives in `docs/source/process.mdx` (`## Map`). Both links now target `/process#map` (doc-builder cross-file style).
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value:docs(builder): drop the stale verification_mode param from as_dataset's docstring
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value:`GeneratorBasedBuilder.as_dataset(self, split=None, in_memory=False)`'s docstring documents a `verification_mode` parameter (with an `<Added version="2.9.1"/>` tag). The parameter belongs to `download_and_prepare`, not `as_dataset`. The stale block is removed (the `download_and_prepare` docstring's own entry is u...
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