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value:## Summary A local file with the same name as a WebDataset member can replace the embedded image. When an `Image` dictionary supplies both a relative archive label and bytes, the encoder can discard the bytes if the label happens to resolve to a file in the working directory. Keep the relative label and the sup...
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value:Fixes #8980. Adding a column to an Arrow-, pandas-, or Polars-formatted `IterableDataset` currently raises `TypeError` during iteration because the internal callback returns a dictionary. Perform this operation in batched Arrow format, append the new column without discarding the original columns, and restore th...
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value:### Describe the bug `IterableDataset.add_column()` fails during iteration after `with_format("arrow")`, `with_format("pandas")`, or `with_format("polars")`. Adding the column before selecting the format works. This prevents a streaming data preparation pipeline from adding metadata columns after it has selected...
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value:Combining iterable datasets can silently skip feature conversion or omit columns depending on the first source. For example, concatenating a source processed with `.map(..., features=features)` with a raw generator declaring the same `ClassLabel` produces integer labels from the first source and strings from the ...
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value:A fully loaded PIL image remains usable after its local source file is removed. `encode_pil_image` currently stores the retained filename, so `Dataset.from_dict` and a `Dataset.map` callback can produce a dataset that raises `FileNotFoundError` on access or `save_to_disk` despite having received usable image pixe...
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value:`IterableDataset.rename_column` / `rename_columns` crash during iteration when the dataset has a table format (`arrow`, `pandas`, `polars`). ```python from datasets import IterableDataset ds = IterableDataset.from_dict({"a": [1, 2, 3], "b": ["x", "y", "z"]}) list(ds.with_format("arrow").rename_column("a",...
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value:Fixes #8973 \get_parquet_column_options\ applied a single top-level \ equire_storage_embed\ result to every leaf under a struct field, disabling compression and dictionary encoding for non-media columns whenever a media feature was present. Compute the embed flag per leaf based on its own feature. This pull req...
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value:Fixes #8973 ### Context & Problem In #8674, Parquet writer options (`compression`, `use_dictionary`, `column_encoding`) were keyed by leaf path rather than top-level column names so nested struct/list fields would be compressed. However, `get_parquet_column_options` still checked `require_storage_embed` only a...
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value:### Describe the bug When a dataset contains a struct or dictionary column that includes an embedded storage feature (such as `Image`, `Audio`, `Video`, etc.) alongside non-media columns (such as text strings, integers, floats, or vectors), saving the dataset to Parquet via `to_parquet()` or `push_to_hub()` disa...
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value:The `eval` loader can't read Inspect logs whose sample ids are strings, which many tasks use (SWE-bench, GPQA, ...). Inspect names sample files `{sample_id}_epoch_{epoch}.json`, and `_sort_samples_key` calls `int()` on the id: ```python from datasets import load_dataset load_dataset("eval", data_files="swe_benc...
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value:Closes #3220. The Hub loading guide now shows where to find the Dataset Viewer’s **Auto-converted to Parquet** link and how to load one split from the conversion branch. The example uses the same CSV dataset already introduced in the guide and links to the Hub documentation for partial conversions and API access...
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value:Saving a dataset containing a null struct can try to read media paths hidden beneath that null. Arrow child arrays may retain values under a null parent; those values are not part of the logical dataset. If a hidden path does not exist, `save_to_disk` raises `FileNotFoundError` even though the corresponding datas...
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value:## Summary Fixes #8967 `Dataset.map(num_proc=...)` with a `suffix_template` whose rank field is not exactly `{rank:05d}` (for example `_{rank:03d}_of_{num_proc:03d}`) worked on the first run, then raised `ValueError: Unknown format code 'd' for object of type 'str'` on every rerun that loaded all shards from th...
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value:Fix map with num_proc failing on a cache hit when suffix_template has a custom rank format
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value:### Describe the bug `Dataset.map` with `num_proc` and a custom `suffix_template` works the first time, but every rerun that loads all shards from the cache raises `ValueError: Unknown format code 'd' for object of type 'str'`. Only the default `{rank:05d}` works. `Dataset.filter` has the same `suffix_template` ...
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value:## Summary Fixes #8965 `Dataset.batch(by_column=...)` and `IterableDataset.batch(by_column=...)` treated a null key as equal to its neighbours, so different groups were merged into one batch. Keys `[1, None, 2]` gave a single batch. A key column with only nulls raised `ArrowNotImplementedError`. Now a null is i...
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value:### Describe the bug `Dataset.batch(by_column=...)` and `IterableDataset.batch(by_column=...)` treat a null key as equal to its neighbours, so rows from different groups end up in the same batch. A key column that contains only nulls raises instead. ### Steps to reproduce the bug ```python from datasets import...
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value:## Description Fixes #8755 — Audio arrays remain NumPy arrays when using PyTorch formatting. ### Changes made - Updated the TorchCodec audio decoder to support returning PyTorch tensors. - Updated `TorchFormatter` to convert Hugging Face audio decoder output to PyTorch-compatible output. - Preserved existing Nu...
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value:I read through the repo and found a handful of small bugs. I reproduced each one before writing a fix. They're independent, so I can split this into separate PRs if that's easier to review. ### `http(s)://` data files fail on a clean install fsspec's `HTTPFileSystem` needs `aiohttp`, but `aiohttp` is only in th...
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value:Closes #8956 ### Summary - Prioritize 3D dataset detection when a repository contains mesh files alongside image textures. - Prevent image textures from causing a 3D dataset to be incorrectly detected as an `imagefolder`. - Preserve the existing format-selection behavior for other formats. ### Tests - `python -...
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value:`Dataset.add_item` infers an Arrow table before applying the existing dataset features. Appending a Python integer above `2**63 - 1` therefore raises `OverflowError` even when its column is declared as `Value("uint64")`. Retry the overflowing column with its existing scalar uint64 type. Other columns retain thei...
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value:It was using the default of `batch_size` which is `None`, which means full downloads By default it now uses max batch size (1000)
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value:CSV loading with an explicit `Value("timestamp[ns]")` feature fails in the default pandas C parser: the feature's NumPy datetime dtype is unsupported by `read_csv(dtype=...)`. Read timestamp columns as objects and let the existing Arrow schema conversion parse them. This preserves the declared timestamp type, na...
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value:`Mesh` (and the `meshfolder` builder behind it) only accepts `.glb`, `.ply` and `.stl`, although `trimesh` — which does the decoding — also reads glTF. So a folder of `.gltf` models produces no `Mesh` column at all, and `Mesh().decode_example({"path": "model.gltf", ...})` raises. Measured on `main` (62e0b421), b...
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value:cc @3outeille lmk if it sounds good to you if `split_dataset_by_node` sounds confusing in this setting we can also imagine a different function dedicated to meshes
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value:[cfahlgren1/3d-model-samples](https://huggingface.co/datasets/cfahlgren1/3d-model-samples/tree/main) has 6 `.glb` files and one `.gltf` model, but the viewer shows it as an `Image` dataset with 15 rows of FlightHelmet textures and no 3D models. The format comes from the most common file extension, and a `.gltf` ...
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value:`ds.with_format("arrow")[range(n)]` can use an Arrow slice, but first `_check_valid_index_key` walks the entire range twice to compute its minimum and maximum. A range is monotonic, so its first and last elements give the same bounds for either step direction. Check the larger endpoint first as before, preserving...
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value:`ConcatenationTable.slice(0, 0)` returns the expected empty table, but a pickle round trip raises `ArrowInvalid: Must pass at least one table`. Empty slices retain no row blocks. Rebuild those results directly from the saved schema, preserving column types, nullability and metadata. Nonempty block reconstruction...
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value:`IterableDataset.load_state_dict()` only stores the state; it is applied when the next iteration starts. Until the first example is read, `state_dict()` keeps returning the dataset's previous state (for a dataset created after a restart, the start of the stream). A checkpoint saved in that window loses the restor...
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value:Fixes #8919. With `num_proc > 1`, `Dataset.map` splits the dataset into equal contiguous shards with `shard(contiguous=True)`, ignoring `batch_size`. Every shard then ends with its own incomplete batch: - a batched function receives short batches in the middle of the dataset, not only at the end; - `Dataset.bat...
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value:After `set_format(type=..., columns=[...])` or `with_transform(..., columns=[...])`, reading a column that is not in the format columns raises `KeyError`: ```python from datasets import Dataset ds = Dataset.from_dict({"input_ids": [[1, 2], [3, 4]], "label": [0, 1], "text": ["a b", "c d"]}) ds.set_format(type="n...
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value:What does this PR do? pyarrow's JSON reader can return a table with invalid list offsets when a list starts with `null`. The `.jsonl` branch of `_read_metadata` in folder-based builders (`imagefolder` and the others) used that table without checking it, so values were silently wrong: `[null, 1]` and `[2]` loaded...
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value:### Describe the bug When the `metadata.jsonl` of an `imagefolder` has a list column whose first element is `null`, `load_dataset` returns wrong values with no error. In the example below, `[null, 1]` and `[2]` come back as `[1, 2]` and `[0]`. The same rows loaded with the `json` builder come back correctly on ...
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value:`Image().encode_example` fails on single-channel arrays shaped `(H, W, 1)`, which is how many image pipelines (OpenCV, torchvision, `np.expand_dims`) hand over grayscale images: ```python import numpy as np from datasets import Dataset, Features, Image array = np.zeros((4, 4, 1), dtype=np.uint8) Dataset.from_di...
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value:CSV readers can reject missing values in declared integer or boolean columns before applying their nullable Arrow schema. With the Python parser, a value such as `"001"` in a declared string column can become `"1"`, losing its leading zeros even though the resulting feature type remains `string`. Map declared ...
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value:`map()` and `filter()` recognize async functions but classify objects with an async `__call__` as synchronous callbacks. A callable mapper then receives a coroutine instead of a mapping; a callable predicate can silently keep every row without being awaited. Use a shared callback classifier for `Dataset` and `It...
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value:Related to #7537. `dill` versions before 0.3.6 can't handle code objects on Python 3.11+, so `Dataset.map(num_proc=...)` crashes. `setup.py` still allows `dill>=0.3.0` on every Python version, so an environment that keeps an older `dill` installs `datasets` without complaint and fails at runtime. #7537 shows the...
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value:Passing a current-directory filename such as `indices_cache_file_name="selected.arrow"` raises `FileNotFoundError` for a noncontiguous selection: the indices writer calls `os.makedirs("")`. The same path is used by `sort`, `shuffle`, and `train_test_split`. Use the current directory when the filename has no pa...
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value:## Summary `_type` is a supported feature column name, but serializing it to dataset card metadata raises `TypeError: expected string or bytes-like object, got 'dict'`. The YAML serializer unconditionally removes `_type`, then treats its feature dictionary as a dataclass type name. ```python from datasets impor...
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value:With the `arrow` or `polars` format, a non-batched `Dataset.filter` crashes before it calls the function even once: ```python import pyarrow.compute as pc from datasets import Dataset ds = Dataset.from_dict({"a": list(range(10))}) ds.with_format("polars").filter(lambda df: df["a"] > 5) # AttributeError: 'DataF...
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value:Fixes #8926. When a field has mixed types, the JSON loader stores it as `Json()`. Before encoding a value, `json_encode_field` tries `ujson_loads` on it and keeps it unchanged if that succeeds, assuming it is already JSON-encoded. So a string that happens to be valid JSON text is stored without its quotes and co...
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value:## Preserve nested fields when combining streaming datasets Combining generator-backed streams with different finite struct fields silently drops fields present only in later sources. Arrow-backed streams fail to cast the same inputs, while map-style concatenation already preserves their union. Recursively comb...
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value:### Describe the bug When a field has mixed types, the JSON loader stores it as `Json()` (the default `on_mixed_types="use_json"` from #8027). Any string value in that field that is itself valid JSON text is then stored without its quotes, so it comes back as a different value and type: `"123"` becomes `123`, `"...
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value:JSON loader turns string values into numbers, booleans or null when a field has mixed types
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value:`cast_column` with a column name that is not in the dataset adds a new column filled with `None` instead of raising, in two places: ```python from datasets import Dataset, Image, Value ds = Dataset.from_dict({"a": [1, 2]}) ds.cast_column("b", Image())[0] # {'a': 1, 'b': None} ids = ds.to_iterable_dataset() lis...
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value:Raise in cast_column when the column is not in the dataset
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value:## Summary Source inspection found that `Pdf.decode_example()` opens remote streams itself but passes them to `pdfplumber.open()` as externally owned file-like objects. Consequently, closing the returned PDF (including leaving its context manager) does not close the decoder's stream, and constructor failures als...
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value:Close decoder-owned streams when decoding remote PDFs
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value:### Fix double nesting of list subfeatures in `Sequence(dict)` In the TFDS-compat conversion, `Sequence(feature={...})` turns a dict of subfeatures into a dict of lists. Since #7672, subfeatures that are already list features are not converted anymore **when all of them are lists** — but the mixed case was still...
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value:## Summary `ClassLabel.int2str` accepts `Iterable` inputs, but currently iterates over them once to validate the labels and again to convert them. A one-shot iterator or generator is exhausted by validation, so valid input silently returns an empty list: ```python label = ClassLabel(names=["negative", "pos...
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value:Fix ClassLabel.int2str for one-shot iterables
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value:Five links in the docs returned 404. Updated to pages that exist (each new URL returns 200): - `webdataset.github.io/webdataset` (audio, image, video dataset guides) → `github.com/webdataset/webdataset`: the docs site is gone and the project moved from `tmbdev` to the `webdataset` org. - `use_with_spark`: Spark ...
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value:Fix dead links to WebDataset, Spark and Albumentations docs
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value:`ConcatenationTable.select([1])` returns the expected table immediately, but discards the selected columns from its stored blocks. Serializing the result then silently loses its rows, including after slicing or filtering. Resolve the validated selection to column names before selecting the stored blocks. This pr...
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value:Preserve concatenated table rows when pickling integer column selections
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value:### Describe the bug With `num_proc > 1`, batched `Dataset.map` (and `Dataset.batch`, which goes through it) splits the dataset into `num_proc` equal row chunks via `self.shard(num_shards, index=rank, contiguous=True)`, ignoring `batch_size`. Each chunk ends with its own short batch, so the function sees wrongly...
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value:Batched map / Dataset.batch with num_proc>1 splits batches at shard boundaries and drop_last_batch loses rows
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value:`Dataset.map` reuses cache files written with a different `num_proc` (#7434) by globbing `f"{cache_file_prefix}*{cache_file_ext}"` and parsing each match with `string_to_dict(path, prefix + suffix_template + ext)`. The prefix is a full filesystem path used unescaped as both a glob and a regex, so special characte...
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value:Fix map cache reuse across num_proc when the cache path has glob/regex special characters
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value:Casting a nullable `LargeList` of an ArrayXD feature to a fixed-length `List` crashes, while the same cast from a regular `List` works: ```python from datasets import Dataset, Features, Array2D, List, LargeList ds = Dataset.from_dict( {"x": [[[[1, 2]], [[3, 4]]], None]}, features=Features({"x": LargeLis...
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value:Setting `set_default=True` during a push can either raise `KeyError('default')` or restore stale `data_files` in the dataset card. The card writer treats a sole configuration as the default even when it has no explicit `default` flag, then unconditionally pops that missing flag. If the selected configuration is ...
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value:Fixes #8914 ## What this fixes `Json.cast_storage` parsed only `storage[:5]` to decide whether a string column already contains JSON. When those five values parsed but a later one did not, the whole column was left untouched: the later value was stored as raw text instead of being encoded as a JSON string, and ...
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value:### Describe the bug Casting a string column to `Json()` uses a 5-row sample to decide whether the column already holds JSON. If the first five values parse as JSON but a later value does not, the later value is stored **unencoded**. It then reads back through `decode_example` as a syntax error instead of as a s...
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value:Saving an empty typed Dataset with default sharding caps the automatically chosen shard count at zero. The save completes, but `load_from_disk()` cannot reconstruct a table from the empty file list. Keep at least one automatically chosen shard. Add regression coverage for default settings, `num_proc=2` and `max_...
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value:### Describe the bug Datasets 5.1.0 writes zero shards when saving an empty typed Dataset with default sharding. The saved state has `_data_files: []`; `load_from_disk()` raises `IndexError: list index out of range` in `ConcatenationTable.from_tables`. This reproduces without Redis, ADBC, network access or downl...
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value:Empty typed Dataset default save cannot reload because it writes zero shards
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value:Link a concrete Redis SQL-to-Arrow-to-Dataset workflow from the PyArrow interoperability guide. Explain the external driver/Search prerequisite, local conversion/persistence scope and one-shard empty-result save setting. No built-in loader or dependency is added. Validation: the exact linked guide example passed...
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value:docs: link Redis ADBC Dataset integration guide
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value:Fixes #8909 The "Example: data extraction" code block in use_with_polars.mdx used `re` and `pl` without importing them, so it failed with a NameError when run on its own. This adds `import re` and `import polars as pl` at the top of the block.
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value:### Describe the bug The "Example: data extraction" code block on https://huggingface.co/docs/datasets/en/use_with_polars uses `re` without importing it: pattern = re.compile("boxed\\{(.*)\\}") Running the block as shown fails with `NameError: name 're' is not defined`. ### Steps to reproduce the bug Cop...
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value:Fixes #8907 Follow-up to #8786, which fixed this for `xpandas_read_csv`. The remaining streaming readers still handed `xopen(...)` to the reader without closing it: - `xpyarrow_parquet_read_table`, `xsio_loadmat`: wrap in `with xopen(...)`. - `xpandas_read_excel`: both the direct read and the BytesIO fallback n...
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value:### Describe the bug #8786 fixed the leaked `xopen` handle in `xpandas_read_csv`, but the other streaming readers in `utils/file_utils.py` still pass `xopen(...)` straight to the reader and never close it: - `xnumpy_load` - `xpandas_read_excel` (both the first try and the BytesIO fallback) - `xpyarrow_parquet_r...
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value:Bumps doc-builder to the latest `main` so the docs on hf.co/docs get [machine-translated](https://github.com/huggingface/doc-builder#machine-translated-documentation) into 11 languages, as discussed on Slack. Pages built by older doc-builder versions can't be translated. 🤖 Generated with [Claude Code](https://c...
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value:Dataset.flatten_indices() currently passes the dataset’s active format to an identity map. With a custom transform, the transform’s output is written to Arrow, while the result retains the same transform and applies it again on access. For example, for stored values [2, 0] and an on-the-fly transform that adds 1...
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value:Title: Load Harbor multi-step tasks without a top-level instruction.md A multi-step Harbor task declares `[[steps]]` in its `task.toml` and keeps its instructions in `steps/<step>/instruction.md`, so it doesn't need an `instruction.md` next to its `task.toml`. Harbor handles that case in several places: - `Task...
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value:# Allow reading prepared datasets from read-only shared caches Addresses the Datasets lock-file failure reported in huggingface/datasets#7900. Hub cache permissions are outside this patch. ## Problem `DatasetBuilder` acquires exclusive file locks while checking cached metadata and while deciding whether a data...
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value:`DatasetDict.class_encode_column` encoded each split on its own, so a split that lacks some classes got a shorter `ClassLabel`, and the same label got a different integer id than in the other splits. Using the train features to decode the ids of another split then returned the wrong class, and concatenating the s...
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value:`Dataset.map(num_proc=2)` currently leaks its temporary `TOKENIZERS_PARALLELISM=false` override into the parent process. On a cold map, Python's copied `os.environ` reports the old value while a newly launched subprocess still inherits `false`. Fully cached maps and pool-constructor errors leave the Python mappin...
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value:Fixes #8898 ## Bug When loading JSONL with the default `on_mixed_types="use_json"`, a record with a literal key such as `"a/b"` is misinterpreted: the PyArrow error column name is split into the nested path `["a", "b"]`, even though the record has one literal key `"a/b"`. Re-encoding with that nested path leaves...
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value:### Describe the bug On main `ef61228a5756dcebfff8ee245d89c72822fb6ae6` (`datasets` 5.2.0.dev0), loading a two-row JSONL file with a literal `a/b` field mixing a number and a string does not finish with the default `on_mixed_types="use_json"`. The same values under a plain field name load as `Json()`. A slash-c...
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value:Replacing a local `.tar.gz` archive at the same path can return old rows from `load_dataset("json", ...)`, even after the builder detects the changed source and creates a new dataset fingerprint. The extraction cache currently identifies the archive by pathname alone. This change includes the absolute path, file...
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value:`cast()` and `cast_column()` fail on any dataset that has a FAISS or Elasticsearch index attached: ```python import numpy as np from datasets import Dataset, Value ds = Dataset.from_dict({"id": list(range(5)), "v": np.eye(5, dtype=np.float32).tolist()}) ds.add_faiss_index("v") ds.cast_column("id", Value("int32"...
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value:Adds `AtomicStructure` alongside `BioStructure` and `BioSequence`, preserving source files and loading atoms lazily with AtomWorks. PDB/mmCIF folder loaders use the new feature; existing serialized legacy feature names and sequence-loader schemas remain supported. ### Behavior - Paths and bytes are stored uncha...
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value:## What `require_decoding(feature, ignore_decode_attribute=...)` drops `ignore_decode_attribute` when it recurses: the `dict`, `list`/`tuple`, `LargeList` and `List` branches call `require_decoding(f)` without forwarding the flag. Only a top-level feature honours it. `ignore_decode_attribute=True` is passed by ...
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value:an int64 column with a null was converted to float64. float64 cannot hold every int64, so `2**62 + 1` came back as a different number. `to_pandas` and the pandas formatter now keep those nulls as missing values, the same way `to_csv` / `to_json` / `to_sql` already do. a column with no nulls stays int64. checked ...
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value:Fixes #8888 `PandasArrayExtensionDtype.__from_arrow__` materialized every fixed-shape ArrayXD column through `ArrayExtensionArray.to_numpy`, which pads the null rows with NaN and promotes the whole column to float64. Two consequences at the pandas boundary: the Arrow row validity was gone (a null row and a legit...
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value:### Describe the bug `Dataset.from_pandas(ds.to_pandas())` loses missing rows in a fixed-shape ArrayXD column. A null row becomes a valid all-NaN array. A legitimate all-NaN array must remain distinct from that missing row. ### Steps to reproduce the bug Reproduced on main `ef61228a5756dcebfff8ee245d89c72822fb...
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value:After concatenating a streaming dataset selected with `take(4)`, `set_epoch(1)` can change its rows from `[0, 1, 2, 3]` to `[0, 3, 6, 9]`. The same problem affects `skip()` and explicit shuffling after concatenation. Propagate shuffling through vertical concatenation's shard wrappers so the existing skip/take or...
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value: ## What does this PR do? Fixes #8877 `Dataset.from_sql()` can silently return incorrect cached rows when two SQLAlchemy queries differ only in their bound parameter values. The existing cache identity includes the compiled SQL placeholders but not their values, causing queries with different `WHERE`, `LIMIT/OF...
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value:Fixes #8743. Use `pyarrow.parquet.ParquetWriter` as a context manager so query, batch-write, and metadata failures finalize the writer before the enclosing path-owned file handle closes. Caller-provided binary streams remain open, and the successful byte-count result is unchanged. This is an alternative to #874...
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value:Running the test suite without the optional `pyspark` dependency aborts collection instead of skipping the spark tests: ``` ERROR tests/packaged_modules/test_spark.py ModuleNotFoundError: No module named 'pyspark' ``` `tests/packaged_modules/test_spark.py` imports `pyspark` at module level, so collection fails ...
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value:Dataset cards with two entries using the same `config_name` silently keep only the last entry when `MetadataConfigs.from_dataset_card_data` builds its dictionary. For example, two `custom` entries pointing at different CSV files cause `load_dataset(..., name="custom")` to load only the second file without warning...
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value:fixes #8877 `str(sql.compile())` drops the bound values, so two queries that differ only by a WHERE, LIMIT, or IN parameter reused one cache entry. the key now inlines those binds. @lhoestq
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value:Fixes #7290 `save_to_disk(num_proc=...)` on an in-memory dataset sends the whole table to every worker, once per shard, instead of just that shard's rows. So it is much slower and uses much more memory than it should. ```python import pickle from datasets import Dataset ds = Dataset.from_dict({"text": ["some t...
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value:Addresses **CVE-2026-57845**, arbitrary code execution through pickle deserialization in the pandas dataset builder. Replaces `Pandas._generate_tables()` with an unconditional migration error before file opening or unpickling. Builder construction and compatible prepared Arrow cache reuse remain supported. File ...
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value:Since #8791 (not in a release yet), a streamed PDF folder from the Hub is decoded in threads by default. Calling `.decode()` again after another step, such as `.shuffle()`, `.take()` or `.filter()`, decodes each example a second time, and `Pdf.decode_example` fails on the already decoded `pdfplumber` PDF: ```pyt...
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value:### Describe the bug When `Dataset.from_sql()` receives a SQLAlchemy `Selectable`, queries with different parameter values can use the same cache key. If the first query is cached, the next query can return its rows instead of the correct results, without warning. This affects `WHERE` conditions, `LIMIT`, and ex...
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value:Fixes #6133 When iterating an `IterableDataset` example by example, rows go through `RebatchedArrowExamplesIterable` with `batch_size=1`, so each row ends up as a 1-row Arrow table that gets cast and formatted on its own. That per-row overhead is why `for ex in ds` is slow, including after `to_iterable_dataset()...
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value:Exporting an empty dataset skips the SQL writer entirely. As a result, `if_exists="replace"` returns zero while leaving old rows in the table, `if_exists="fail"` accepts an existing table, and exporting a new empty split leaves its table missing. Write one empty batch through the existing pandas conversion so th...
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value:## Summary Preserve unrestricted extension filters when calling `DataFilesPatternsList.filter_extensions`. `DataFilesPatternsList.from_patterns(["*"])` stores `allowed_extensions=[None]`, where `None` means unrestricted. Calling `.filter_extensions([".json"])` on unchanged main attempts `None + [".json"]` and r...
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value:## What Removed a duplicated 'a' in a load.py docstring ('of a a Storage Bucket') and a duplicated 'to' in docs/source/process.mdx ('save it to to push_to_hub'). ## Why A small, objectively-verifiable improvement (typo) found during a daily open-source maintenance pass (2026-10-22). ## How verified Found both w...
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value:`IterableDataset.batch(by_column=...)` can silently drop a complete group after an ordinary checkpoint restore. For example, group IDs 0–8 into triples, consume the first two groups, then save and reload state: uninterrupted iteration returns `[6, 7, 8]`, while current main returns nothing. The grouping callback...
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value:Preserve grouped streaming batches when resuming checkpoints
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value:`IterableDataset.to_parquet(..., batch_size=2)` currently ignores the requested batch size: exporting seven rows creates a single seven-row Parquet row group, while `Dataset.to_parquet` creates row groups of `[2, 2, 2, 1]`. This prevents callers from controlling the row groups used when exporting streaming traini...
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value:Honor batch_size when exporting an IterableDataset to Parquet
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value:WebDataset schema inference currently builds Arrow tables containing the complete binary payloads from its first examples. A single value above Arrow's binary offset limit raises `ArrowCapacityError`, even with `streaming=True`. Use empty byte strings only in the temporary examples passed to schema inference. Th...
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value:Avoid copying WebDataset binary payloads during schema inference
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value:The GenBank loader keeps the `""` escape inside quoted qualifier values. A wrapped line that ends in an escaped `""` also closes the value early, and a stray `"` lands at the end. The INSDC feature table (section 3.3.3.1) escapes each quotation mark in free text by doubling it. Its own example is `/note="This is ...
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value:Unescape doubled quotes in GenBank qualifier values
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value:`Dataset.select_columns` accepts a list with repeated names and returns a dataset that looks fine but breaks on first use: ```python from datasets import Dataset ds = Dataset.from_dict({"a": [1, 2], "b": [3, 4]}) sel = ds.select_columns(["a", "a"]) print(sel.column_names, len(sel.features)) # ['a', 'a'] 1 sel[...
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value:Raise on duplicate column names in Dataset.select_columns
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