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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:include bound SQL values in the dataset cache key
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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:Fix save_to_disk sending the whole table to every worker for in-memory datasets
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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:Fix decoding a streamed PDF dataset twice after shuffle, take or filter
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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:Dataset.from_sql caches different SQLAlchemy queries under the same key when bound values change
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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:Honor table policies when exporting empty datasets to SQL
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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:Preserve unrestricted filters when extending data-file patterns
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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:Fix doubled words in load.py docstring and process docs
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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:Preserve grouped streaming batches when resuming checkpoints
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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:Honor batch_size when exporting an IterableDataset to Parquet
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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:Avoid copying WebDataset binary payloads during schema inference
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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:Unescape doubled quotes in GenBank qualifier values
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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:Raise on duplicate column names in Dataset.select_columns
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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:Preserve rows when concatenating pandas ArrayXD batches
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value:`PandasArrayExtensionArray._concat_same_type` can turn whole input batches into individual rows. For example, concatenating dense batches with 2 and 1 rows returns 2 rows instead of 3, with an extra batch dimension inside each row. A single input chunk is also wrapped as one row. Equally sized object-backed chunk...
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value:Fix forwarding custom User-Agent to fsspec HTTP requests
value:2026-10-20T14:17:24Z
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value:## Summary Related to #6046. Forward the configured DownloadConfig.user_agent to fsspec HTTP/HTTPS requests. - Reuse the existing get_datasets_user_agent() helper. - Preserve explicitly configured User-Agent headers. - Keep existing HTTP proxy handling unchanged. - Add regression tests for default and custom h...
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value:Fix concatenation cache fingerprints for different axes
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value: ## What does this PR do? Fixes #8859 Concatenating the same datasets using different axes can produce the same fingerprint. As a result, `map()` can reuse cached results from the wrong concatenation without warning. This change adds `axis` to the existing fingerprint calculation and adds two regression tests ...
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value:Keep threaded decoding reconfigurable after IterableDataset.shard
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value:Since #8791, `load_dataset(..., streaming=True)` decodes media datasets from the Hub in worker threads, and `IterableDataset.decode()` replaces that threaded step when it finds it as the last step of the dataset (`MappedExamplesIterable.decoding_pool`). `MappedExamplesIterable.shard_data_sources`, `shuffle_data_...
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value:IterableDataset.decode(False) has no effect after shard() on a streamed media dataset
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value:### Describe the bug Since #8791, `load_dataset(..., streaming=True)` decodes media datasets from the Hub in worker threads by default. `decode()` replaces that threaded decoding step when it is the last step of the dataset, but `shard()` loses track of it. After `ds.shard(...)`, `ds.decode(False)` keeps yieldin...
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value:Close owned event loops and pending work in streaming async maps
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value:When an async-mapped `IterableDataset` creates an event loop for iteration, it retains that loop without closing it. Repeated epochs therefore leak file descriptors. Early iterator closure also leaves pending callbacks without completing their asynchronous cleanup. Track loop ownership per iterator, settle that ...
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value:`Dataset.push_to_hub()` can upload path-only records for images or audio nested inside a struct, `List`, or `LargeList` when `decode=False`, even with `embed_external_files=True`. The resulting Parquet shards refer to files on the uploader's machine instead of containing their bytes. Use the existing recursive `...
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value:Fix HDF5 compound array field inference
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value:HDF5 compound records can contain numeric array fields, such as `np.dtype([("id", "int32"), ("values", "float32", (3,))])`. Loading this valid file currently raises `TypeError: 'NoneType' object is not iterable` during schema inference: the subarray dtype is mistaken for another compound record. Keep the field d...
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value:concatenate_datasets reuses preprocessing caches across different axes
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value:### Describe the bug Concatenating the same disk-backed datasets using different axes gives the same fingerprint, even though the resulting datasets are different. As a result, calling `map()` on one can reuse the cached results of the other without warning. In the example below, a dataset with two rows of pair...
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value:Fix inverted split slices reading the rest of the split
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value:A split slice whose end falls one row before its start returns the rest of the split instead of nothing: ```python import pathlib, tempfile from datasets import load_dataset path = pathlib.Path(tempfile.mkdtemp()) / "data.csv" path.write_text("x\n" + "\n".join(map(str, range(10))) + "\n") print(list(load_datase...
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value:Reject duplicate WebDataset fields instead of silently overwriting data
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value:A TAR archive can contain consecutive members with the same name, such as two `00000.txt` entries with different contents. The WebDataset pipeline currently overwrites the first value and returns only the second without reporting that data was lost. This change raises `ValueError` before overwriting an existing ...
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value:Preserve active iterators when reconfiguring threaded decoding
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value:Creating a new decoding view from a threaded `IterableDataset` currently shuts down the original dataset's decoding pool. If an existing iterator has prefetched examples queued behind active decoders, calling `ds.decode(False)` or changing its thread count cancels those examples. Continuing the original iterator ...
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value:Fix duplicated word in FileLock umask comment
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value:A one-word comment typo in `src/datasets/utils/_filelock.py`: the comment reads "In previous **previous** it was already using the current umask", duplicating a word and dropping the noun. ```diff # The "mode" argument is required if we want to use the current umask in filelock >= 3.10 - # In pre...
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value:Drop a leading UTF-8 BOM in the conll loader
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value:### What was wrong `load_dataset("conll", ...)` keeps a leading UTF-8 BOM. Because the BOM sits at the very start of the first line, it also defeats the two line-level checks (`skip_docstart` and `comment_prefix`), which compare the beginning of a line, so the first marker/comment line is turned into a data row:...
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value:### What was wrong `load_dataset("text", ...)` keeps a leading UTF-8 BOM as part of the data: ```python import codecs import os import tempfile from datasets import load_dataset path = os.path.join(tempfile.mkdtemp(), "corpus.txt") with open(path, "wb") as f: f.write(codecs.BOM_UTF8 + b"hello\nworld\n") ...
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value:Since #8791, streaming a media dataset from the Hub decodes it in worker threads by default, through the `map` step added by `IterableDataset.decode(num_threads=...)`. `cast` and `cast_column` only replaced `info.features` on top of that step, so they had no effect on decoding: * `cast_column("audio", Audio(samp...
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value:cast_column / cast are ignored on streaming datasets decoded in threads (audio sampling_rate, decode=False)
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value:### Describe the bug Since #8791, `load_dataset(..., streaming=True)` decodes media in worker threads by default when the dataset is on the Hub. The threaded decoding is a `map` step created by `IterableDataset.decode(num_threads=...)`, so the examples coming out of the dataset are already decoded. `IterableDat...
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value:Read string_to_dict fields by group name instead of position
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value:`string_to_dict` turns every `{field}` in the pattern into a named group `(?P<_field>.+)` and then reads the match with `result.groups()`, which is positional. Any other capture group in the pattern shifts the values, so `string_to_dict("train/alice", "(train|test)/{name}")` returns `{'name': 'train'}` instead of...
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value:`to_tf_dataset(num_workers=...)` can import a user's collator and initialize TensorFlow before `worker_loop` hides its GPUs. Hide GPUs in the spawn environment so initialization already uses the CPU, then restore the parent environment. Fixes #6948. Six new cases cover imported collators with eager TensorFlow ...
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value:Restores packaged inline type information. The `py.typed` marker is included in the wheel and source archive and explicit aliases mark the existing public re exports. Annotating the `Features` constructor's variadic arguments as `Any` also lets ordinary dictionary inputs type check. Fixes #7390. Checked an ins...
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value:Streaming `with_format("torch").map(...)` warns for every row when a transform returns tensors. Copy existing tensors directly while keeping dtype/device overrides, independent storage and leaf gradient settings. Fixes #7088. Added 18 regression cases, including batched maps. Formatting checks: 59 passed, 12 s...
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value:Warn once when resuming a shuffled dataset
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value:Repeated checkpoint restores can print the same shuffle-buffer warning thousands of times. This shows it once per process, including when several datasets are restored. Fixes #7444. Added four cases covering repeated restores and initial checkpoints, with checks on the returned rows. The iterable suite has 655 p...
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value:The Torchvision example now resizes masks with nearest neighbor interpolation so it doesn't create new class labels. I also removed the old output image, which shows the incorrect mask boundaries. Fixes #6865. Checked the updated example with upscaling and downscaling, for single examples and batches. Class la...
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value:When the first config in a README has no matching data files, the error now includes its name and the dataset path. This makes it easier to find the broken entry. Added tests for README and standalone YAML configs, Hub and bucket loaders and explicit file overrides. Fixes #6819. Tests: 302 local tests passe...
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value:Follow up to #8243. Strip the UTF-8 BOM at the start of each JSON input file. Multifile loads with inferred or explicit `List(Json())` columns otherwise fail when a later file has a BOM. Adds eight regression cases covering inferred/explicit features and regular/streaming loads, including multiple batches and ...
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value:Fix indices buffer loading in Dataset.from_buffer
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value:`Dataset.from_buffer` reads the data buffer twice when `indices_buffer` is provided. this raises a type error for string columns and can silently return the wrong rows for uint64 data. Read the supplied indices buffer instead, with 8 regression cases covering empty, reordered and repeated indices, plus the no ind...
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value:Create the table before the workers append in to_sql with num_proc
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value:`to_sql` with `num_proc > 1` hands every batch to the pool at once. The batch at offset 0 runs `DataFrame.to_sql` with `if_exists` as given (`"fail"` by default) and is meant to create the table; the later batches run with `if_exists="append"`, which also creates the table when it is missing. Whenever a later bat...
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value:to_sql with num_proc > 1 fails with 'table already exists' when a later batch reaches the database first
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value:### Describe the bug `Dataset.to_sql(name, con, num_proc=N)` with more than one batch fails with `table already exists` (sqlite: `(sqlite3.OperationalError) table t already exists`, or pandas' `ValueError: Table 't' already exists.`), and whether it fails depends on which worker reaches the database first. `Sql...
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value:Refuse an iterable of bools as a row index instead of reading it as indices 0 and 1
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value:`Dataset.__getitem__` reads a list, tuple, numpy array or pandas Series of booleans as row indices: `_query_table` turns the key into integers with `np.fromiter(key, np.int64)`, so a mask becomes the rows 0 and 1, and the result is silently wrong. ```python >>> ds = Dataset.from_dict({"a": [10, 20, 30, 40, 50]})...
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value:Indexing a Dataset with a list or array of bools silently returns rows 0 and 1
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value:### Describe the bug `Dataset.__getitem__` accepts a list, tuple, numpy array or pandas Series of booleans and reads it as integer row indices: every `True` becomes row 1 and every `False` row 0. No error is raised, and the result has the length of the mask, so it looks like a valid selection. The docstring says...
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value:Write the encoding passed to to_csv
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value:`Dataset.to_csv(path, encoding="utf-16")` wrote UTF-8. `CsvDatasetWriter._batch_csv` hands the batch to pandas with `path_or_buf=None`, so pandas returns a `str` and never applies `encoding`; the writer then encoded that `str` with a hard-coded `"utf-8"`. The docstring points at `pandas.DataFrame.to_csv` for the ...
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value:Number the index across batches in to_csv and to_sql
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value:`to_csv(index=True)` and `to_sql(index=True)` wrote an index column that restarts at 0 in every batch: `CsvDatasetWriter._batch_csv` and `SqlDatasetWriter._batch_sql` convert each batch with `batch.to_pandas()`, which gives the batch a fresh `RangeIndex` from 0, and pandas writes that. With the default `batch_siz...
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value:Cast dictionary-encoded storage such as pandas Categorical columns in ClassLabel
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value:`ClassLabel.cast_storage` handles `pa.StringArray` and `pa.IntegerArray` and hands anything else to `array_cast(storage, int64)`. A pandas `Categorical` column arrives as a `pa.DictionaryArray` (`dictionary<values=large_string, indices=int8>`), so Arrow tries to parse the category names as integers: ``` ArrowInv...
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value:to_csv ignores the encoding argument and always writes UTF-8
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value:### Describe the bug `Dataset.to_csv(path, encoding="utf-16")` writes UTF-8. The docstring says the extra keyword arguments go to `pandas.DataFrame.to_csv`, which documents `encoding` (and `errors`), and both are accepted without complaint, but the file is always UTF-8. The cause is in `datasets/io/csv.py`: `Cs...
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value:to_csv and to_sql with index=True restart the index at 0 in every batch
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value:### Describe the bug `Dataset.to_csv(..., index=True)` and `Dataset.to_sql(..., index=True)` write an index column whose values restart at 0 at every batch boundary. The docstrings of both methods say "If you would like to write the index, pass `index=True` and also set a name for the index column by passing `in...
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value:ClassLabel.cast_storage fails on a pandas Categorical column (dictionary-encoded Arrow storage)
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value:### Describe the bug `Dataset.from_pandas(df, features=...)` fails when the label column of the DataFrame is a pandas `Categorical` and the feature is a `ClassLabel`. pandas hands the column to Arrow as a `DictionaryArray` (`dictionary<values=large_string, indices=int8>`), and `ClassLabel.cast_storage` only know...
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value:docs: clarify checksum recording defaults
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value:Fixes #8590 Clarifies that checksum recording has been disabled by default since Datasets 4.8.5, and that `verification_mode="all_checks"` does not enable it. The integrity guide now explains when checksum comparison runs, shows how to pin a Hub dataset commit for reproducibility, and distinguishes that from ver...
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value:Fixes #5717 Supersedes [#8141](https://github.com/huggingface/datasets/pull/8141), which @kasperg3 [agreed to hand over](https://github.com/huggingface/datasets/pull/8141#issuecomment-6208799638). The first commit is kasperg3's, minus a `to_dict` line that [a later commit](https://github.com/huggingface/datasets...
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value:Related to #8793. `IterableDataset.iter(...).close()` can leave nested generators alive while the caller keeps the closed iterator. On Python 3.12 this leaves shuffled streaming sources and their files open until that iterator is deleted. Return an iterator that closes and releases its owned batch generator, so ...
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value:Speed up Dataset iteration ~7x for the default Python format
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value:`for row in ds` slices a one-row table and runs `format_table` on it for every row. With the default Python format that means `to_pydict()` on a 1-row table, `_unnest`, and `decode_example`, so most of the time goes to per-row overhead rather than conversion. Datasets with an indices mapping (after `shuffle` or `...
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value:bump fsspec and remove aiohttp dep
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value:Fix duplicated article in load.py docstring
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value:## What Fixed the duplicated article 'a a Storage Bucket' in a docstring in load.py. ## Why A small, objectively-verifiable improvement (typo) found during a daily open-source maintenance pass (2026-10-16). ## How verified Found with a grep for repeated words. Checked the diff: 1 line changed in 1 file. Committ...
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value:Accept path-like objects in `save_to_disk` / `load_from_disk` on older fsspec
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value:`Dataset.save_to_disk`, `Dataset.load_from_disk`, `DatasetDict.save_to_disk`, `DatasetDict.load_from_disk` and `datasets.load_from_disk` all document their path argument as `path-like`, but they pass it straight to `fsspec.core.url_to_fs`, which only started stringifying `os.PathLike` inputs in fsspec 2024.6. On ...
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value:Fix streaming raising FileNotFoundError for existing files when the Hub is briefly unavailable
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value:Fixes #7440 When the Hub is briefly unavailable (429, 5xx or a timeout), streaming can raise `FileNotFoundError` for a file that exists, and a long training run stops. ```python from unittest.mock import patch from huggingface_hub import HfFileSystem from huggingface_hub.errors import HfHubHTTPError f...
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value:Stop streaming take after the requested input boundary
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value:Fully exhausting `dataset.take(n)` currently asks the upstream iterable for one extra example (or Arrow table) before stopping. If that next read raises, a sample containing all requested rows still fails. The extra read can also run unnecessary mapping or I/O. Stop both iteration paths immediately after yieldin...
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value:Preserve column order and metadata when unpickling concatenated datasets
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value:Pickling a dataset concatenated along columns can undo `select_columns()` ordering and replace the full feature metadata with metadata from its first source. For example, two memory-mapped datasets concatenated as `a, b` and selected as `b, a` come back from a pickle roundtrip as `a, b`. Restore the saved schema...
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value:Synchronize feature decoding after in-place dictionary unions
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value:`Features |= other` inherits `dict.__ior__`, so it changes the schema without updating the cached decoding flags. Adding a column then raises `KeyError` during decoding. Replacing a `Value("string")` or `Json(decode=False)` column with `Json()` silently leaves JSON payloads encoded as strings. Apply the existing...
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value:Using `defaults | example` inside `Dataset.map()` should keep existing example values. For an unread overlapping column, the reverse union currently removes its deferred-formatting marker while retaining its `None` placeholder. Row mapping silently writes null values; batched mapping raises `TypeError`. Keep the...
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value:Skip empty streams when rebatching the entire dataset
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value:Mapping an empty Arrow or pandas stream with `batched=True` and `batch_size=None` (also `0` or a negative value) crashes with `ArrowInvalid: Must pass at least one table` after `take(0)`. If a filter instead emits empty tables, the same path invokes the callback with an empty batch. Positive-size batches already ...
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value:After a typed Arrow or pandas map, `select_columns()` removes columns from rows but retains the parent iterable's full feature schema. A subsequent `filter()` reintroduces those removed columns during formatting, then raises `CastError` because they no longer match the dataset's selected schema. Project `SelectC...
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value:Accept NumPy integer indices on nested columns
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value:Indexing a nested column with a NumPy integer, such as `dataset["metadata"]["score"][np.int64(0)]`, treats the returned row as an iterable and raises `TypeError`. Ordinary dataset columns already accept NumPy integer indices. Recognize NumPy integers in the nested-column scalar path as well. Regression tests cov...
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value:Honor new_fingerprint when casting non-decoder columns
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value:`Dataset.cast_column(..., new_fingerprint="cast-result")` ignores the supplied fingerprint for features without a decoder, including `Value`, `ClassLabel`, and `List`. The returned dataset and its saved `state.json` instead contain the fingerprint produced by the nested `cast()` call. Decoder-backed features alre...
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value:Arrow-formatted batched maps advance `with_indices=True` by the number of output rows when read through the Python row iterator. If a batch is duplicated, filtered, or dropped, later callbacks receive the wrong source indices. For example, concatenating a mapped Arrow stream with a generator-backed stream makes s...
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value:`Dataset.to_iterable_dataset()` keeps the rows and features but currently drops the split name and all other `DatasetInfo` fields. For example, a dataset with `split="train"`, a description and a license becomes a stream with `split=None` and empty description/license values. This loses attribution and provenance...
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value:Preserve headers and document structure when exporting empty datasets
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value:An empty `Dataset` currently writes zero bytes for both CSV and JSON exports. That drops the CSV header and makes `to_json(..., lines=False)` produce an invalid JSON document. This is reachable when filtering removes every record or a partition has no rows. Serialize one empty batch so CSV retains the requested ...
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value:Restore legacy unsorted dict hashing for the 2.15 cache lookup
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value:Fixes #8410 ### Problem `DatasetBuilder._check_legacy_cache2` patches `Pickler._legacy_no_dict_keys_sorting = True` to recompute the `config_id` that datasets 2.15 wrote, since 2.15 hashed dicts without sorting their keys. Since 4.4.0 the flag does nothing, so the lookup computes the current (sorted) hash and m...
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value:Fix CSV column_names overrides for configured datasets
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value:Fixes #7077. When loading a CSV dataset directory, `column_names` can be ignored and the first data row used as the header. It is also ignored when overriding column names from README configuration. Loading with the explicit `"csv"` builder already works. Normalize incoming `column_names` to `names` before the ...
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value:Always release open Parquet fragments on early stream stop (pyarrow >= 25)
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value:Fixes #8793 The workaround for apache/arrow#45214 in the Parquet builder (`del parquet_fragment` + `gc.collect()` when a stream stops before the fragment is fully read) was gated on `datasets.config.PYARROW_VERSION <= 24.0.0`. The issue reports that the fatal `PyGILState_Release` at interpreter exit still happen...
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value:Support remote streaming reads for TsFile
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value:Streaming a remote TsFile currently validates its header through `xopen`, then passes the URL string to `TsFileReader`, whose path-based constructor opens local files. Keep the fsspec seekable binary source alive and pass it to the file-object reader introduced in TsFile 2.5.0. Local files continue using the nati...
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value:Test TsFile 2.5.0 without dependency workarounds
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value:TsFile 2.5.0 is now available on PyPI and removes the PyArrow upper bounds that required installing the SDK with `--no-deps` only in the Python 3.14 job. Add `tsfile>=2.5.0` to the shared test requirements so the existing TsFile tests also run in the Python 3.10 jobs and the Python 3.14 NumPy 2 environment, and r...
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value:fix(splits): handle SplitInfo objects in SplitDict.from_split_dict
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value:Fixes #8617. Bug explanation: `SplitDict.copy()` crashes with `AttributeError` because `from_split_dict` calls `.get()` on the `SplitInfo` dataclass instances passed from `to_split_dict()`, which have no `.get()` method. What changed: one line in `src/datasets/splits.py` inside `from_split_dict`. Dict inputs be...
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value:docs: clarify download modes and transform caching
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value:2026-11-05T11:42:38Z
value:## Summary The cache guide currently recommends `force_redownload` to get data without previous `map` transforms. Reloading with `load_dataset` already returns the original prepared dataset. ```diff - Re-download files to get the original data without transforms. + Use download_mode for source downloads and dat...
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value:Keep the split in Dataset.repeat
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value:`Dataset.repeat(n)` returns `split=None` for any `n >= 1`, while `repeat(0)`, `select`, `shuffle` and `filter` keep the split: ```python ds = Dataset.from_dict({"x": [1, 2]}, split="train") ds.repeat(3).split # None ds.repeat(0).split # train ``` `repeat` concatenates `[self] * num_times` without passing the ...
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value:Fix misleading pickle or dill wording in fingerprint hashing
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value:Fingerprint hashing uses the custom dill pickler in `datasets.utils._dill`, but its failure warnings and caching documentation say objects can be serializable with "pickle or dill". This incorrectly suggests that successful pickle serialization is sufficient when dill serialization fails. This change makes the t...
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value:Keep the info and split when map recombines shards
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value:Fixes #5967. With `num_proc > 1`, `map` concatenates the processed shards via `_concatenate_map_style_datasets(all_transformed_shards)` without passing an info or split. The split is therefore always `None`, and `DatasetInfo.from_merge` drops `config_name`/`dataset_name` as soon as the shard infos differ, e.g. w...
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value:Fix concatenate_datasets giving every rank all the data after split_dataset_by_node
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value:Fixes #8799 If you split iterable datasets with `split_dataset_by_node` and then concatenate them, every rank gets all the data instead of its own part. The cause: `_concatenate_iterable_datasets` doesn't pass the split (`distributed=`) to the dataset it returns. This PR fixes it the same way `interleave_da...
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value:concatenate_datasets drops the split_dataset_by_node split, so every rank gets all the data
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value:### Describe the bug If you call `split_dataset_by_node` on iterable datasets and then concatenate them with `concatenate_datasets`, the result is no longer split: every rank iterates over the full data of all inputs. There is no error. In distributed training, each rank silently trains on the same data, so...
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value:Extract single-file archives atomically (temp file + os.replace)
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value:Fixes #5088 ## What does this PR do? The single-file extractors (`GzipExtractor`, `XzExtractor`, `ZstdExtractor`, `Bzip2Extractor`) streamed decompression **directly to the final cache path**, while `ExtractManager._do_extract` only checks for the file's existence to skip re-extraction. A process killed mid-ext...
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value:Add a regression test for extracting into a symlinked directory
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value:#8303 fixed #8296 (a symlink planted at the extraction directory made `Extractor.extract` write the archive into the directory it points to), but it shipped without a test. This adds one. The test plants a symlink to another directory at the output path, extracts a tar archive, and checks that the output path is...
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value:Support sorting by float16 columns
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value:`Dataset.sort` fails when a sort key is a `float16` column, or a struct with a `float16` field: ```python ds = Dataset.from_dict({"x": [0.5, -1.0, 2.0]}, features=Features({"x": Value("float16")})) ds.sort("x") # ArrowNotImplementedError: halffloat ``` Arrow has no sort kernel for half floats, on pyarrow 24 an...
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value:Fix push_to_hub dropping rows when num_proc exceeds num_shards
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value:`Dataset.push_to_hub` silently uploads only part of the dataset when `num_shards` is smaller than `num_proc`: ```python ds = Dataset.from_dict({"i": list(range(2000))}) ds.push_to_hub("user/repo", num_shards=2, num_proc=4) # uploads 1000 of the 2000 rows, no error ``` With `num_shards=3, num_proc=4` it uploads...
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value:Fix JSON loader turning plain strings into other types in inferred Json columns
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value:Fixes #8713. **Bug:** When `load_dataset("json")` infers a `Json` column (a column mixing objects and strings, with no explicit `features` passed), any plain string in that column that happens to be valid JSON (e.g. `"123"`, `"null"`, `"true"`) was decoded to another type on load: `123`, `None`, `True`. Only str...
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value:Fatal `PyGILState_Release` at interpreter exit when streaming Parquet with pyarrow 25 (arrow#45214 workaround is gated to pyarrow <= 24)
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value:### Describe the bug When streaming Parquet datasets from the Hub and stopping iteration early (normal for streaming), the process aborts during interpreter shutdown: ``` Fatal Python error: PyGILState_Release: thread state 0x7fca9c0036d0 must be current when releasing Python runtime state: finalizing (tstate=0...
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value:Skip complete Parquet sources using metadata counts
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value:Streaming `skip(n)` currently decodes every preceding Parquet source. This change uses `_generate_num_examples` to advance past complete sources using footer row counts, then keeps the existing scan/slice logic for the remainder. Addresses #5380, following [the maintainer’s suggested approach](https://github.c...
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value:Fast streaming decode for image/audio/video/etc. folders datasets
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value:enable multithreading by default only mesh datasets have a lower multithreading since they load the full files in memory, to avoid OOMs
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value:Fix Arrow fingerprinting capturing PyArrow globals
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value:## Summary Fix Arrow fingerprinting/serialization failing with `PicklingError: Can't pickle <class 'MonthDayNano'>` on the declared Python 3.11 / dill 0.4.1 / PyArrow 26.0.0 dependency combination. A two-row `Dataset.from_dict` fails during fingerprint creation, and the existing chunk-independent Arrow-table has...
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value:re-pushing all dataset partitions corrupts it
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value:### Describe the bug If I push a dataset to the Hub, rename a column, and push it again to the same repo, `load_dataset` fails with a `CastError`. The parquet file has the new column name, but the README metadata still lists the old one. It only happens when the dataset has a single split. With multiple splits,...
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value:fix: copy features to the card when re-pushing a split
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value:Fixes the bug reported in #8789 . `_get_updated_dataset_card()` updates the splits and sizes in the existing `dataset_info`, but never the features. So re-pushing every split of a dataset with different columns (e.g. after renaming a column) left the card declaring the old schema. `load_dataset` then fails wit...
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value:Fix streaming map callbacks returning None
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value:`IterableDataset.map()` documents that a callback returning `None` runs for side effects and leaves the input data unchanged. It currently raises `TypeError`: the Python path unpacks `None` as a mapping, and the table-formatted path rejects it as an invalid return type. ```python from datasets import IterableDat...
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value:Close the xopen handle in xpandas_read_csv
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value:`xpandas_read_csv` hands `xopen(path, "rb")` to `pd.read_csv`, and pandas never closes a buffer it did not open. The handle now closes after a full read, and when `iterator=True` or `chunksize` is set it closes with the reader, which pandas calls on exhaustion and on `close()`, and which #8779 adds for a generato...
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value:Raise a clear ValueError when interleave_datasets gets the wrong number of probabilities
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value:On main, `interleave_datasets([d, d], probabilities=[1.0])` with map-style datasets raises `IndexError: boolean index did not match indexed array along axis 0; size of axis is 2 but size of corresponding boolean axis is 1`. datasets 4.0.0 raised `ValueError: a and p must have same size` for the same call. Iterabl...
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value:CSV builder never closes the xopen file handle passed to pandas.read_csv (streaming and non-streaming)
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value:### Describe the bug The packaged `csv` builder leaves the file object of every CSV it reads open, even after a complete read. Only the garbage collector closes it. `xpandas_read_csv` (`src/datasets/utils/file_utils.py:1273`) passes `xopen(path, "rb")` to `pd.read_csv`. pandas wraps that buffer, and `IOHandles.c...
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value:Fix DatasetDict examples in the NumPy and JAX guides
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value:The `DatasetDict` examples in the NumPy and JAX guides call `DatasetDict.from_dict(data)`, but `DatasetDict` has no `from_dict` (only `Dataset` does), so the snippet fails: ``` AttributeError: type object 'DatasetDict' has no attribute 'from_dict' ``` This builds the `DatasetDict` from `Dataset.from_dict(...)` ...
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