music datasets
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Datasets:
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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type 'quality_breakdown' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 642, in write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 457, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'quality_breakdown' with no child field to Parquet. Consider adding a dummy child field.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1847, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 661, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 457, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'quality_breakdown' with no child field to Parquet. Consider adding a dummy child field.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1456, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1858, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
id string | path string | folder_name string | parent_folder_name string | files list | album_art_hash null | other_files list | file_hashes_present bool | avg_bitrate float64 | unique_artists list | unique_albums list | generic_filename_score float64 | generic_title_score float64 | hebrew_metadata_ratio float64 | metadata_completeness_ratio float64 | lossless_ratio float64 | lyrics_ratio float64 | quality_score null | quality_breakdown dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
D:\ืืขืื ืชืฉืืื\ืืืื ืื ืื\ืืืค ืืืคื | D:\ืืขืื ืชืฉืืื\ืืืื ืื ืื\ืืืค ืืืคื | ืืืค ืืืคื | ืืืื ืื ืื | [
{
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... | null | [] | true | 192 | [
"ืืืื ืื ืื"
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{
"filename": "ืกืื ืกืื [High quality].mp3",
"filepath": "D:\\ืืขืื ืชืฉืืื\\ืืืืืืฃ\\ืกืื ืกืื [High quality].mp3",
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"title": ... | null | [
{
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"hash": "fbb42629e41fd3f5f4c8fdd6b3a916a0e8307bc97f48de1e1fb3fc6a95f98346"
}
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D:\ืืขืื ืชืฉืืื\ืืืจืื ืืืืืืื\ืืืช ืืงืืืฉื | D:\ืืขืื ืชืฉืืื\ืืืจืื ืืืืืืื\ืืืช ืืงืืืฉื | ืืืช ืืงืืืฉื | ืืืจืื ืืืืืืื | [
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"bitra... | null | [] | true | 128 | [
"ืืืจืื ืืืืืืื"
] | [
"ืืืช ืืงืืืฉื"
] | 0.287375 | 0.287375 | 1 | 1 | 0 | 0 | null | {} |
D:\ืืขืื ืชืฉืืื\ืืืื ืืจ ืืื | D:\ืืขืื ืชืฉืืื\ืืืื ืืจ ืืื | ืืืื ืืจ ืืื | ืืขืื ืชืฉืืื | [
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"bi... | null | [] | true | 192 | [
"ืจืืขืืฉืืข"
] | [
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] | 0.699387 | 0.279468 | 1 | 1 | 0 | 0 | null | {} |
D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืืจื ืจืืื - ืืื ืืืืืื | D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืืจื ืจืืื - ืืื ืืืืืื | ืืืจื ืจืืื - ืืื ืืืืืื | ืืืจืื ืจืืื | [
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"bitrate": 160... | null | [] | true | 160 | [
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] | [
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] | 0.272386 | 0 | 1 | 0 | 0 | 0 | null | {} |
D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืืจื ืจืืื - ืงืืขืชื ืืช ืืืฉืื\ืืืจื ืจืืื - ืงืืขืชื ืืช ืืืฉืื | D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืืจื ืจืืื - ืงืืขืชื ืืช ืืืฉืื\ืืืจื ืจืืื - ืงืืขืชื ืืช ืืืฉืื | ืืืจื ืจืืื - ืงืืขืชื ืืช ืืืฉืื | ืืืจื ืจืืื - ืงืืขืชื ืืช ืืืฉืื | [
{
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{
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"title": "ืืื ืจื... | null | [] | true | 251.428571 | [
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] | [
"New Title (135)"
] | 0.276174 | 0.232262 | 0.642857 | 0.357143 | 0 | 0 | null | {} |
D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืืืืช ืืืืืจ | D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืืืืช ืืืืืจ | ืืืืืช ืืืืืจ | ืืืจืื ืจืืื | [
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"title":... | null | [
{
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] | true | 320 | [
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] | [
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] | 0.264384 | 0.264384 | 1 | 1 | 0 | 0 | null | {} |
D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืกื ื ืืืขืจ | D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืกื ื ืืืขืจ | ืกื ื ืืืขืจ | ืืืจืื ืจืืื | [
{
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"duration": 280.0145,
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"title... | null | [] | true | 128 | [
"ืืืจื ืจืืื"
] | [
"ืกื ื ืืืขืจ"
] | 0.166956 | 0.31593 | 1 | 1 | 0 | 0 | null | {} |
D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืื ืจืืื | D:\ืืขืื ืชืฉืืื\ืืืจืื ืจืืื\ืืื ืจืืื | ืืื ืจืืื | ืืืจืื ืจืืื | [
{
"filename": "ืื ืืฉืืื ืืื 04.MP3",
"filepath": "D:\\ืืขืื ืชืฉืืื\\ืืืจืื ืจืืื\\ืืื ืจืืื\\ืื ืืฉืืื ืืื 04.MP3",
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"duration": 262.35575,
"bitrate": 128,
"ti... | null | [] | true | 128 | [
"ืืืจื ืจืืื"
] | [
"ืืื ืจืืื"
] | 0.326214 | 0.319319 | 1 | 0.5 | 0 | 0 | null | {} |
End of preview.
Real Music Albums FS
Real Music Albums FS is a structured dataset representing metadata extracted from real-world music album directories in Hebrew. The dataset was created by scanning existing folder structures from personal or archival music collections, typically stored on hard drives or local systems.
The data is organized by artist and album, and contains information on individual audio files including file names, sizes, formats, and file hashes.
Dataset Summary
- Language: Hebrew
- Domain: Music, Audio File Metadata
- Structure: JSON Lines format
- Data Types: Structured metadata (not audio files)
- Content: Real folder names, album names, file listings, file extensions, sizes, hashes
This dataset is useful for tasks such as:
- Analyzing real-world music archive structures
- Mapping artist and album relationships
- Building music file management tools
- Training machine learning models for audio file classification or file organization
- Creating tools for file deduplication and music metadata extraction
Features
Each record includes:
- A unique identifier (
id) - Full path to the album folder
- Album name and artist name (inferred from directory structure)
- List of file metadata per track (file name, extension, size in MB, hash)
The dataset does not include the actual music files โ only metadata extracted from them.
Intended Use
This dataset was created for developers, data scientists, and researchers interested in:
- Digital music archiving
- File organization using metadata
- Music library cleaning and deduplication
- AI applications involving structured audio metadata
Languages
- Primary Language: Hebrew (file and folder names)
- The metadata is language-agnostic, though folder/file names are primarily Hebrew.
License
- License: MIT
- Attribution: If using this dataset, please cite appropriately.
Citation
If you use this dataset, please cite the Hugging Face repository or link to: https://huggingface.co/datasets/NHLOCAL/real_music_albums_fs
Contact
Maintained by: NHLOCAL on Hugging Face
For questions, suggestions, or collaborations, feel free to reach out via the Hugging Face profile.
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