The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 26 new columns ({'is_pull_request', 'milestone', 'timeline_url', 'pull_request', 'user', 'repository_url', 'number', 'url', 'labels_url', 'created_at', 'performed_via_github_app', 'assignee', 'id', 'comments_url', 'assignees', 'author_association', 'closed_at', 'labels', 'locked', 'events_url', 'reactions', 'node_id', 'draft', 'updated_at', 'state', 'active_lock_reason'}) and 3 missing columns ({'comment_length', 'text', 'embeddings'}).

This happened while the json dataset builder was generating data using

hf://datasets/eleldar/github-issues/issues-datasets-with-comments.jsonl (at revision faaa5ae72041e00317ea618556294838aae8d07f)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              url: string
              repository_url: string
              labels_url: string
              comments_url: string
              events_url: string
              html_url: string
              id: int64
              node_id: string
              number: int64
              title: string
              user: struct<login: string, id: int64, node_id: string, avatar_url: string, gravatar_id: string, url: string, html_url: string, followers_url: string, following_url: string, gists_url: string, starred_url: string, subscriptions_url: string, organizations_url: string, repos_url: string, events_url: string, received_events_url: string, type: string, site_admin: bool>
                child 0, login: string
                child 1, id: int64
                child 2, node_id: string
                child 3, avatar_url: string
                child 4, gravatar_id: string
                child 5, url: string
                child 6, html_url: string
                child 7, followers_url: string
                child 8, following_url: string
                child 9, gists_url: string
                child 10, starred_url: string
                child 11, subscriptions_url: string
                child 12, organizations_url: string
                child 13, repos_url: string
                child 14, events_url: string
                child 15, received_events_url: string
                child 16, type: string
                child 17, site_admin: bool
              labels: list<item: struct<id: int64, node_id: string, url: string, name: string, color: string, default: bool, description: string>>
                child 0, item: struct<id: int64, node_id: string, url: string, name: string, color: string, default: bool, description: string>
                    child 0, id: int64
                    child 1, node_id: string
                    child 2, url: string
                    child 3, name: string
                    child 4, color: string
                    child 5, defaul
              ...
              ld 7, followers_url: string
                    child 8, following_url: string
                    child 9, gists_url: string
                    child 10, starred_url: string
                    child 11, subscriptions_url: string
                    child 12, organizations_url: string
                    child 13, repos_url: string
                    child 14, events_url: string
                    child 15, received_events_url: string
                    child 16, type: string
                    child 17, site_admin: bool
                child 9, open_issues: int64
                child 10, closed_issues: int64
                child 11, state: string
                child 12, created_at: int64
                child 13, updated_at: int64
                child 14, due_on: int64
                child 15, closed_at: int64
              comments: list<item: string>
                child 0, item: string
              created_at: int64
              updated_at: int64
              closed_at: int64
              author_association: string
              active_lock_reason: null
              body: string
              reactions: struct<url: string, total_count: int64, +1: int64, -1: int64, laugh: int64, hooray: int64, confused: int64, heart: int64, rocket: int64, eyes: int64>
                child 0, url: string
                child 1, total_count: int64
                child 2, +1: int64
                child 3, -1: int64
                child 4, laugh: int64
                child 5, hooray: int64
                child 6, confused: int64
                child 7, heart: int64
                child 8, rocket: int64
                child 9, eyes: int64
              timeline_url: string
              performed_via_github_app: null
              draft: bool
              pull_request: struct<url: string, html_url: string, diff_url: string, patch_url: string, merged_at: int64>
                child 0, url: string
                child 1, html_url: string
                child 2, diff_url: string
                child 3, patch_url: string
                child 4, merged_at: int64
              is_pull_request: bool
              to
              {'html_url': Value(dtype='string', id=None), 'title': Value(dtype='string', id=None), 'comments': Value(dtype='string', id=None), 'body': Value(dtype='string', id=None), 'comment_length': Value(dtype='int64', id=None), 'text': Value(dtype='string', id=None), 'embeddings': Sequence(feature=Value(dtype='float64', id=None), length=-1, id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 26 new columns ({'is_pull_request', 'milestone', 'timeline_url', 'pull_request', 'user', 'repository_url', 'number', 'url', 'labels_url', 'created_at', 'performed_via_github_app', 'assignee', 'id', 'comments_url', 'assignees', 'author_association', 'closed_at', 'labels', 'locked', 'events_url', 'reactions', 'node_id', 'draft', 'updated_at', 'state', 'active_lock_reason'}) and 3 missing columns ({'comment_length', 'text', 'embeddings'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/eleldar/github-issues/issues-datasets-with-comments.jsonl (at revision faaa5ae72041e00317ea618556294838aae8d07f)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

html_url
string
title
string
comments
string
body
string
comment_length
int64
text
string
embeddings
sequence
https://github.com/huggingface/datasets/issues/3973
ConnectionError and SSLError
Hi ! You can download the `oscar.py` file from this repository at `/datasets/oscar/oscar.py`. Then you can load the dataset by passing the local path to `oscar.py` to `load_dataset`: ```python load_dataset("path/to/oscar.py", "unshuffled_deduplicated_it") ```
code ``` from datasets import load_dataset dataset = load_dataset('oscar', 'unshuffled_deduplicated_it') ``` bug report ``` --------------------------------------------------------------------------- ConnectionError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_29788/2615425180.py in <module> ----> 1 dataset = load_dataset('oscar', 'unshuffled_deduplicated_it') D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs) 1658 1659 # Create a dataset builder -> 1660 builder_instance = load_dataset_builder( 1661 path=path, 1662 name=name, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs) 1484 download_config = download_config.copy() if download_config else DownloadConfig() 1485 download_config.use_auth_token = use_auth_token -> 1486 dataset_module = dataset_module_factory( 1487 path, 1488 revision=revision, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_dir, data_files, **download_kwargs) 1236 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}" 1237 ) from None -> 1238 raise e1 from None 1239 else: 1240 raise FileNotFoundError( D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_dir, data_files, **download_kwargs) 1173 if path.count("/") == 0: # even though the dataset is on the Hub, we get it from GitHub for now 1174 # TODO(QL): use a Hub dataset module factory instead of GitHub -> 1175 return GithubDatasetModuleFactory( 1176 path, 1177 revision=revision, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in get_module(self) 531 revision = self.revision 532 try: --> 533 local_path = self.download_loading_script(revision) 534 except FileNotFoundError: 535 if revision is not None or os.getenv("HF_SCRIPTS_VERSION", None) is not None: D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in download_loading_script(self, revision) 511 if download_config.download_desc is None: 512 download_config.download_desc = "Downloading builder script" --> 513 return cached_path(file_path, download_config=download_config) 514 515 def download_dataset_infos_file(self, revision: Optional[str]) -> str: D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\utils\file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs) 232 if is_remote_url(url_or_filename): 233 # URL, so get it from the cache (downloading if necessary) --> 234 output_path = get_from_cache( 235 url_or_filename, 236 cache_dir=cache_dir, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\utils\file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token, ignore_url_params, download_desc) 580 _raise_if_offline_mode_is_enabled(f"Tried to reach {url}") 581 if head_error is not None: --> 582 raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})") 583 elif response is not None: 584 raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})") ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.0.0/datasets/oscar/oscar.py (SSLError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.0.0/datasets/oscar/oscar.py (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:1129)')))"))) ``` It may be caused by Caused by SSLError(in China?) because it works well on google colab. So how can I download this dataset manually?
32
ConnectionError and SSLError code ``` from datasets import load_dataset dataset = load_dataset('oscar', 'unshuffled_deduplicated_it') ``` bug report ``` --------------------------------------------------------------------------- ConnectionError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_29788/2615425180.py in <module> ----> 1 dataset = load_dataset('oscar', 'unshuffled_deduplicated_it') D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, **config_kwargs) 1658 1659 # Create a dataset builder -> 1660 builder_instance = load_dataset_builder( 1661 path=path, 1662 name=name, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in load_dataset_builder(path, name, data_dir, data_files, cache_dir, features, download_config, download_mode, revision, use_auth_token, **config_kwargs) 1484 download_config = download_config.copy() if download_config else DownloadConfig() 1485 download_config.use_auth_token = use_auth_token -> 1486 dataset_module = dataset_module_factory( 1487 path, 1488 revision=revision, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_dir, data_files, **download_kwargs) 1236 f"Couldn't find '{path}' on the Hugging Face Hub either: {type(e1).__name__}: {e1}" 1237 ) from None -> 1238 raise e1 from None 1239 else: 1240 raise FileNotFoundError( D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in dataset_module_factory(path, revision, download_config, download_mode, force_local_path, dynamic_modules_path, data_dir, data_files, **download_kwargs) 1173 if path.count("/") == 0: # even though the dataset is on the Hub, we get it from GitHub for now 1174 # TODO(QL): use a Hub dataset module factory instead of GitHub -> 1175 return GithubDatasetModuleFactory( 1176 path, 1177 revision=revision, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in get_module(self) 531 revision = self.revision 532 try: --> 533 local_path = self.download_loading_script(revision) 534 except FileNotFoundError: 535 if revision is not None or os.getenv("HF_SCRIPTS_VERSION", None) is not None: D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\load.py in download_loading_script(self, revision) 511 if download_config.download_desc is None: 512 download_config.download_desc = "Downloading builder script" --> 513 return cached_path(file_path, download_config=download_config) 514 515 def download_dataset_infos_file(self, revision: Optional[str]) -> str: D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\utils\file_utils.py in cached_path(url_or_filename, download_config, **download_kwargs) 232 if is_remote_url(url_or_filename): 233 # URL, so get it from the cache (downloading if necessary) --> 234 output_path = get_from_cache( 235 url_or_filename, 236 cache_dir=cache_dir, D:\DataScience\PythonSet\IDES\anaconda\lib\site-packages\datasets\utils\file_utils.py in get_from_cache(url, cache_dir, force_download, proxies, etag_timeout, resume_download, user_agent, local_files_only, use_etag, max_retries, use_auth_token, ignore_url_params, download_desc) 580 _raise_if_offline_mode_is_enabled(f"Tried to reach {url}") 581 if head_error is not None: --> 582 raise ConnectionError(f"Couldn't reach {url} ({repr(head_error)})") 583 elif response is not None: 584 raise ConnectionError(f"Couldn't reach {url} (error {response.status_code})") ConnectionError: Couldn't reach https://raw.githubusercontent.com/huggingface/datasets/2.0.0/datasets/oscar/oscar.py (SSLError(MaxRetryError("HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /huggingface/datasets/2.0.0/datasets/oscar/oscar.py (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:1129)')))"))) ``` It may be caused by Caused by SSLError(in China?) because it works well on google colab. So how can I download this dataset manually? Hi ! You can download the `oscar.py` file from this repository at `/datasets/oscar/oscar.py`. Then you can load the dataset by passing the local path to `oscar.py` to `load_dataset`: ```python load_dataset("path/to/oscar.py", "unshuffled_deduplicated_it") ```
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-0.0612009093, 0.187172398, 0.0423916094, 0.2452308536, -0.0002006661, -0.1311197281, 0.1252480447, -0.0863222182 ]
https://github.com/huggingface/datasets/issues/3969
Cannot preview cnn_dailymail dataset
I guess the cache got corrupted due to a previous issue with Google Drive service. The cache should be regenerated, e.g. by passing `download_mode="force_redownload"`. CC: @severo
## Dataset viewer issue for '*cnn_dailymail*' **Link:** https://huggingface.co/datasets/cnn_dailymail *short description of the issue* Am I the one who added this dataset ? Yes-No
26
Cannot preview cnn_dailymail dataset ## Dataset viewer issue for '*cnn_dailymail*' **Link:** https://huggingface.co/datasets/cnn_dailymail *short description of the issue* Am I the one who added this dataset ? Yes-No I guess the cache got corrupted due to a previous issue with Google Drive service. The cache should be regenerated, e.g. by passing `download_mode="force_redownload"`. CC: @severo
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https://github.com/huggingface/datasets/issues/3968
Cannot preview 'indonesian-nlp/eli5_id' dataset
Hi @cahya-wirawan, thanks for reporting. Your dataset is working OK in streaming mode: ```python In [1]: from datasets import load_dataset ...: ds = load_dataset("indonesian-nlp/eli5_id", split="train", streaming=True) ...: item = next(iter(ds)) ...: item Using custom data configuration indonesian-nlp--eli5_id-9fe728a7e760fb7b Out[1]: {'q_id': '1oy5tc', 'title': 'dalam sepak bola apa gunanya menyia-nyiakan dua permainan pertama dengan terburu-buru - di tengah - bukan permainan terburu-buru biasa saya mendapatkannya', 'selftext': '', 'document': '', 'subreddit': 'explainlikeimfive', 'answers': {'a_id': ['ccwtgnz', 'ccwtmho', 'ccwt946', 'ccwvj0u'], 'text': ['Jaga pertahanan tetap jujur, rasakan operan terburu-buru, buka permainan yang lewat. Pelanggaran yang terlalu satu dimensi akan gagal. Dan mereka yang bergegas ke tengah kadang-kadang dapat dibuka lebar-lebar untuk ukuran yard yang besar.', 'Jika Anda melempar bola sepanjang waktu, maka pertahanan akan beradaptasi untuk selalu menutupi umpan. Dengan melakukan permainan lari sederhana sesekali, Anda memaksa pertahanan untuk tetap dekat dan menjaga dari lari. Terkadang, pelanggaran dapat membuat pertahanan lengah dengan berpura-pura berlari dan membebaskan penerima mereka. Selain itu, Anda tidak perlu mendapatkan yard besar di setiap permainan. Terkadang, paling baik mendapatkan beberapa yard sekaligus. Selama Anda mendapatkan yang pertama, Anda dalam kondisi yang baik.', 'Dalam kebanyakan kasus, O-Line seharusnya membuat lubang untuk dilalui kembali. Jika Anda menjalankan terlalu banyak permainan ke luar / melempar, pertahanan akan mengejar. Juga, 2 permainan 5 yard memberi Anda satu set down baru.', 'Saya Anda tidak suka jenis drama itu, tonton CFL. Kami hanya mendapatkan 3 down sehingga Anda tidak bisa menyia-nyiakannya. Lebih banyak lagi yang lewat.'], 'score': [3, 2, 2, 2]}, 'title_urls': {'url': []}, 'selftext_urls': {'url': []}, 'answers_urls': {'url': []}} ``` Therefore, it should be properly rendered in the previewer. Let me ping @severo to have a look at it.
## Dataset viewer issue for '*indonesian-nlp/eli5_id*' **Link:** https://huggingface.co/datasets/indonesian-nlp/eli5_id I can not see the dataset preview. ``` Server Error Status code: 400 Exception: Status400Error Message: Not found. Maybe the cache is missing, or maybe the dataset does not exist. ``` Am I the one who added this dataset ? Yes
271
Cannot preview 'indonesian-nlp/eli5_id' dataset ## Dataset viewer issue for '*indonesian-nlp/eli5_id*' **Link:** https://huggingface.co/datasets/indonesian-nlp/eli5_id I can not see the dataset preview. ``` Server Error Status code: 400 Exception: Status400Error Message: Not found. Maybe the cache is missing, or maybe the dataset does not exist. ``` Am I the one who added this dataset ? Yes Hi @cahya-wirawan, thanks for reporting. Your dataset is working OK in streaming mode: ```python In [1]: from datasets import load_dataset ...: ds = load_dataset("indonesian-nlp/eli5_id", split="train", streaming=True) ...: item = next(iter(ds)) ...: item Using custom data configuration indonesian-nlp--eli5_id-9fe728a7e760fb7b Out[1]: {'q_id': '1oy5tc', 'title': 'dalam sepak bola apa gunanya menyia-nyiakan dua permainan pertama dengan terburu-buru - di tengah - bukan permainan terburu-buru biasa saya mendapatkannya', 'selftext': '', 'document': '', 'subreddit': 'explainlikeimfive', 'answers': {'a_id': ['ccwtgnz', 'ccwtmho', 'ccwt946', 'ccwvj0u'], 'text': ['Jaga pertahanan tetap jujur, rasakan operan terburu-buru, buka permainan yang lewat. Pelanggaran yang terlalu satu dimensi akan gagal. Dan mereka yang bergegas ke tengah kadang-kadang dapat dibuka lebar-lebar untuk ukuran yard yang besar.', 'Jika Anda melempar bola sepanjang waktu, maka pertahanan akan beradaptasi untuk selalu menutupi umpan. Dengan melakukan permainan lari sederhana sesekali, Anda memaksa pertahanan untuk tetap dekat dan menjaga dari lari. Terkadang, pelanggaran dapat membuat pertahanan lengah dengan berpura-pura berlari dan membebaskan penerima mereka. Selain itu, Anda tidak perlu mendapatkan yard besar di setiap permainan. Terkadang, paling baik mendapatkan beberapa yard sekaligus. Selama Anda mendapatkan yang pertama, Anda dalam kondisi yang baik.', 'Dalam kebanyakan kasus, O-Line seharusnya membuat lubang untuk dilalui kembali. Jika Anda menjalankan terlalu banyak permainan ke luar / melempar, pertahanan akan mengejar. Juga, 2 permainan 5 yard memberi Anda satu set down baru.', 'Saya Anda tidak suka jenis drama itu, tonton CFL. Kami hanya mendapatkan 3 down sehingga Anda tidak bisa menyia-nyiakannya. Lebih banyak lagi yang lewat.'], 'score': [3, 2, 2, 2]}, 'title_urls': {'url': []}, 'selftext_urls': {'url': []}, 'answers_urls': {'url': []}} ``` Therefore, it should be properly rendered in the previewer. Let me ping @severo to have a look at it.
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0.010053739, 0.5650959611, -0.0282601137, 0.0279992819, 0.0998950824, -0.4115599096 ]
https://github.com/huggingface/datasets/issues/3968
Cannot preview 'indonesian-nlp/eli5_id' dataset
Thanks @albertvillanova for checking it. Btw, I have another dataset indonesian-nlp/lfqa_id which has the same issue. However, this dataset is still private, is it the reason why the preview doesn't work?
## Dataset viewer issue for '*indonesian-nlp/eli5_id*' **Link:** https://huggingface.co/datasets/indonesian-nlp/eli5_id I can not see the dataset preview. ``` Server Error Status code: 400 Exception: Status400Error Message: Not found. Maybe the cache is missing, or maybe the dataset does not exist. ``` Am I the one who added this dataset ? Yes
31
Cannot preview 'indonesian-nlp/eli5_id' dataset ## Dataset viewer issue for '*indonesian-nlp/eli5_id*' **Link:** https://huggingface.co/datasets/indonesian-nlp/eli5_id I can not see the dataset preview. ``` Server Error Status code: 400 Exception: Status400Error Message: Not found. Maybe the cache is missing, or maybe the dataset does not exist. ``` Am I the one who added this dataset ? Yes Thanks @albertvillanova for checking it. Btw, I have another dataset indonesian-nlp/lfqa_id which has the same issue. However, this dataset is still private, is it the reason why the preview doesn't work?
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https://github.com/huggingface/datasets/issues/3965
TypeError: Couldn't cast array of type for JSONLines dataset
Hi @lewtun, thanks for reporting. It seems that our library fails at inferring the dtype of the columns: - `milestone` - `performed_via_github_app` (and assigns them `null` dtype).
## Describe the bug One of the [course participants](https://discuss.huggingface.co/t/chapter-5-questions/11744/20?u=lewtun) is having trouble loading a JSONLines dataset that's composed of the GitHub issues from `spacy` (see stack trace below). This reminds me a bit of #2799 where one can load the dataset in `pandas` but not in `datasets` and perhaps increasing the `block_size` is needed again. ## Steps to reproduce the bug ```python from datasets import load_dataset from huggingface_hub import hf_hub_url import pandas as pd # returns 'https://huggingface.co/datasets/Evan/spaCy-github-issues/resolve/main/spacy-issues.jsonl' data_files = hf_hub_url(repo_id="Evan/spaCy-github-issues", filename="spacy-issues.jsonl", repo_type="dataset") # throws TypeError: Couldn't cast array of type dset = load_dataset("json", data_files=data_files, split="test") # no problem with pandas - note this take a while as the file is >2GB df = pd.read_json(data_files, orient="records", lines=True) df.head() ``` ## Expected results I can load any line-separated JSON file, similar to pandas. ## Actual results ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset builder_instance.download_and_prepare( File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare self._download_and_prepare( File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 683, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 1136, in _prepare_split writer.write_table(table) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/arrow_writer.py", line 511, in write_table pa_table = table_cast(pa_table, self._schema) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1121, in table_cast return cast_table_to_features(table, Features.from_arrow_schema(schema)) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in cast_table_to_features arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in <listcomp> arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper return func(array, *args, **kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in wrapper return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in <listcomp> return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1086, in cast_array_to_feature return array_cast(array, feature(), allow_number_to_str=allow_number_to_str) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper return func(array, *args, **kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 920, in wrapper return func(array, *args, **kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1019, in array_cast raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}") TypeError: Couldn't cast array of type struct<url: string, html_url: string, labels_url: string, id: int64, node_id: string, number: int64, title: string, description: string, creator: struct<login: string, id: int64, node_id: string, avatar_url: string, gravatar_id: string, url: string, html_url: string, followers_url: string, following_url: string, gists_url: string, starred_url: string, subscriptions_url: string, organizations_url: string, repos_url: string, events_url: string, received_events_url: string, type: string, site_admin: bool>, open_issues: int64, closed_issues: int64, state: string, created_at: timestamp[s], updated_at: timestamp[s], due_on: null, closed_at: timestamp[s]> to null ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.9.7 - PyArrow version: 7.0.0 - Pandas version: 1.4.1
27
TypeError: Couldn't cast array of type for JSONLines dataset ## Describe the bug One of the [course participants](https://discuss.huggingface.co/t/chapter-5-questions/11744/20?u=lewtun) is having trouble loading a JSONLines dataset that's composed of the GitHub issues from `spacy` (see stack trace below). This reminds me a bit of #2799 where one can load the dataset in `pandas` but not in `datasets` and perhaps increasing the `block_size` is needed again. ## Steps to reproduce the bug ```python from datasets import load_dataset from huggingface_hub import hf_hub_url import pandas as pd # returns 'https://huggingface.co/datasets/Evan/spaCy-github-issues/resolve/main/spacy-issues.jsonl' data_files = hf_hub_url(repo_id="Evan/spaCy-github-issues", filename="spacy-issues.jsonl", repo_type="dataset") # throws TypeError: Couldn't cast array of type dset = load_dataset("json", data_files=data_files, split="test") # no problem with pandas - note this take a while as the file is >2GB df = pd.read_json(data_files, orient="records", lines=True) df.head() ``` ## Expected results I can load any line-separated JSON file, similar to pandas. ## Actual results ``` Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/load.py", line 1702, in load_dataset builder_instance.download_and_prepare( File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 594, in download_and_prepare self._download_and_prepare( File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 683, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/builder.py", line 1136, in _prepare_split writer.write_table(table) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/arrow_writer.py", line 511, in write_table pa_table = table_cast(pa_table, self._schema) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1121, in table_cast return cast_table_to_features(table, Features.from_arrow_schema(schema)) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in cast_table_to_features arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1102, in <listcomp> arrays = [cast_array_to_feature(table[name], feature) for name, feature in features.items()] File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper return func(array, *args, **kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in wrapper return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 918, in <listcomp> return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks]) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1086, in cast_array_to_feature return array_cast(array, feature(), allow_number_to_str=allow_number_to_str) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 944, in wrapper return func(array, *args, **kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 920, in wrapper return func(array, *args, **kwargs) File "/Users/lewtun/miniconda3/envs/hf/lib/python3.9/site-packages/datasets/table.py", line 1019, in array_cast raise TypeError(f"Couldn't cast array of type\n{array.type}\nto\n{pa_type}") TypeError: Couldn't cast array of type struct<url: string, html_url: string, labels_url: string, id: int64, node_id: string, number: int64, title: string, description: string, creator: struct<login: string, id: int64, node_id: string, avatar_url: string, gravatar_id: string, url: string, html_url: string, followers_url: string, following_url: string, gists_url: string, starred_url: string, subscriptions_url: string, organizations_url: string, repos_url: string, events_url: string, received_events_url: string, type: string, site_admin: bool>, open_issues: int64, closed_issues: int64, state: string, created_at: timestamp[s], updated_at: timestamp[s], due_on: null, closed_at: timestamp[s]> to null ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: macOS-10.16-x86_64-i386-64bit - Python version: 3.9.7 - PyArrow version: 7.0.0 - Pandas version: 1.4.1 Hi @lewtun, thanks for reporting. It seems that our library fails at inferring the dtype of the columns: - `milestone` - `performed_via_github_app` (and assigns them `null` dtype).
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https://github.com/huggingface/datasets/issues/3960
Load local dataset error
Hi! Instead of @nateraw's `image-folder`, I suggest using the newly released `imagefolder` dataset: ```python >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train/**'], 'validation': ['/ssd/datasets/imagenet/pytorch/val/**']} >>> ds = load_dataset('imagefolder', data_files=data_files, cache_dir='./', task='image-classification') ``` Let us know if that resolves the issue.
When i used the datasets==1.11.0, it's all right. Util update the latest version, it get the error like this: ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train'], 'validation': ['/ssd/datasets/imagenet/pytorch/val']} >>> ds = load_dataset('nateraw/image-folder', data_files=data_files, cache_dir='./', task='image-classification') [] https://huggingface.co/datasets/nateraw/image-folder/resolve/main/ /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1671, in load_dataset **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1521, in load_dataset_builder **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 1031, in __init__ super().__init__(*args, **kwargs) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 255, in __init__ sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 584, in from_local_or_remote if not isinstance(patterns_for_key, DataFilesList) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 546, in from_local_or_remote data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 196, in resolve_patterns_locally_or_by_urls for path in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions): File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 146, in _resolve_single_pattern_locally raise FileNotFoundError(error_msg) FileNotFoundError: Unable to find '/ssd/datasets/imagenet/pytorch/train' at /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main ``` I need some help to solve the problem, thanks!
40
Load local dataset error When i used the datasets==1.11.0, it's all right. Util update the latest version, it get the error like this: ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train'], 'validation': ['/ssd/datasets/imagenet/pytorch/val']} >>> ds = load_dataset('nateraw/image-folder', data_files=data_files, cache_dir='./', task='image-classification') [] https://huggingface.co/datasets/nateraw/image-folder/resolve/main/ /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1671, in load_dataset **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1521, in load_dataset_builder **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 1031, in __init__ super().__init__(*args, **kwargs) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 255, in __init__ sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 584, in from_local_or_remote if not isinstance(patterns_for_key, DataFilesList) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 546, in from_local_or_remote data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 196, in resolve_patterns_locally_or_by_urls for path in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions): File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 146, in _resolve_single_pattern_locally raise FileNotFoundError(error_msg) FileNotFoundError: Unable to find '/ssd/datasets/imagenet/pytorch/train' at /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main ``` I need some help to solve the problem, thanks! Hi! Instead of @nateraw's `image-folder`, I suggest using the newly released `imagefolder` dataset: ```python >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train/**'], 'validation': ['/ssd/datasets/imagenet/pytorch/val/**']} >>> ds = load_dataset('imagefolder', data_files=data_files, cache_dir='./', task='image-classification') ``` Let us know if that resolves the issue.
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https://github.com/huggingface/datasets/issues/3960
Load local dataset error
> Hi! Instead of @nateraw's `image-folder`, I suggest using the newly released `imagefolder` dataset: > > ```python > >>> from datasets import load_dataset > >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train/**'], 'validation': ['/ssd/datasets/imagenet/pytorch/val/**']} > >>> ds = load_dataset('imagefolder', data_files=data_files, cache_dir='./', task='image-classification') > ``` > > Let us know if that resolves the issue. Sorry, replied late. Thanks a lot! It's worked for me. But it seems much slower than before, and now gets stuck..... ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train/**'], 'validation': ['/ssd/datasets/imagenet/pytorch/val/**']} >>> ds = load_dataset('imagefolder', data_files=data_files, cache_dir='./', task='image-classification') Resolving data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1281167/1281167 [00:02<00:00, 437283.97it/s] Resolving data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50001/50001 [00:00<00:00, 89094.29it/s] Using custom data configuration default-baebca6347576b33 Downloading and preparing dataset image_folder/default to ./image_folder/default-baebca6347576b33/0.0.0/ee92df8e96c6907f3c851a987be3fd03d4b93b247e727b69a8e23ac94392a091... 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When i used the datasets==1.11.0, it's all right. Util update the latest version, it get the error like this: ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train'], 'validation': ['/ssd/datasets/imagenet/pytorch/val']} >>> ds = load_dataset('nateraw/image-folder', data_files=data_files, cache_dir='./', task='image-classification') [] https://huggingface.co/datasets/nateraw/image-folder/resolve/main/ /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1671, in load_dataset **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1521, in load_dataset_builder **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 1031, in __init__ super().__init__(*args, **kwargs) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 255, in __init__ sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 584, in from_local_or_remote if not isinstance(patterns_for_key, DataFilesList) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 546, in from_local_or_remote data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 196, in resolve_patterns_locally_or_by_urls for path in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions): File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 146, in _resolve_single_pattern_locally raise FileNotFoundError(error_msg) FileNotFoundError: Unable to find '/ssd/datasets/imagenet/pytorch/train' at /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main ``` I need some help to solve the problem, thanks!
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Load local dataset error When i used the datasets==1.11.0, it's all right. Util update the latest version, it get the error like this: ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train'], 'validation': ['/ssd/datasets/imagenet/pytorch/val']} >>> ds = load_dataset('nateraw/image-folder', data_files=data_files, cache_dir='./', task='image-classification') [] https://huggingface.co/datasets/nateraw/image-folder/resolve/main/ /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1671, in load_dataset **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/load.py", line 1521, in load_dataset_builder **config_kwargs, File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 1031, in __init__ super().__init__(*args, **kwargs) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/builder.py", line 255, in __init__ sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 584, in from_local_or_remote if not isinstance(patterns_for_key, DataFilesList) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 546, in from_local_or_remote data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions) File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 196, in resolve_patterns_locally_or_by_urls for path in _resolve_single_pattern_locally(base_path, pattern, allowed_extensions): File "/gf3/home/txacs/gv3/anaconda3/envs/txacs/lib/python3.6/site-packages/datasets/data_files.py", line 146, in _resolve_single_pattern_locally raise FileNotFoundError(error_msg) FileNotFoundError: Unable to find '/ssd/datasets/imagenet/pytorch/train' at /dat/txacs/git/txacs/examples/image-classification/https:/huggingface.co/datasets/nateraw/image-folder/resolve/main ``` I need some help to solve the problem, thanks! > Hi! Instead of @nateraw's `image-folder`, I suggest using the newly released `imagefolder` dataset: > > ```python > >>> from datasets import load_dataset > >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train/**'], 'validation': ['/ssd/datasets/imagenet/pytorch/val/**']} > >>> ds = load_dataset('imagefolder', data_files=data_files, cache_dir='./', task='image-classification') > ``` > > Let us know if that resolves the issue. Sorry, replied late. Thanks a lot! It's worked for me. But it seems much slower than before, and now gets stuck..... ``` >>> from datasets import load_dataset >>> data_files={'train': ['/ssd/datasets/imagenet/pytorch/train/**'], 'validation': ['/ssd/datasets/imagenet/pytorch/val/**']} >>> ds = load_dataset('imagefolder', data_files=data_files, cache_dir='./', task='image-classification') Resolving data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1281167/1281167 [00:02<00:00, 437283.97it/s] Resolving data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50001/50001 [00:00<00:00, 89094.29it/s] Using custom data configuration default-baebca6347576b33 Downloading and preparing dataset image_folder/default to ./image_folder/default-baebca6347576b33/0.0.0/ee92df8e96c6907f3c851a987be3fd03d4b93b247e727b69a8e23ac94392a091... 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https://github.com/huggingface/datasets/issues/3956
TypeError: __init__() missing 1 required positional argument: 'scheme'
Hi @amirj, thanks for reporting. At first sight, your issue seems a version incompatibility between your Elasticsearch client and your Elasticsearch server. Feel free to have a look at Elasticsearch client docs: https://www.elastic.co/guide/en/elasticsearch/client/python-api/current/overview.html#_compatibility > Language clients are forward compatible; meaning that clients support communicating with greater or equal minor versions of Elasticsearch. Elasticsearch language clients are only backwards compatible with default distributions and without guarantees made.
## Describe the bug Based on [this tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) the provided code should add Elasticsearch index but raised the following error, probably the new Elasticsearch version is not compatible though the tutorial doesn't provide any information about the supporting Elasticsearch version. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import load_dataset squad = load_dataset('squad', split='validation') squad.add_elasticsearch_index("context", host="localhost", port="9200") ``` ## Expected results [Creating an elastic index based on the provided tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) ## Actual results ``` --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-8fb51aa33961> in <module> 1 from datasets import load_dataset 2 squad = load_dataset('squad', split='validation') ----> 3 squad.add_elasticsearch_index("context", host="localhost", port="9200") ~/opt/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 3777 """ 3778 with self.formatted_as(type=None, columns=[column]): -> 3779 super().add_elasticsearch_index( 3780 column=column, 3781 index_name=index_name, ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 587 """ 588 index_name = index_name if index_name is not None else column --> 589 es_index = ElasticSearchIndex( 590 host=host, port=port, es_client=es_client, es_index_name=es_index_name, es_index_config=es_index_config 591 ) ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in __init__(self, host, port, es_client, es_index_name, es_index_config) 123 from elasticsearch import Elasticsearch # noqa: F811 124 --> 125 self.es_client = es_client if es_client is not None else Elasticsearch([{"host": host, "port": str(port)}]) 126 self.es_index_name = ( 127 es_index_name ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/__init__.py in __init__(self, hosts, cloud_id, api_key, basic_auth, bearer_auth, opaque_id, headers, connections_per_node, http_compress, verify_certs, ca_certs, client_cert, client_key, ssl_assert_hostname, ssl_assert_fingerprint, ssl_version, ssl_context, ssl_show_warn, transport_class, request_timeout, node_class, node_pool_class, randomize_nodes_in_pool, node_selector_class, dead_node_backoff_factor, max_dead_node_backoff, serializer, serializers, default_mimetype, max_retries, retry_on_status, retry_on_timeout, sniff_on_start, sniff_before_requests, sniff_on_node_failure, sniff_timeout, min_delay_between_sniffing, sniffed_node_callback, meta_header, timeout, randomize_hosts, host_info_callback, sniffer_timeout, sniff_on_connection_fail, http_auth, maxsize, _transport) 310 311 if _transport is None: --> 312 node_configs = client_node_configs( 313 hosts, 314 cloud_id=cloud_id, ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in client_node_configs(hosts, cloud_id, **kwargs) 99 else: 100 assert hosts is not None --> 101 node_configs = hosts_to_node_configs(hosts) 102 103 # Remove all values which are 'DEFAULT' to avoid overwriting actual defaults. ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in hosts_to_node_configs(hosts) 142 143 elif isinstance(host, Mapping): --> 144 node_configs.append(host_mapping_to_node_config(host)) 145 else: 146 raise ValueError( ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in host_mapping_to_node_config(host) 209 options["path_prefix"] = options.pop("url_prefix") 210 --> 211 return NodeConfig(**options) # type: ignore 212 213 TypeError: __init__() missing 1 required positional argument: 'scheme' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: Mac - Python version: 3.8.0 - PyArrow version: 7.0.0 - ElaticSearch Info: { "name" : "byname", "cluster_name" : "elasticsearch_brew", "cluster_uuid" : "9xkjrltiQIG0J95ciWhqRA", "version" : { "number" : "7.10.2-SNAPSHOT", "build_flavor" : "oss", "build_type" : "tar", "build_hash" : "unknown", "build_date" : "2021-01-16T01:41:27.115673Z", "build_snapshot" : true, "lucene_version" : "8.7.0", "minimum_wire_compatibility_version" : "6.8.0", "minimum_index_compatibility_version" : "6.0.0-beta1" }, "tagline" : "You Know, for Search" }
66
TypeError: __init__() missing 1 required positional argument: 'scheme' ## Describe the bug Based on [this tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) the provided code should add Elasticsearch index but raised the following error, probably the new Elasticsearch version is not compatible though the tutorial doesn't provide any information about the supporting Elasticsearch version. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import load_dataset squad = load_dataset('squad', split='validation') squad.add_elasticsearch_index("context", host="localhost", port="9200") ``` ## Expected results [Creating an elastic index based on the provided tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) ## Actual results ``` --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-8fb51aa33961> in <module> 1 from datasets import load_dataset 2 squad = load_dataset('squad', split='validation') ----> 3 squad.add_elasticsearch_index("context", host="localhost", port="9200") ~/opt/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 3777 """ 3778 with self.formatted_as(type=None, columns=[column]): -> 3779 super().add_elasticsearch_index( 3780 column=column, 3781 index_name=index_name, ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 587 """ 588 index_name = index_name if index_name is not None else column --> 589 es_index = ElasticSearchIndex( 590 host=host, port=port, es_client=es_client, es_index_name=es_index_name, es_index_config=es_index_config 591 ) ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in __init__(self, host, port, es_client, es_index_name, es_index_config) 123 from elasticsearch import Elasticsearch # noqa: F811 124 --> 125 self.es_client = es_client if es_client is not None else Elasticsearch([{"host": host, "port": str(port)}]) 126 self.es_index_name = ( 127 es_index_name ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/__init__.py in __init__(self, hosts, cloud_id, api_key, basic_auth, bearer_auth, opaque_id, headers, connections_per_node, http_compress, verify_certs, ca_certs, client_cert, client_key, ssl_assert_hostname, ssl_assert_fingerprint, ssl_version, ssl_context, ssl_show_warn, transport_class, request_timeout, node_class, node_pool_class, randomize_nodes_in_pool, node_selector_class, dead_node_backoff_factor, max_dead_node_backoff, serializer, serializers, default_mimetype, max_retries, retry_on_status, retry_on_timeout, sniff_on_start, sniff_before_requests, sniff_on_node_failure, sniff_timeout, min_delay_between_sniffing, sniffed_node_callback, meta_header, timeout, randomize_hosts, host_info_callback, sniffer_timeout, sniff_on_connection_fail, http_auth, maxsize, _transport) 310 311 if _transport is None: --> 312 node_configs = client_node_configs( 313 hosts, 314 cloud_id=cloud_id, ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in client_node_configs(hosts, cloud_id, **kwargs) 99 else: 100 assert hosts is not None --> 101 node_configs = hosts_to_node_configs(hosts) 102 103 # Remove all values which are 'DEFAULT' to avoid overwriting actual defaults. ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in hosts_to_node_configs(hosts) 142 143 elif isinstance(host, Mapping): --> 144 node_configs.append(host_mapping_to_node_config(host)) 145 else: 146 raise ValueError( ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in host_mapping_to_node_config(host) 209 options["path_prefix"] = options.pop("url_prefix") 210 --> 211 return NodeConfig(**options) # type: ignore 212 213 TypeError: __init__() missing 1 required positional argument: 'scheme' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: Mac - Python version: 3.8.0 - PyArrow version: 7.0.0 - ElaticSearch Info: { "name" : "byname", "cluster_name" : "elasticsearch_brew", "cluster_uuid" : "9xkjrltiQIG0J95ciWhqRA", "version" : { "number" : "7.10.2-SNAPSHOT", "build_flavor" : "oss", "build_type" : "tar", "build_hash" : "unknown", "build_date" : "2021-01-16T01:41:27.115673Z", "build_snapshot" : true, "lucene_version" : "8.7.0", "minimum_wire_compatibility_version" : "6.8.0", "minimum_index_compatibility_version" : "6.0.0-beta1" }, "tagline" : "You Know, for Search" } Hi @amirj, thanks for reporting. At first sight, your issue seems a version incompatibility between your Elasticsearch client and your Elasticsearch server. Feel free to have a look at Elasticsearch client docs: https://www.elastic.co/guide/en/elasticsearch/client/python-api/current/overview.html#_compatibility > Language clients are forward compatible; meaning that clients support communicating with greater or equal minor versions of Elasticsearch. Elasticsearch language clients are only backwards compatible with default distributions and without guarantees made.
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https://github.com/huggingface/datasets/issues/3956
TypeError: __init__() missing 1 required positional argument: 'scheme'
@albertvillanova It doesn't seem a version incompatibility between the client and server, since the following code is working: ``` from elasticsearch import Elasticsearch es_client = Elasticsearch("http://localhost:9200") dataset.add_elasticsearch_index(column="e1", es_client=es_client, es_index_name="e1_index") ```
## Describe the bug Based on [this tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) the provided code should add Elasticsearch index but raised the following error, probably the new Elasticsearch version is not compatible though the tutorial doesn't provide any information about the supporting Elasticsearch version. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import load_dataset squad = load_dataset('squad', split='validation') squad.add_elasticsearch_index("context", host="localhost", port="9200") ``` ## Expected results [Creating an elastic index based on the provided tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) ## Actual results ``` --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-8fb51aa33961> in <module> 1 from datasets import load_dataset 2 squad = load_dataset('squad', split='validation') ----> 3 squad.add_elasticsearch_index("context", host="localhost", port="9200") ~/opt/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 3777 """ 3778 with self.formatted_as(type=None, columns=[column]): -> 3779 super().add_elasticsearch_index( 3780 column=column, 3781 index_name=index_name, ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 587 """ 588 index_name = index_name if index_name is not None else column --> 589 es_index = ElasticSearchIndex( 590 host=host, port=port, es_client=es_client, es_index_name=es_index_name, es_index_config=es_index_config 591 ) ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in __init__(self, host, port, es_client, es_index_name, es_index_config) 123 from elasticsearch import Elasticsearch # noqa: F811 124 --> 125 self.es_client = es_client if es_client is not None else Elasticsearch([{"host": host, "port": str(port)}]) 126 self.es_index_name = ( 127 es_index_name ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/__init__.py in __init__(self, hosts, cloud_id, api_key, basic_auth, bearer_auth, opaque_id, headers, connections_per_node, http_compress, verify_certs, ca_certs, client_cert, client_key, ssl_assert_hostname, ssl_assert_fingerprint, ssl_version, ssl_context, ssl_show_warn, transport_class, request_timeout, node_class, node_pool_class, randomize_nodes_in_pool, node_selector_class, dead_node_backoff_factor, max_dead_node_backoff, serializer, serializers, default_mimetype, max_retries, retry_on_status, retry_on_timeout, sniff_on_start, sniff_before_requests, sniff_on_node_failure, sniff_timeout, min_delay_between_sniffing, sniffed_node_callback, meta_header, timeout, randomize_hosts, host_info_callback, sniffer_timeout, sniff_on_connection_fail, http_auth, maxsize, _transport) 310 311 if _transport is None: --> 312 node_configs = client_node_configs( 313 hosts, 314 cloud_id=cloud_id, ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in client_node_configs(hosts, cloud_id, **kwargs) 99 else: 100 assert hosts is not None --> 101 node_configs = hosts_to_node_configs(hosts) 102 103 # Remove all values which are 'DEFAULT' to avoid overwriting actual defaults. ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in hosts_to_node_configs(hosts) 142 143 elif isinstance(host, Mapping): --> 144 node_configs.append(host_mapping_to_node_config(host)) 145 else: 146 raise ValueError( ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in host_mapping_to_node_config(host) 209 options["path_prefix"] = options.pop("url_prefix") 210 --> 211 return NodeConfig(**options) # type: ignore 212 213 TypeError: __init__() missing 1 required positional argument: 'scheme' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: Mac - Python version: 3.8.0 - PyArrow version: 7.0.0 - ElaticSearch Info: { "name" : "byname", "cluster_name" : "elasticsearch_brew", "cluster_uuid" : "9xkjrltiQIG0J95ciWhqRA", "version" : { "number" : "7.10.2-SNAPSHOT", "build_flavor" : "oss", "build_type" : "tar", "build_hash" : "unknown", "build_date" : "2021-01-16T01:41:27.115673Z", "build_snapshot" : true, "lucene_version" : "8.7.0", "minimum_wire_compatibility_version" : "6.8.0", "minimum_index_compatibility_version" : "6.0.0-beta1" }, "tagline" : "You Know, for Search" }
30
TypeError: __init__() missing 1 required positional argument: 'scheme' ## Describe the bug Based on [this tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) the provided code should add Elasticsearch index but raised the following error, probably the new Elasticsearch version is not compatible though the tutorial doesn't provide any information about the supporting Elasticsearch version. ## Steps to reproduce the bug ```python # Sample code to reproduce the bug from datasets import load_dataset squad = load_dataset('squad', split='validation') squad.add_elasticsearch_index("context", host="localhost", port="9200") ``` ## Expected results [Creating an elastic index based on the provided tutorial](https://huggingface.co/docs/datasets/faiss_es#elasticsearch) ## Actual results ``` --------------------------------------------------------------------------- TypeError Traceback (most recent call last) <ipython-input-6-8fb51aa33961> in <module> 1 from datasets import load_dataset 2 squad = load_dataset('squad', split='validation') ----> 3 squad.add_elasticsearch_index("context", host="localhost", port="9200") ~/opt/anaconda3/lib/python3.8/site-packages/datasets/arrow_dataset.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 3777 """ 3778 with self.formatted_as(type=None, columns=[column]): -> 3779 super().add_elasticsearch_index( 3780 column=column, 3781 index_name=index_name, ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in add_elasticsearch_index(self, column, index_name, host, port, es_client, es_index_name, es_index_config) 587 """ 588 index_name = index_name if index_name is not None else column --> 589 es_index = ElasticSearchIndex( 590 host=host, port=port, es_client=es_client, es_index_name=es_index_name, es_index_config=es_index_config 591 ) ~/opt/anaconda3/lib/python3.8/site-packages/datasets/search.py in __init__(self, host, port, es_client, es_index_name, es_index_config) 123 from elasticsearch import Elasticsearch # noqa: F811 124 --> 125 self.es_client = es_client if es_client is not None else Elasticsearch([{"host": host, "port": str(port)}]) 126 self.es_index_name = ( 127 es_index_name ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/__init__.py in __init__(self, hosts, cloud_id, api_key, basic_auth, bearer_auth, opaque_id, headers, connections_per_node, http_compress, verify_certs, ca_certs, client_cert, client_key, ssl_assert_hostname, ssl_assert_fingerprint, ssl_version, ssl_context, ssl_show_warn, transport_class, request_timeout, node_class, node_pool_class, randomize_nodes_in_pool, node_selector_class, dead_node_backoff_factor, max_dead_node_backoff, serializer, serializers, default_mimetype, max_retries, retry_on_status, retry_on_timeout, sniff_on_start, sniff_before_requests, sniff_on_node_failure, sniff_timeout, min_delay_between_sniffing, sniffed_node_callback, meta_header, timeout, randomize_hosts, host_info_callback, sniffer_timeout, sniff_on_connection_fail, http_auth, maxsize, _transport) 310 311 if _transport is None: --> 312 node_configs = client_node_configs( 313 hosts, 314 cloud_id=cloud_id, ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in client_node_configs(hosts, cloud_id, **kwargs) 99 else: 100 assert hosts is not None --> 101 node_configs = hosts_to_node_configs(hosts) 102 103 # Remove all values which are 'DEFAULT' to avoid overwriting actual defaults. ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in hosts_to_node_configs(hosts) 142 143 elif isinstance(host, Mapping): --> 144 node_configs.append(host_mapping_to_node_config(host)) 145 else: 146 raise ValueError( ~/opt/anaconda3/lib/python3.8/site-packages/elasticsearch/_sync/client/utils.py in host_mapping_to_node_config(host) 209 options["path_prefix"] = options.pop("url_prefix") 210 --> 211 return NodeConfig(**options) # type: ignore 212 213 TypeError: __init__() missing 1 required positional argument: 'scheme' ``` ## Environment info <!-- You can run the command `datasets-cli env` and copy-and-paste its output below. --> - `datasets` version: 2.0.0 - Platform: Mac - Python version: 3.8.0 - PyArrow version: 7.0.0 - ElaticSearch Info: { "name" : "byname", "cluster_name" : "elasticsearch_brew", "cluster_uuid" : "9xkjrltiQIG0J95ciWhqRA", "version" : { "number" : "7.10.2-SNAPSHOT", "build_flavor" : "oss", "build_type" : "tar", "build_hash" : "unknown", "build_date" : "2021-01-16T01:41:27.115673Z", "build_snapshot" : true, "lucene_version" : "8.7.0", "minimum_wire_compatibility_version" : "6.8.0", "minimum_index_compatibility_version" : "6.0.0-beta1" }, "tagline" : "You Know, for Search" } @albertvillanova It doesn't seem a version incompatibility between the client and server, since the following code is working: ``` from elasticsearch import Elasticsearch es_client = Elasticsearch("http://localhost:9200") dataset.add_elasticsearch_index(column="e1", es_client=es_client, es_index_name="e1_index") ```
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https://github.com/huggingface/datasets/issues/3956
TypeError: __init__() missing 1 required positional argument: 'scheme'
"Hi @amirj, \r\n\r\nI really think it is a version incompatibility issue between your Elasticsearch (...TRUNCATED)
"## Describe the bug\r\nBased on [this tutorial](https://huggingface.co/docs/datasets/faiss_es#elast(...TRUNCATED)
125
"TypeError: __init__() missing 1 required positional argument: 'scheme' \n ## Describe the bug\r\nBa(...TRUNCATED)
[-0.2016850263,-0.3632028699,-0.0670639575,-0.1154993474,-0.0156479795,0.2479981333,0.2341077775,0.2(...TRUNCATED)
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