Consider using "Sequence" instead of "List"

### Feature request

Hi, please consider using `Sequence` type annotation instead of `List` in function arguments such as in [`Dataset.from_parquet()`](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L1088). It leads to type checking errors, see below.


**How to reproduce**
```py
list_of_filenames = ["foo.parquet", "bar.parquet"]
ds = Dataset.from_parquet(list_of_filenames)
```

**Expected mypy output:**
```
Success: no issues found
```

**Actual mypy output:**
```py
test.py:19: error: Argument 1 to "from_parquet" of "Dataset" has incompatible type "List[str]"; expected "Union[Union[str, bytes, PathLike[Any]], List[Union[str, bytes, PathLike[Any]]]]"  [arg-type]
test.py:19: note: "List" is invariant -- see https://mypy.readthedocs.io/en/stable/common_issues.html#variance
test.py:19: note: Consider using "Sequence" instead, which is covariant
```

**Env:** mypy 0.991, Python 3.10.0, datasets 2.7.1

Comments:
Hi! Linking a comment to provide more info on the issue: https://stackoverflow.com/a/39458225. This means we should replace all (most of) the occurrences of `List` with `Sequence` in function signatures.

@tranhd95 Would you be interested in submitting a PR?

Hi all! I tried to reproduce this issue and didn't work for me. Also in your example i noticed that the variables have different names: `list_of_filenames` and `list_of_files`, could this be related to that?
```python
#I found random data in parquet format:
!wget "https://github.com/Teradata/kylo/raw/master/samples/sample-data/parquet/userdata1.parquet"
!wget "https://github.com/Teradata/kylo/raw/master/samples/sample-data/parquet/userdata2.parquet"

#Then i try reproduce
list_of_files = ["userdata1.parquet", "userdata2.parquet"]
ds = Dataset.from_parquet(list_of_files)
```
**My output:**
```python
WARNING:datasets.builder:Using custom data configuration default-e287d097dc54e046
Downloading and preparing dataset parquet/default to /root/.cache/huggingface/datasets/parquet/default-e287d097dc54e046/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec...
Downloading data files: 100%
1/1 [00:00<00:00, 40.38it/s]
Extracting data files: 100%
1/1 [00:00<00:00, 23.43it/s]
Dataset parquet downloaded and prepared to /root/.cache/huggingface/datasets/parquet/default-e287d097dc54e046/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec. Subsequent calls will reuse this data.
```
P.S. This is my first experience with open source. So do not judge strictly if I do not understand something)

@dantema There is indeed a typo in variable names. Nevertheless, I'm sorry if I was not clear but the output is from `mypy` type checker. You can run the code snippet without issues. The problem is with the type checking.

However, I found out that the type annotation is actually misleading. The [`from_parquet`](https://github.com/huggingface/datasets/blob/5ef1ab1cc06c2b7a574bf2df454cd9fcb071ccb2/src/datasets/arrow_dataset.py#L1039) method should also accept list of [`PathLike`](https://github.com/huggingface/datasets/blob/main/src/datasets/utils/typing.py#L8) objects which includes [`os.PathLike`](https://docs.python.org/3/library/os.html#os.PathLike). But if I would ran the code snippet below, an exception is thrown.

**Code**
```py
from pathlib import Path

list_of_filenames = [Path("foo.parquet"), Path("bar.parquet")]
ds = Dataset.from_parquet(list_of_filenames)
```
**Output**
```py
[/usr/local/lib/python3.8/dist-packages/datasets/arrow_dataset.py](https://localhost:8080/#) in from_parquet(path_or_paths, split, features, cache_dir, keep_in_memory, columns, **kwargs)
   1071         from .io.parquet import ParquetDatasetReader
   1072 
-> 1073         return ParquetDatasetReader(
   1074             path_or_paths,
   1075             split=split,

[/usr/local/lib/python3.8/dist-packages/datasets/io/parquet.py](https://localhost:8080/#) in __init__(self, path_or_paths, split, features, cache_dir, keep_in_memory, streaming, **kwargs)
     35         path_or_paths = path_or_paths if isinstance(path_or_paths, dict) else {self.split: path_or_paths}
     36         hash = _PACKAGED_DATASETS_MODULES["parquet"][1]
---> 37         self.builder = Parquet(
     38             cache_dir=cache_dir,
     39             data_files=path_or_paths,

[/usr/local/lib/python3.8/dist-packages/datasets/builder.py](https://localhost:8080/#) in __init__(self, cache_dir, config_name, hash, base_path, info, features, use_auth_token, repo_id, data_files, data_dir, name, **config_kwargs)
    298 
    299         if data_files is not None and not isinstance(data_files, DataFilesDict):
--> 300             data_files = DataFilesDict.from_local_or_remote(
    301                 sanitize_patterns(data_files), base_path=base_path, use_auth_token=use_auth_token
    302             )

[/usr/local/lib/python3.8/dist-packages/datasets/data_files.py](https://localhost:8080/#) in from_local_or_remote(cls, patterns, base_path, allowed_extensions, use_auth_token)
    794         for key, patterns_for_key in patterns.items():
    795             out[key] = (
--> 796                 DataFilesList.from_local_or_remote(
    797                     patterns_for_key,
    798                     base_path=base_path,

[/usr/local/lib/python3.8/dist-packages/datasets/data_files.py](https://localhost:8080/#) in from_local_or_remote(cls, patterns, base_path, allowed_extensions, use_auth_token)
    762     ) -> "DataFilesList":
    763         base_path = base_path if base_path is not None else str(Path().resolve())
--> 764         data_files = resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions)
    765         origin_metadata = _get_origin_metadata_locally_or_by_urls(data_files, use_auth_token=use_auth_token)
    766         return cls(data_files, origin_metadata)

[/usr/local/lib/python3.8/dist-packages/datasets/data_files.py](https://localhost:8080/#) in resolve_patterns_locally_or_by_urls(base_path, patterns, allowed_extensions)
    357     data_files = []
    358     for pattern in patterns:
--> 359         if is_remote_url(pattern):
    360             data_files.append(Url(pattern))
    361         else:

[/usr/local/lib/python3.8/dist-packages/datasets/utils/file_utils.py](https://localhost:8080/#) in is_remote_url(url_or_filename)
     62 
     63 def is_remote_url(url_or_filename: str) -> bool:
---> 64     parsed = urlparse(url_or_filename)
     65     return parsed.scheme in ("http", "https", "s3", "gs", "hdfs", "ftp")
     66 

[/usr/lib/python3.8/urllib/parse.py](https://localhost:8080/#) in urlparse(url, scheme, allow_fragments)
    373     Note that we don't break the components up in smaller bits
    374     (e.g. netloc is a single string) and we don't expand % escapes."""
--> 375     url, scheme, _coerce_result = _coerce_args(url, scheme)
    376     splitresult = urlsplit(url, scheme, allow_fragments)
    377     scheme, netloc, url, query, fragment = splitresult

[/usr/lib/python3.8/urllib/parse.py](https://localhost:8080/#) in _coerce_args(*args)
    125     if str_input:
    126         return args + (_noop,)
--> 127     return _decode_args(args) + (_encode_result,)
    128 
    129 # Result objects are more helpful than simple tuples

[/usr/lib/python3.8/urllib/parse.py](https://localhost:8080/#) in _decode_args(args, encoding, errors)
    109 def _decode_args(args, encoding=_implicit_encoding,
    110                        errors=_implicit_errors):
--> 111     return tuple(x.decode(encoding, errors) if x else '' for x in args)
    112 
    113 def _coerce_args(*args):

[/usr/lib/python3.8/urllib/parse.py](https://localhost:8080/#) in <genexpr>(.0)
    109 def _decode_args(args, encoding=_implicit_encoding,
    110                        errors=_implicit_errors):
--> 111     return tuple(x.decode(encoding, errors) if x else '' for x in args)
    112 
    113 def _coerce_args(*args):

AttributeError: 'PosixPath' object has no attribute 'decode'
```

@mariosasko Should I create a new issue? 

@mariosasko I would like to take this issue up. 

@avinashsai Hi, I've assigned you the issue.

@tranhd95 Yes, feel free to report this in a new issue.

@avinashsai Are you still working on this? If not I would like to give it a try.

@mariosasko I would like to take this issue up!

Hi @tranhd95 @mariosasko ,I hope you all are doing well.

I am interested in this issue, is this still open and unresolved ?

Thanks and Regards

@mariosasko I would like to take this issue up.

Hi @mariosasko, I’d like to work on this issue. I’ll start by replacing List with Sequence in relevant function signatures and ensure type checking passes. Let me know if there are any specific files to prioritize.

Hi @mariosasko, can I please work on this issue?

Hi, I’m new to this repo and would love to work on this issue. Is it still available?

Hi! I’d like to work on this issue. 
Please let me know if it’s okay to proceed or if there are any guidelines I should follow.
Thanks!



I've opened PR #8112 which covers the broader codebase — arrow_dataset.py, iterable_dataset.py, combine.py, and dataset_dict.py. Happy to extend to other files or make adjustments based on feedback.



I’ve created PR #8142 for this issue.

This is my first attempt at contributing to open source, so I apologize in advance for any mistakes or anything I may have missed.

I’d really appreciate any feedback, suggestions, or advice for improvement. I’m happy to learn and make changes if needed.

Thank you!