Support Zstandard compressed files
> What if people want to run some tests without having zstandard ?
> Usually what we do is add a decorator @require_zstandard for example

@lhoestq I think I'm missing something here...

Tests are a *development* tool (to ensure we deliver a good quality lib), not something we offer to the end users of the lib. Users of the lib just `pip install datasets` and no tests are delivered with the lib (`tests` directory is outside the `src` code dir). 

On the contrary, developers (contributors) of the lib do need to be able to run tests (TDD). And because of that, they are required to install datasets differently: `pip install -e .[dev]`, so that all required developing (and testing) dependencies are properly installed (included `zstandard`).

Apart from `zsatandard`, there are many other dev/test required dependencies for running tests, and we do not have a `@require_toto` for each and every of these dependencies in our tests: 
- `pytest` and `absl-py` (they are not dependencies in install_requires, but only in TEST_REQUIRE extras_require), 
- `boto3` (in test_filesystem.py), 
- `seqeval` (in test_metric_common.py), 
- `bs4` (used by eli5 and tested in test_hf_gcp.py)
- ...

So IMHO, to run tests you should previously install datasets with dev or tests dependencies: either `pip install -e .[dev]` or `pip install -e .[tests]` (the latter to be used in CI testing-only part of the development cycle). And the tests should be written accordingly, assuming all tests dependencies are installed. Hi !
I was saying that because the other dependencies you mentioned are only required for _some_ tests. While here zstd is required for _all_ tests since it's imported in the conftest.py
Feel free to keep it as it is right now, or maybe move the fixture to test_file_utils.py to allow users without zstd to run tests for their builders, dataset card etc. without issues Thank you ! I think we can merge now @lhoestq does this mean that the pile could have streaming support in the future? Afaik streaming doesnt support zstandard compressed type > @lhoestq does this mean that the pile could have streaming support in the future? Afaik streaming doesnt support zstandard compressed type

just for reference, i tried to stream one of the `.zst` files from [the pile](https://the-eye.eu/public/AI/pile/) using

```python
data_files = ["https://the-eye.eu/public/AI/pile/train/00.jsonl.zst"]
streamed_dataset = load_dataset('json', split='train', data_files=data_files, streaming=True)
```

and got the following error:

```
Using custom data configuration default-4e71acadc389c254
---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
/tmp/ipykernel_1187680/10848115.py in <module>
      1 data_files = ["https://the-eye.eu/public/AI/pile/train/00.jsonl.zst"]
      2 
----> 3 streamed_dataset = load_dataset('json', split='train', data_files=data_files, streaming=True)
      4 

~/miniconda3/envs/hf/lib/python3.8/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, script_version, use_auth_token, task, streaming, **config_kwargs)
    835         # this extends the open and os.path.join functions for data streaming
    836         extend_module_for_streaming(builder_instance.__module__, use_auth_token=use_auth_token)
--> 837         return builder_instance.as_streaming_dataset(
    838             split=split,
    839             use_auth_token=use_auth_token,

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/builder.py in as_streaming_dataset(self, split, base_path, use_auth_token)
    922             data_dir=self.config.data_dir,
    923         )
--> 924         splits_generators = {sg.name: sg for sg in self._split_generators(dl_manager)}
    925         # By default, return all splits
    926         if split is None:

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/packaged_modules/json/json.py in _split_generators(self, dl_manager)
     50         if not self.config.data_files:
     51             raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
---> 52         data_files = dl_manager.download_and_extract(self.config.data_files)
     53         if isinstance(data_files, (str, list, tuple)):
     54             files = data_files

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in download_and_extract(self, url_or_urls)
    140 
    141     def download_and_extract(self, url_or_urls):
--> 142         return self.extract(self.download(url_or_urls))

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in extract(self, path_or_paths)
    115 
    116     def extract(self, path_or_paths):
--> 117         urlpaths = map_nested(self._extract, path_or_paths, map_tuple=True)
    118         return urlpaths
    119 

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/py_utils.py in map_nested(function, data_struct, dict_only, map_list, map_tuple, map_numpy, num_proc, types)
    202         num_proc = 1
    203     if num_proc <= 1 or len(iterable) <= num_proc:
--> 204         mapped = [
    205             _single_map_nested((function, obj, types, None, True))
    206             for obj in utils.tqdm(iterable, disable=disable_tqdm)

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/py_utils.py in <listcomp>(.0)
    203     if num_proc <= 1 or len(iterable) <= num_proc:
    204         mapped = [
--> 205             _single_map_nested((function, obj, types, None, True))
    206             for obj in utils.tqdm(iterable, disable=disable_tqdm)
    207         ]

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/py_utils.py in _single_map_nested(args)
    141     # Singleton first to spare some computation
    142     if not isinstance(data_struct, dict) and not isinstance(data_struct, types):
--> 143         return function(data_struct)
    144 
    145     # Reduce logging to keep things readable in multiprocessing with tqdm

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _extract(self, urlpath)
    119 
    120     def _extract(self, urlpath):
--> 121         protocol = self._get_extraction_protocol(urlpath)
    122         if protocol is None:
    123             # no extraction

~/miniconda3/envs/hf/lib/python3.8/site-packages/datasets/utils/streaming_download_manager.py in _get_extraction_protocol(self, urlpath)
    137         elif path.endswith(".zip"):
    138             return "zip"
--> 139         raise NotImplementedError(f"Extraction protocol for file at {urlpath} is not implemented yet")
    140 
    141     def download_and_extract(self, url_or_urls):

NotImplementedError: Extraction protocol for file at https://the-eye.eu/public/AI/pile/train/00.jsonl.zst is not implemented yet
```

i'm not sure whether @Shashi456 is referring to a fundamental limitation with "streaming" zstandard compression files or simply that we need to support the protocol in the streaming api of `datasets`

 @lewtun our streaming mode patches the Python `open` function. I could have a look tomorrow if it is easily implementable for this case. @lewtun, I have tested and yes, it is easily implementable. I've created a draft Pull Request with an implementation proposal: #2786. thanks a lot @albertvillanova - now i can stream the pile :)
Close #2572.

cc: @thomwolf 