reformat and fix the generator

zenodo.py

@@ -12,52 +12,12 @@ This dataset is for downloading a Zenodo dataset without extra packages.
 """
 
 
-
-
 class NewDataset(datasets.GeneratorBasedBuilder):
     """This dataset downloads a zenodo dataset and returns its path."""
 
     VERSION = datasets.Version("1.1.0")
 
-    # This is an example of a dataset with multiple configurations.
-    # If you don't want/need to define several sub-sets in your dataset,
-    # just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
-
-    # If you need to make complex sub-parts in the datasets with configurable options
-    # You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
-    # BUILDER_CONFIG_CLASS = MyBuilderConfig
-
-    # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'first_domain')
-    # data = datasets.load_dataset('my_dataset', 'second_domain')
-    # BUILDER_CONFIGS = [
-    #     datasets.BuilderConfig(name="first_domain", version=VERSION, description="This part of my dataset covers a first domain"),
-    #     datasets.BuilderConfig(name="second_domain", version=VERSION, description="This part of my dataset covers a second domain"),
-    # ]
-
-    # DEFAULT_CONFIG_NAME = "first_domain"  # It's not mandatory to have a default configuration. Just use one if it make sense.
-
     def _info(self):
-        # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
-        # if self.config.name == "first_domain":  # This is the name of the configuration selected in BUILDER_CONFIGS above
-        #     features = datasets.Features(
-        #         {
-        #             "sentence": datasets.Value("string"),
-        #             "option1": datasets.Value("string"),
-        #             "answer": datasets.Value("string")
-        #             # These are the features of your dataset like images, labels ...
-        #         }
-        #     )
-        # else:  # This is an example to show how to have different features for "first_domain" and "second_domain"
-        #     features = datasets.Features(
-        #         {
-        #             "sentence": datasets.Value("string"),
-        #             "option2": datasets.Value("string"),
-        #             "second_domain_answer": datasets.Value("string")
-        #             # These are the features of your dataset like images, labels ...
-        #         }
-        #     )
-
         features = datasets.Features(
             {
                 "path": datasets.Value("string"),
@@ -65,28 +25,11 @@ class NewDataset(datasets.GeneratorBasedBuilder):
         )
 
         return datasets.DatasetInfo(
-            # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
-            # This defines the different columns of the dataset and their types
-            features=features,  # Here we define them above because they are different between the two configurations
-            # If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and
-            # specify them. They'll be used if as_supervised=True in builder.as_dataset.
-            # supervised_keys=("sentence", "label"),
-            # Homepage of the dataset for documentation
-            # homepage=_HOMEPAGE,
-            # License for the dataset if available
-            # license=_LICENSE,
-            # Citation for the dataset
-            # citation=_CITATION,
+            features=features,
         )
 
     def _split_generators(self, dl_manager):
-        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
-        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
-
-        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
-        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
-        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         zenodo_id = self.config.name.split("_")[0]
         filename = self.config.name.split("_")[1]
 
@@ -102,10 +45,5 @@ class NewDataset(datasets.GeneratorBasedBuilder):
             ),
         ]
 
-    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, filepath):
-        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
-        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
-        
-        yield "path", filepath
-        
+        yield 0, {"path": filepath}