Modify to be nested

regulatory_comments.py

@@ -35,7 +35,7 @@ _HOMEPAGE = "https://www.regulations.gov/"
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URLS = {"url": "https://huggingface.co/datasets/ro-h/regulatory_comments/raw/main/temp.csv"
+_URLS = {"url": "https://huggingface.co/datasets/ro-h/regulatory_comments/raw/main/docket_comments.json"
 
 }
 
@@ -62,71 +62,75 @@ class RegComments(datasets.GeneratorBasedBuilder):
     #            comment_text = comment_data['data']['attributes']['comment'],
     #            commenter_name = comment_data['data']['attributes'].get('firstName', '') + " " + comment_data['data']['attributes'].get('lastName', '')
     #        ) #use pandas
-
+    
     def _info(self):
-        print("info called")
-        features = datasets.Features(
-              {"docket_agency": datasets.Value("string"),
-               "docket_title": datasets.Value("string"),
-               "docket_date": datasets.Value("string"),
-               "comment_id": datasets.Value("string"),
-               "comment_date": datasets.Value("string"),
-               "comment_url": datasets.Value("string"),
-               "comment_title": datasets.Value("string"),
-               "commenter_name": datasets.Value("string"),
-               "comment_length": datasets.Value("int64"),
-               "comment_text": datasets.Value("string"),
-              }
-          )
-        
-        
+        features = datasets.Features({
+            "id": datasets.Value("string"),
+            "title": datasets.Value("string"),
+            "context": datasets.Value("string"),
+            "comments": datasets.Sequence({
+                "text": datasets.Value("string"),
+                "comment_id": datasets.Value("string"),
+                "comment_url": datasets.Value("string"),
+                "comment_date": datasets.Value("string"),
+                "comment_title": datasets.Value("string"),
+                "commenter_fname": datasets.Value("string"),
+                "commenter_lname": datasets.Value("string"),
+                "comment_length": datasets.Value("int32")
+            })
+        })
+
         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 documentaxtion
+            features=features,
             homepage=_HOMEPAGE
         )
 
     def _split_generators(self, dl_manager):
         print("split generators called")
-        # 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
+        # URLS should point to where your dataset is located
         urls = _URLS["url"]
-        data_dir = dl_manager.download_and_extract(urls) 
+        data_dir = dl_manager.download_and_extract(urls)
         print("urls accessed")
         print(data_dir)
-       #print("File path:", os.path.join(data_dir, "train.csv"))
-        return [datasets.SplitGenerator(name=datasets.Split.TRAIN,
-                # These kwargs will be passed to _generate_examples
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "filepath": data_dir,
-                    #"split": "train",
-                },),]
+                    "filepath": os.path.join(data_dir, 'docket_comments.json'),
+                },
+            ),
+        ]
     
-    #method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, filepath):
-        print("generate examples called")
-        with open(filepath, encoding="utf-8") as f:
-            reader = csv.DictReader(f)
-            for key, row in enumerate(reader):
+        """This function returns the examples in the raw (text) form."""
+        logger.info("generating examples from = %s", filepath)
+        key = 0
+        with open(filepath, 'r', encoding='utf-8') as f:
+            data = json.load(f)
+            for docket in data:
+                docket_id = docket["id"]
+                docket_title = docket["title"]
+                docket_context = docket["context"]
+                comments = []
+                for comment in docket["comments"]:
+                    comment_data = {
+                        "text": comment["text"],
+                        "comment_id": comment["comment_id"],
+                        "comment_url": comment["comment_url"],
+                        "comment_date": comment["comment_date"],
+                        "comment_title": comment["comment_title"],
+                        "commenter_fname": comment["commenter_fname"],
+                        "commenter_lname": comment["commenter_lname"],
+                        "comment_length": comment["comment_length"]
+                    }
+                    comments.append(comment_data)
+
                 yield key, {
-                    "docket_agency": row["docket_agency"],
-                    "docket_title": row["docket_title"],
-                    "docket_date": row["docket_date"],
-                    "comment_id": row["comment_id"],
-                    "comment_date": row["comment_date"],
-                    "comment_url": row["comment_url"],
-                    "comment_title": row["comment_title"],
-                    "commenter_name": row["commenter_name"],
-                    "comment_length": int(row["comment_length"]),
-                    "comment_text": row["comment_text"],
-                }
+                    "id": docket_id,
+                    "title": docket_title,
+                    "context": docket_context,
+                    "comments": comments
+                }
+                key += 1