Builder created

test_builder.py

@@ -0,0 +1,94 @@
+
+import os
+import textwrap
+from textwrap import TextWrapper
+import datasets
+import pyarrow.parquet as pq
+
+_URLS = {
+    "original_text": "./original_text",
+    "unlabeled_sentences": "./unlabeled_sentences"
+}
+
+_metadata = {
+    "citation": """\
+    @InProceedings{
+        huggingface:dataset,
+        title = {Paraguay Legislation Dataset},
+        author={Peres, Fernando; Costa, Victor},
+        year={2023}
+    }
+    """,
+
+    "description": "Dataset for researching.",
+
+    "homepage": "https://www.leyes.com.py/",
+
+    "license": "apache-2.0",
+}
+
+
+class TestBuilder(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="raw_text",
+            version=VERSION,
+            description="desc raw text",
+        ),
+
+        datasets.BuilderConfig(
+            name="unlabeled_sentences",
+            version=VERSION,
+            description="desc unlabeled",
+        ),
+    ]
+
+    def _info(self):
+
+        features = None
+        if self.config.name == "raw_text":
+
+            features = datasets.Features(
+                {
+                    "id": datasets.Value(dtype="int64"),
+                    "text": datasets.Value(dtype="string"),
+                }
+            )
+
+        if self.config.name == "unlabeled_sentences":
+            features = features = datasets.Features(
+                {
+                    "id": datasets.Value(dtype="int64"),
+                    "text_2": datasets.Value(dtype="string"),
+                    "note": datasets.Value(dtype="string"),
+                }
+            )
+
+        return datasets.DatasetInfo(
+            builder_name=self.config.name,
+            description="description xxxxxxxxxxxxxxx",
+            features=features,
+            homepage=_metadata["homepage"],
+            license=_metadata["license"],
+            citation=_metadata["citation"],
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = _URLS
+
+        filepaths = dl_manager.download_and_extract(urls_to_download)
+
+        return datasets.SplitGenerator(
+            name=datasets.Split.TRAIN,
+            gen_kwargs={"filepath": filepaths},
+        )
+
+    def _generate_examples(self, filepath):
+        pq_table = pq.read_table(filepath)
+        for i in range(len(pq_table)):
+            yield i, {
+                col_name: pq_table[col_name][i].as_py()
+                for col_name in pq_table.column_names
+            }