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chess_studies.py

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+
+"""Chess studies and annotated games from the top lichess studies and from https://www.angelfire.com/games3/smartbridge/"""
+
+
+import os
+import pandas as pd
+
+import datasets
+
+
+_CITATION = """TO COME."""
+
+_DESCRIPTION = """\
+Chess studies and annotated games from the top lichess studies and from https://www.angelfire.com/games3/smartbridge/
+This dataset consists of annotated chess games from several sources and aggregated into a single dataset. It is intended 
+to train language models to generate chess games and studies.
+"""
+
+_HOMEPAGE = ""
+
+_LICENSE = "CC0"
+
+_URLS = {
+    "lichess": "lichess_studies.csv",
+    "others": "others.csv",
+}
+
+
+class ChessStudies(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="lichess", version=VERSION, description="Top studies scrapped from the lichess website"),
+        datasets.BuilderConfig(name="others", version=VERSION, description="Studies aggregated from other sources"),
+    ]
+
+    DEFAULT_CONFIG_NAME = "lichess"
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "text": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = _URLS[self.config.name]
+        data_dir = dl_manager.download(urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir),
+                    "split": "train",
+                },
+            ),
+        ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath, split):
+        df = pd.read_csv(filepath)
+        for i, row in df.iterrows():
+            yield i, {
+                "text": row['text'],
+            }