Create bbc_alltime.py

bbc_alltime.py

@@ -0,0 +1,108 @@
+import datasets
+import json
+
+_CITATION = """\
+@misc{li2023estimating,
+      title={Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation}, 
+      author={Yucheng Li},
+      year={2023},
+      eprint={2309.10677},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+This dataset contains BBC News articles from 2017 to 2022. The articles are arraged by month. Access the specific month by using the format "YYYY-MM" as config. Such as load_dataset("RealTimeData/bbc_alltime", "2021-1").
+"""
+
+_HOMEPAGE = "https://github.com/liyucheng09/Contamination_Detector"
+
+_TIMES = ["2017-10", "2017-11", "2017-12", "2017-1", "2017-2", "2017-3", "2017-4", "2017-5", "2017-6", "2017-7", "2017-8", "2017-9", "2018-10", "2018-11", "2018-12", "2018-1", "2018-2", "2018-3", "2018-4", "2018-5", "2018-6", "2018-7", "2018-8", "2018-9", "2019-10", "2019-11", "2019-12", "2019-1", "2019-2", "2019-3", "2019-4", "2019-5", "2019-6", "2019-7", "2019-8", "2019-9", "2020-10", "2020-11", "2020-12", "2020-1", "2020-2", "2020-3", "2020-4", "2020-5", "2020-6", "2020-7", "2020-8", "2020-9", "2021-10", "2021-11", "2021-12", "2021-1", "2021-2", "2021-3", "2021-4", "2021-5", "2021-6", "2021-7", "2021-8", "2021-9", "2022-10", "2022-11", "2022-12", "2022-1", "2022-2", "2022-3", "2022-4", "2022-5", "2022-6", "2022-7", "2022-8", "2022-9", "all"]
+
+
+class Bbc_alltimes(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=time, version=datasets.Version("1.0.0"), description=f"BBC News articles published in the priod of {time}"
+        )
+        for time in _TIMES
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "title": datasets.Value("string"),
+                "published_date": datasets.Value("string"),
+                "authors": datasets.Value("string"),
+                "description": datasets.Value("string"),
+                "section": datasets.Value("string"),
+                "content": datasets.Value("string"),
+                "link": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        if self.config.name == "all":
+            times = _TIMES[:-1]
+            files = dl_manager.download_and_extract('all_articles.zip')
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={"files": files},
+                )
+            ]
+        else:
+            time = self.config.name
+            _URL = f"articles/{time}.json"
+            file = dl_manager.download(_URL)
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={"files": file},
+                )
+            ]
+
+    def _generate_examples(self, files):
+        """Yields examples."""
+        if self.config.name == "all":
+            assert isinstance(files, list)
+            for file in files:
+                time = file.strip('.json')
+                with open(file, encoding="utf-8") as f:
+                    data = json.load(f)
+                length = len(data['title'])
+                for i in range(length):
+                    yield f'{time}-{i}', {
+                        "title": data['title'][i],
+                        "published_date": data['published_date'][i],
+                        "authors": data['authors'][i],
+                        "description": data['description'][i],
+                        "section": data['section'][i],
+                        "content": data['content'][i],
+                        "link": data['link'][i],
+                    }
+        else:
+            assert isinstance(files, str)
+            time = self.config.name
+            with open(files, encoding="utf-8") as f:
+                data = json.load(f)
+            length = len(data['title'])
+            for i in range(length):
+                yield f'{time}-{i}', {
+                    "title": data['title'][i],
+                    "published_date": data['published_date'][i],
+                    "authors": data['authors'][i],
+                    "description": data['description'][i],
+                    "section": data['section'][i],
+                    "content": data['content'][i],
+                    "link": data['link'][i],
+                }