feat: forgot to include script lol

biodataome.py

@@ -0,0 +1,77 @@
+#%%
+import datasets
+from datasets.tasks import TaskTemplate
+from sklearn.model_selection import train_test_split
+import pandas as pd
+import csv
+import os
+
+_ORIGIN = "http://dataome.mensxmachina.org/"
+_CITATION = """ """
+
+class BioDataome(datasets.GeneratorBasedBuilder):
+    METADATA = pd.read_csv(f"biodataome_data.csv")
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name=i, 
+                               version=datasets.Version("1.0.0"), 
+                               description=d)
+        for i, d in zip(
+            METADATA["GSE"], 
+            METADATA["Disease"],
+            )
+    ]
+
+    print(BUILDER_CONFIGS)
+
+    def _info(self) -> datasets.DatasetInfo:
+        print(BioDataome.BUILDER_CONFIGS)
+        return datasets.DatasetInfo(
+            description="",
+            citation=_CITATION,
+            homepage=_ORIGIN,
+            license="",
+        )
+
+    def _split_generators(self, dl_manager):
+        gse = self.config.name
+        url = self.METADATA[self.METADATA["GSE"] == gse]["Datapath"].values[0]
+        metadata_url = self.METADATA[self.METADATA["GSE"] == gse]["DataAnnot"].values[0] 
+        data: datasets.download.DownloadManager = dl_manager.download(url)
+        metadata: datasets.download.DownloadManager = dl_manager.download(metadata_url)
+
+        new_name = os.path.dirname(data) + "/" + os.path.basename(data).split(".")[0] + "_processed.csv"
+
+        df = pd.read_csv(data, index_col=0)
+        df = df.T
+        df.to_csv(new_name, index=False)
+
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": new_name, "metadata": metadata}),
+        ]
+    
+    def _generate_examples(self, filepath, metadata):
+        print(filepath)
+        with open(filepath, "r") as f:
+            f_header = f.readline()
+            with open(metadata, "r") as m:
+                m_header = m.readline()
+                for key, (row, meta) in enumerate(zip(f, m)):
+                    metadata = csv.reader([meta], quotechar='"').__next__()
+                    row = row.split(",")
+                    yield key, {
+                        "data":
+                        {
+                            i.strip(): j for i, j in zip(f_header.split(","), row)
+                        },
+                        "metadata":
+                        {
+                            i.strip(): j for i, j in zip(m_header.split(","), metadata)
+                        }
+                    }
+
+#%%
+if __name__ == "__main__":
+    ds = datasets.load_dataset("./load_script.py", "GSE17933")
+    ds['train'][0]
+
+# %%