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Dagster/API_R&D/dagster_adapter/dagster_pipeline.py

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+from dagster import op, job, In, Out
+import pysera
+from api.execution_context import ExecutionContext
+from api.assets import Asset
+
+
+@op(out={"image_input": Out(str), "mask_input": Out(str)})
+def image_reader_op():
+    image_input = "data/sample/images"
+    mask_input  = "data/sample/masks"
+    return {"image_input": image_input, "mask_input": mask_input}
+
+
+@op(ins={"image_input": In(str), "mask_input": In(str)}, out={"features": Out(Asset)})
+def pysera_extractor_op(image_input, mask_input):
+    output_dir = "results"
+
+    result = pysera.process_batch(
+        image_input=image_input,
+        mask_input=mask_input,
+        output_path=output_dir,
+        num_workers="auto",
+        enable_parallelism=True,
+        apply_preprocessing=True,
+        categories="all",
+        dimensions="1st,2_5d,3d",
+        feature_value_mode="REAL_VALUE",
+        extraction_mode="handcrafted_feature",
+        report="info",
+    )
+
+    df = result.get("features_extracted")
+    return {"features": Asset(df, "pysera_features_df")}
+
+@op(ins={"features": In(Asset)}, out={"csv_path": Out(Asset)})
+def csv_writer_op(features):
+    import os
+    import csv
+    from datetime import datetime
+
+    df = features.data
+    rows = []
+    if hasattr(df, "iterrows"):
+        for _, row in df.iterrows():
+            rows.append({"name": row[0], "value": row[1]})
+
+    os.makedirs("results", exist_ok=True)
+    ts = datetime.now().strftime("%Y%m%d_%H%M%S")
+    path = os.path.join("results", f"features_dagster_{ts}.csv")
+
+    with open(path, "w", newline="", encoding="utf-8") as f:
+        w = csv.writer(f)
+        w.writerow(["name", "value"])
+        for r in rows:
+            w.writerow([r["name"], r["value"]])
+
+    return {"csv_path": Asset(path, "csv_path")}
+
+@job
+def radiuma_pysera_job():
+    image_mask = image_reader_op()
+    feats = pysera_extractor_op(
+        image_input=image_mask["image_input"],
+        mask_input=image_mask["mask_input"],
+    )
+    csv_writer_op(features=feats["features"])