diff --git a/examples/polars_recipe.py b/examples/polars_recipe.py
new file mode 100644
index 0000000..14ed1c0
--- /dev/null
+++ b/examples/polars_recipe.py
@@ -0,0 +1,131 @@
+#!/usr/bin/env python3
+"""Small Polars recipe for Generated Gallery JSONL.GZ exports.
+
+Usage:
+  python examples/polars_recipe.py
+  python examples/polars_recipe.py https://generatedgallery.com/index/generated-gallery.prompts.jsonl.gz cinematic 5 10000
+"""
+import gzip
+import io
+import json
+import sys
+import urllib.request
+from pathlib import Path
+
+import polars as pl
+
+DEFAULT_URL = "https://generatedgallery.com/index/generated-gallery.prompts.jsonl.gz"
+DEFAULT_LABEL = "cinematic"
+DEFAULT_SAMPLE_SIZE = 5
+DEFAULT_LIMIT = 10000
+
+
+def open_stream(location: str):
+    if location.startswith(("http://", "https://")):
+        req = urllib.request.Request(
+            location,
+            headers={"User-Agent": "generatedgallery-polars-recipe/1.0"},
+        )
+        with urllib.request.urlopen(req, timeout=60) as response:
+            raw = response.read()
+        bio = io.BytesIO(raw)
+        if location.endswith(".gz"):
+            return io.TextIOWrapper(gzip.GzipFile(fileobj=bio), encoding="utf-8")
+        return io.TextIOWrapper(bio, encoding="utf-8")
+
+    path = Path(location)
+    if path.suffix == ".gz":
+        return gzip.open(path, "rt", encoding="utf-8")
+    return path.open("r", encoding="utf-8")
+
+
+def load_rows(location: str, limit: int):
+    rows = []
+    with open_stream(location) as handle:
+        for line in handle:
+            line = line.strip()
+            if not line:
+                continue
+            record = json.loads(line)
+            labels = record.get("labels", {})
+            generation = record.get("generation", {})
+            source = record.get("source", {})
+            rows.append({
+                "id": record.get("id"),
+                "styles": labels.get("styles") or [],
+                "subjects": labels.get("subjects") or [],
+                "model_family": labels.get("model_family"),
+                "prompt": generation.get("prompt") or "",
+                "source_url": source.get("url") or record.get("url"),
+            })
+            if len(rows) >= limit:
+                break
+    return pl.DataFrame(rows)
+
+
+def print_list_top(df: pl.DataFrame, field: str, label: str):
+    top = (
+        df.select(pl.col(field).explode().drop_nulls().alias("value"))
+        .group_by("value")
+        .len()
+        .sort("len", descending=True)
+        .head(10)
+    )
+    print(f"\nTop {label}:")
+    for row in top.iter_rows(named=True):
+        print(f"- {row['value']}: {row['len']}")
+
+
+def print_model_top(df: pl.DataFrame):
+    top = (
+        df.select(pl.col("model_family"))
+        .drop_nulls()
+        .group_by("model_family")
+        .len()
+        .sort("len", descending=True)
+        .head(10)
+    )
+    print("\nTop model families:")
+    for row in top.iter_rows(named=True):
+        print(f"- {row['model_family']}: {row['len']}")
+
+
+def print_samples(df: pl.DataFrame, label: str, sample_size: int):
+    sample = (
+        df.filter(
+            pl.col("styles").list.contains(label)
+            | pl.col("subjects").list.contains(label)
+            | (pl.col("model_family") == label)
+        )
+        .select("prompt", "source_url")
+        .head(sample_size)
+    )
+    print(f"\nSample rows for label '{label}':")
+    if sample.height == 0:
+        print("- no rows matched")
+        return
+    for row in sample.iter_rows(named=True):
+        prompt = row["prompt"].replace("\n", " ").strip()
+        if len(prompt) > 180:
+            prompt = f"{prompt[:177]}..."
+        print(f"- prompt: {prompt}")
+        print(f"  source: {row['source_url']}")
+
+
+def main():
+    location = sys.argv[1] if len(sys.argv) > 1 else DEFAULT_URL
+    label = sys.argv[2] if len(sys.argv) > 2 else DEFAULT_LABEL
+    sample_size = int(sys.argv[3]) if len(sys.argv) > 3 else DEFAULT_SAMPLE_SIZE
+    limit = int(sys.argv[4]) if len(sys.argv) > 4 else DEFAULT_LIMIT
+
+    df = load_rows(location, limit=limit)
+    print(f"Loaded {df.height} rows from: {location}")
+    print_list_top(df, "styles", "styles")
+    print_list_top(df, "subjects", "subjects")
+    print_model_top(df)
+    print_samples(df, label=label, sample_size=sample_size)
+    print("\nMedia rights note: upstream creators/platforms keep rights to source media. Verify rights before reuse.")
+
+
+if __name__ == "__main__":
+    main()