backup

app.py

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+from datasets import load_dataset
+import gradio as gr
+import random
+import requests
+from PIL import Image
+from io import BytesIO
+
+# Load the dataset
+steam_dataset = load_dataset("taesiri/SteamCommunityImagesDailyDumpy")
+
+# Convert to pandas once and keep it in memory
+df = steam_dataset["train"].to_pandas()
+game_counts = df["game_name"].value_counts().to_dict()
+game_list = list(game_counts.keys())
+
+# Cache for storing processed game data
+game_cache = {}
+
+
+def get_random_image(game_name):
+    # Lazy loading: only process game data when first requested
+    if game_name not in game_cache:
+        game_cache[game_name] = df[df["game_name"] == game_name]["image_url"].tolist()
+
+    # Get random image URL from cached list
+    random_url = random.choice(game_cache[game_name])
+
+    # Download and return image
+    response = requests.get(random_url)
+    img = Image.open(BytesIO(response.content))
+    return img, f"Total images available for {game_name}: {game_counts[game_name]}"
+
+
+# Create Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Steam Game Image Preview")
+
+    with gr.Row():
+        game_dropdown = gr.Dropdown(
+            choices=game_list,
+            label="Select a Game",
+            info="Choose a game to see random screenshots",
+        )
+
+    with gr.Row():
+        show_btn = gr.Button("Show Random Image")
+
+    with gr.Column():
+        image_output = gr.Image(type="pil", label="Random Game Image")
+        stats_output = gr.Textbox(label="Statistics")
+
+    show_btn.click(
+        fn=get_random_image,
+        inputs=[game_dropdown],
+        outputs=[image_output, stats_output],
+    )
+
+demo.launch()