Create app.py

app.py

@@ -0,0 +1,79 @@
+import gradio as gr
+import pandas as pd
+import time
+
+
+# ── Demo data source ──────────────────────────────────────────────────────────
+# Replace this with your real data source (DB query, API call, model output…)
+SAMPLE_ROWS = [
+    {"Name": "Alpha",   "Value": 10,  "Status": "✅ Done"},
+    {"Name": "Beta",    "Value": 25,  "Status": "✅ Done"},
+    {"Name": "Gamma",   "Value": 15,  "Status": "✅ Done"},
+    {"Name": "Delta",   "Value": 42,  "Status": "✅ Done"},
+    {"Name": "Epsilon", "Value": 8,   "Status": "✅ Done"},
+    {"Name": "Zeta",    "Value": 33,  "Status": "✅ Done"},
+    {"Name": "Eta",     "Value": 19,  "Status": "✅ Done"},
+    {"Name": "Theta",   "Value": 56,  "Status": "✅ Done"},
+]
+
+
+# ── Generator: yields growing DataFrame on each step ─────────────────────────
+def stream_dataframe(query: str, delay: float):
+    """
+    Streams rows into a gr.Dataframe one-by-one.
+    Yields the *full accumulated* DataFrame each iteration so Gradio
+    replaces the table contents live.
+    """
+    cols = ["Name", "Value", "Status"]
+    df = pd.DataFrame(columns=cols)
+    yield df, "⏳ Starting…"
+
+    source = [r for r in SAMPLE_ROWS if query.lower() in r["Name"].lower()] \
+             if query.strip() else SAMPLE_ROWS
+
+    if not source:
+        yield df, "⚠️ No results found."
+        return
+
+    for i, row in enumerate(source, 1):
+        time.sleep(delay)
+        df = pd.concat([df, pd.DataFrame([row])], ignore_index=True)
+        yield df, f"⏳ Loaded {i} / {len(source)} rows…"
+
+    yield df, f"✅ Complete — {len(df)} rows loaded."
+
+
+# ── Gradio UI ─────────────────────────────────────────────────────────────────
+with gr.Blocks(title="Streaming DataFrame Demo") as demo:
+    gr.Markdown("# 📊 Streaming DataFrame\nRows populate live as data arrives.")
+
+    with gr.Row():
+        query_box = gr.Textbox(
+            label="Filter by name (leave blank for all)",
+            placeholder="e.g. Alpha",
+            scale=4,
+        )
+        delay_slider = gr.Slider(
+            minimum=0.1, maximum=2.0, value=0.6, step=0.1,
+            label="Row delay (s)",
+            scale=1,
+        )
+
+    run_btn = gr.Button("▶ Stream Data", variant="primary")
+
+    status = gr.Textbox(label="Status", interactive=False)
+    table = gr.Dataframe(
+        headers=["Name", "Value", "Status"],
+        datatype=["str", "number", "str"],
+        interactive=False,
+        wrap=True,
+    )
+
+    run_btn.click(
+        fn=stream_dataframe,
+        inputs=[query_box, delay_slider],
+        outputs=[table, status],
+    )
+
+if __name__ == "__main__":
+    demo.launch()