Application

app.py

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+import gradio as gr
+import subprocess
+import time
+import csv
+import os
+import pandas as pd
+
+TEST_SCRIPT = "./tests/test_script.sh"
+OUTPUT_CSV = "grading_results.csv"
+
+def run_cmd(cmd):
+    result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
+    return result.stdout.strip(), result.stderr.strip(), result.returncode
+
+def grade_single_image(image_name):
+    out, err, code = run_cmd(f"docker pull {image_name}")
+    if code != 0:
+        return {"docker_image": image_name, "score": 0, "remark": "Pull failed"}
+
+    out, err, code = run_cmd(f"docker run -d -p 5000:5000 {image_name}")
+    if code != 0:
+        return {"docker_image": image_name, "score": 0, "remark": "Run failed"}
+
+    container_id = out.strip()
+    time.sleep(3)
+
+    score_out, _, _ = run_cmd(f"bash {TEST_SCRIPT} {container_id}")
+    try:
+        score = int(score_out.strip())
+    except:
+        score = 0
+
+    run_cmd(f"docker stop {container_id}")
+    run_cmd(f"docker rm {container_id}")
+
+    return {"docker_image": image_name, "score": score, "remark": "Success" if score > 0 else "Failed Tests"}
+
+def grade_images(image_list):
+    results = []
+    for image_name in image_list.splitlines():
+        image_name = image_name.strip()
+        if not image_name:
+            continue
+        results.append(grade_single_image(image_name))
+
+    df = pd.DataFrame(results)
+    df.to_csv(OUTPUT_CSV, index=False)
+    return df, OUTPUT_CSV
+
+with gr.Blocks(theme=gr.themes.Soft()) as app:
+    gr.Markdown("## 🐳 Docker AutoGrader")
+    gr.Markdown("Enter Docker Hub image names (one per line) to automatically test and grade them.")
+
+    image_input = gr.Textbox(
+        label="Docker Image List",
+        placeholder="e.g.,\nramguru/student1_app:latest\nramguru/student2_app:v1",
+        lines=6
+    )
+
+    grade_button = gr.Button("Run AutoGrader 🚀")
+    output_table = gr.Dataframe(label="Grading Results", interactive=False)
+    output_file = gr.File(label="Download CSV Report")
+
+    grade_button.click(grade_images, inputs=image_input, outputs=[output_table, output_file])
+
+app.launch()