feat: backend cloud function code (#225)

data-analytics/minigolf-demo/backend/main.py

@@ -0,0 +1,152 @@
+import functions_framework
+import firebase_admin
+from firebase_admin import firestore
+from google.cloud import bigquery, storage
+from flask import make_response
+import base64
+import matplotlib.pyplot as plt
+from io import BytesIO
+from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
+import pandas as pd
+
+
+PROJECT_ID = ""
+BACKGROUND_IMAGE_BUCKET = ""
+VIDEO_BUCKET = ""
+BQ_DATASET = ""
+BQ_PREFIX = f"{PROJECT_ID}.{BQ_DATASET}"
+
+
+if not firebase_admin._apps:
+    firebase_admin.initialize_app(options={'projectId':f'{PROJECT_ID}'})
+
+
+db = firestore.client()
+bq_client = bigquery.Client()
+
+
+def get_user_status(user_id):
+    """Retrieves the status of a user from Firestore."""
+    user_doc_ref = db.collection('users_a').document(user_id)
+    user_doc = user_doc_ref.get()
+
+    if not user_doc.exists:
+        return None  # Return None if user not found
+
+    return user_doc.to_dict().get('status')
+
+
+def get_commentary(user_id):
+    """Fetches commentary for a user from BigQuery."""
+    query = f"""
+        SELECT commentary
+        FROM `{BQ_PREFIX}.commentary`
+        WHERE user_id = '{user_id}'
+    """
+    query_job = bq_client.query(query)
+    results = list(query_job)
+    return results[0].commentary if results else None
+
+
+def get_stat(user_id):
+    """Calculates and returns game statistics."""
+    query = f"SELECT * FROM {BQ_PREFIX}.tracking"
+    df = bq_client.query(query).to_dataframe()
+    last_frame_per_user = df.groupby('user_id')['frame_number'].transform(max)
+    df_filtered = df[df['frame_number'] == last_frame_per_user]
+    df_filtered = df_filtered[df_filtered['distance'] < 30]
+    user_shot_counts = df_filtered.groupby('user_id')['shot_number'].first()
+    user_shot_counts = user_shot_counts[user_shot_counts > 0]
+    shot_number_freq = user_shot_counts.value_counts()
+
+    # Selected user's number of shots
+    num_users = df['user_id'].nunique()
+    user_shots = user_shot_counts.get(user_id, 0)
+    average_shots_per_user = user_shot_counts.mean()
+
+    plt.figure(figsize=(8, 6))  # Set figure size
+    plt.xlim(0, 9)
+    barlist = plt.bar(shot_number_freq.index, shot_number_freq.values, color='#4285F4')
+    plt.xlabel('Number of Shots')
+    plt.ylabel('Number of Users')
+    plt.title('Distribution of Number of Shots per User')
+
+    if user_shots in shot_number_freq.index:
+        barlist[shot_number_freq.index.get_loc(user_shots)].set_color('#34A853')
+        plt.legend([barlist[shot_number_freq.index.get_loc(user_shots)]], [f'Shot Number of {user_id}'])
+
+    plt.xticks(range(9))
+
+    # Save the plot to a BytesIO object
+    fig = plt.gcf()
+    canvas = FigureCanvas(fig)
+    output = BytesIO()
+    canvas.print_png(output)
+    plt.close(fig)  # Close the figure to prevent memory leaks
+
+    # Encode the image in Base64
+    base64_encoded_image = base64.b64encode(output.getvalue()).decode('utf-8')
+
+    # --- Construct the stat dictionary ---
+    stat = {
+        'num_users': num_users,
+        'user_shots': user_shots,
+        'average_shots': f'{average_shots_per_user:.2f}',
+        'barchart': base64_encoded_image
+    }
+    return stat
+
+
+
+@functions_framework.http
+def get_user_data(request):
+    """HTTP Cloud Function.
+    Args:
+        request (flask.Request): The request object.
+        <https://flask.palletsprojects.com/en/1.1.x/api/#incoming-request-data>
+    Returns:
+        The response text, or any set of values that can be turned into a
+        Response object using `make_response`
+        <https://flask.palletsprojects.com/en/1.1.x/api/#flask.make_response>.
+    """
+
+    request_args = request.args
+    if request_args and 'userId' in request_args:
+        user_id = request_args['userId']
+    else:
+        return {'error': 'userId parameter is required'}, 400
+
+    try:
+        image_url = None
+        commentary = None
+        video_url = None
+        stat = None
+
+        status = get_user_status(user_id)
+        if not status:
+            return {'error': 'User is not existed'}, 400
+        if status != "processing":
+            image_url = f"https://storage.cloud.google.com/{BACKGROUND_IMAGE_BUCKET}/{user_id}.png"
+            video_url = f"https://storage.cloud.google.com/{VIDEO_BUCKET}/{user_id}.mp4"
+            commentary = get_commentary(user_id)
+            stat = get_stat(user_id)
+
+        response_data = {
+            'status': status,
+            'imageUrl': image_url,
+            'commentary': commentary,
+            'videoUrl': video_url,
+            'users': int(stat['num_users']),
+            'shots': int(stat['user_shots']),
+            'average': stat['average_shots'],
+            'barchart': stat['barchart']
+        }
+
+        response = make_response(response_data)
+        response.headers.add('Access-Control-Allow-Origin', 'http://127.0.0.1:5501')
+        response.headers['Content-Type'] = 'application/json'
+        return response, 200
+
+    except Exception as e:
+        print(f"Error fetching user status: {e}")
+        return {'error': 'Failed to fetch user status'}, 500

data-analytics/minigolf-demo/backend/requirements.txt

@@ -0,0 +1,10 @@
+functions-framework==3.*
+firebase-admin
+flask
+flask-cors
+google-cloud-bigquery
+google-cloud-storage
+google-cloud-bigquery-storage
+matplotlib
+pandas
+db-dtypes