[Count Events] Add empty notebook for build marketplace CI

modules/src/count_events/count_events.ipynb

@@ -0,0 +1,37 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    ""
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

modules/src/count_events/count_events.py

@@ -0,0 +1,39 @@
+# Copyright 2025 Iguazio
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from mlrun.model_monitoring.applications import (
+    ModelMonitoringApplicationBase, ModelMonitoringApplicationMetric,
+)
+import mlrun.model_monitoring.applications.context as mm_context
+
+
+class CountApp(ModelMonitoringApplicationBase):
+    def do_tracking(
+        self, monitoring_context: mm_context.MonitoringApplicationContext
+    ) -> ModelMonitoringApplicationMetric:
+        sample_df = monitoring_context.sample_df
+        monitoring_context.logger.debug("Sample data-frame", sample_df=sample_df)
+        count = len(sample_df)
+        monitoring_context.logger.info(
+            "Counted events for model endpoint window",
+            model_endpoint_name=monitoring_context.model_endpoint.metadata.name,
+            count=count,
+            start=monitoring_context.start_infer_time,
+            end=monitoring_context.end_infer_time,
+        )
+        return ModelMonitoringApplicationMetric(
+            name="count",
+            value=count,
+        )

modules/src/count_events/item.yaml

@@ -0,0 +1,17 @@
+apiVersion: v1
+categories:
+- model-serving
+description: Count events in each time window
+example:
+generationDate: 2025-09-16:12-25
+hidden: false
+labels:
+  author: iguazio
+mlrunVersion: 1.10.0-rc27
+name: count_events
+spec:
+    filename: count_events.py
+    image: mlrun/mlrun
+    kind: monitoring_application
+    requirements:
+version: 1.0.0

modules/src/count_events/requirements.txt

@@ -0,0 +1,3 @@
+mlrun==1.10.0-rc27
+pandas==2.1.4
+pytest~=8.2

modules/src/count_events/test_count_events.py

@@ -0,0 +1,75 @@
+# Copyright 2025 Iguazio
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+
+from mlrun.model_monitoring.applications import ModelMonitoringApplicationMetric
+import mlrun.model_monitoring.applications.context as mm_context
+
+from count_events import CountApp
+
+from unittest.mock import Mock
+from datetime import datetime
+import pandas as pd
+import pytest
+
+class TestCountApp:
+    """Test suite for CountApp class."""
+
+    def setup_method(self):
+        """Set up test fixtures before each test method."""
+        self.count_app = CountApp()
+    @staticmethod
+    def _create_mock_monitoring_context(sample_df, model_endpoint_name="test-model"):
+        """Helper method to create a mock monitoring context."""
+        mock_context = Mock(spec=mm_context.MonitoringApplicationContext)
+
+        # Mock the sample dataframe
+        mock_context.sample_df = sample_df
+
+        # Mock the logger
+        mock_logger = Mock()
+        mock_context.logger = mock_logger
+
+        # Mock the model endpoint
+        mock_model_endpoint = Mock()
+        mock_model_endpoint.metadata.name = model_endpoint_name
+        mock_context.model_endpoint = mock_model_endpoint
+
+        # Mock time attributes
+        mock_context.start_infer_time = datetime(2025, 1, 1, 10, 0, 0)
+        mock_context.end_infer_time = datetime(2025, 1, 1, 11, 0, 0)
+
+        return mock_context
+
+
+    @pytest.mark.parametrize("df_size", [0, 1, 10, 100, 1000])
+    def test_do_tracking_with_various_dataframe_sizes(self, df_size):
+        """Test do_tracking with various dataframe sizes using parametrized test."""
+        # Arrange
+        if df_size == 0:
+            test_df = pd.DataFrame()
+        else:
+            test_df = pd.DataFrame({"col1": range(df_size)})
+
+        mock_context = self._create_mock_monitoring_context(test_df)
+
+        # Act
+        result = self.count_app.do_tracking(mock_context)
+
+        # Assert
+        assert isinstance(result, ModelMonitoringApplicationMetric)
+        assert result.value == df_size
+        assert result.name == "count"
+