Language-Of-Things-Training/05-python/simple-python.lotnb at main · CorefluxCommunity/Language-Of-Things-Training · GitHub

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[
  {
    "kind": 1,
    "language": "markdown",
    "value": "# Simple Python - Adding Programming Power\n\n[⬅️ Previous: Database Routes](../04-routes/database-routes.lotnb) | [🏠 Back to Index](../index.lotnb) | [➡️ Next: Advanced Python](./advanced-python.lotnb)\n\n---\n\n<details>\n<summary><strong>Navigation Menu</strong></summary>\n\n| Section | Tutorials |\n|---------|----------|\n| **Setup** | [Environment Setup](../00-setup/verify-environment.lotnb) |\n| **Basics** | [Timed Actions](../01-basics/timed-actions.lotnb) \\| [Topic Actions](../01-basics/topic-actions.lotnb) |\n| **Logic** | [Conditional Logic](../02-logic/conditional-logic.lotnb) |\n| **Models** | [Basic Models](../03-models/basic-models.lotnb) \\| [Action Models](../03-models/action-models.lotnb) \\| [Inheritance](../03-models/model-inheritance.lotnb) |\n| **Routes** | [MQTT Bridge](../04-routes/mqtt-bridge.lotnb) \\| [Database](../04-routes/database-routes.lotnb) |\n| **Python** | [Simple](./simple-python.lotnb) \\| [Advanced](./advanced-python.lotnb) |\n\n</details>\n\n---\n\n> **CAUTION - Free Tier Resource Limits**\n>\n> The free version of Coreflux has resource limits:\n> - **Routes**: 2 maximum\n> - **Actions**: 12 maximum\n> - **Models**: 40 maximum\n>\n> Delete unused resources before creating new ones during exercises.\n\n---\n\n## Learning Objectives\n\nIn this tutorial, you will learn:\n- How to integrate Python scripts with LoT actions\n- The `CALL PYTHON` syntax and parameter passing\n- Creating Python functions for LoT integration\n- Handling return values and JSON data\n- Error handling in Python scripts\n- When to use Python vs pure LoT logic\n\n---\n\n## 📖 Introduction\n\n**Python Integration** extends LoT's capabilities with full programming language features:\n- Complex calculations and algorithms\n- External library integration\n- File operations and data processing\n- Machine learning and AI integration\n- Advanced string manipulation and parsing\n\n### Real-World Applications\n- **Data Analysis**: Statistical calculations on sensor data\n- **Image Processing**: Analyze camera feeds with computer vision\n- **Machine Learning**: Predictive maintenance algorithms\n- **External APIs**: Complex API interactions and data transformation\n\n---\n\n## 🧠 Core Concepts\n\n### CALL PYTHON Syntax\n\n```lot\nCALL PYTHON \"ScriptName.function_name\"\n    WITH (parameter1, parameter2, ...)\n    RETURN AS {variable_name}\n```\n\n### Python Script Structure\n\n```python\n# Script Name: ScriptName\ndef function_name(param1, param2):\n    # Your Python code here\n    return result\n```\n\n### Parameter Passing\n\n- **Single Parameter**: `WITH (PAYLOAD)`\n- **Multiple Parameters**: `WITH (param1, param2, param3)`\n- **Mixed Types**: `WITH (PAYLOAD, \"string\", 123, TRUE)`\n\n### Return Value Handling\n\n- **Simple Values**: Return strings, numbers, booleans\n- **JSON Objects**: Return dictionaries for structured data\n- **Error Handling**: Return error indicators or None\n\n---\n\n## 🛠️ Hands-On Examples\n\n### Example 1: Simple Math Calculator\n\nLet's start with basic Python functions:"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Script Name: MathCalculator\r\ndef add_numbers(a, b):\r\n    \"\"\"Add two numbers and return the result\"\"\"\r\n    try:\r\n        result = float(a) + float(b)\r\n        return result\r\n    except (ValueError, TypeError):\r\n        return 0\r\n\r\ndef calculate_percentage(value, total):\r\n    \"\"\"Calculate percentage with error handling\"\"\"\r\n    try:\r\n        if float(total) == 0:\r\n            return 0\r\n        percentage = (float(value) / float(total)) * 100\r\n        return round(percentage, 2)\r\n    except (ValueError, TypeError, ZeroDivisionError):\r\n        return 0\r\n\r\ndef format_temperature(celsius):\r\n    \"\"\"Convert Celsius to Fahrenheit and format nicely\"\"\"\r\n    try:\r\n        celsius_val = float(celsius)\r\n        fahrenheit = (celsius_val * 9/5) + 32\r\n        return f\"{celsius_val}°C ({fahrenheit:.1f}°F)\"\r\n    except (ValueError, TypeError):\r\n        return \"Invalid temperature\""
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "DEFINE ACTION SimpleMathProcessor\r\nON TOPIC \"math/+/calculate\" DO\r\n    SET \"operation\" WITH TOPIC POSITION 2\r\n    \r\n    IF {operation} EQUALS \"add\" THEN\r\n        // Expect payload like \"5,3\" for adding 5 + 3\r\n        SET \"numbers\" WITH PAYLOAD\r\n        CALL PYTHON \"MathCalculator.add_numbers\"\r\n            WITH (5, 3)\r\n            RETURN AS {result}\r\n        PUBLISH TOPIC \"math/add/result\" WITH {result}\r\n    \r\n    ELSE IF {operation} EQUALS \"percentage\" THEN\r\n        // Calculate percentage: value out of total\r\n        CALL PYTHON \"MathCalculator.calculate_percentage\"\r\n            WITH (GET TOPIC \"math/current/value\", GET TOPIC \"math/current/total\")\r\n            RETURN AS {percentage}\r\n        PUBLISH TOPIC \"math/percentage/result\" WITH {percentage}\r\n    \r\n    ELSE IF {operation} EQUALS \"temperature\" THEN\r\n        // Format temperature with conversion\r\n        CALL PYTHON \"MathCalculator.format_temperature\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {formatted_temp}\r\n        PUBLISH TOPIC \"math/temperature/formatted\" WITH {formatted_temp}"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "**What this does:**\n- Defines simple Python functions for common calculations\n- Calls different Python functions based on topic structure\n- Handles parameters from both payload and stored topics\n- Includes error handling in Python functions\n- Demonstrates basic Python-LoT integration\n\n**Test it:**\n```\nPublish to: math/temperature/calculate\nPayload: 25\nResult in math/temperature/formatted: \"25°C (77.0°F)\"\n```\n\n---\n\n### Example 2: String Processing Functions\n\nLet's create Python functions for text processing:"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Script Name: TextProcessor\r\ndef clean_sensor_data(raw_data):\r\n    \"\"\"Clean and validate sensor data string\"\"\"\r\n    try:\r\n        # Remove whitespace and convert to uppercase\r\n        cleaned = str(raw_data).strip().upper()\r\n        \r\n        # Basic validation\r\n        if len(cleaned) == 0:\r\n            return \"INVALID_DATA\"\r\n        \r\n        # Remove special characters except numbers and letters\r\n        import re\r\n        cleaned = re.sub(r'[^A-Z0-9._-]', '', cleaned)\r\n        \r\n        return cleaned\r\n    except Exception as e:\r\n        return f\"ERROR: {str(e)}\"\r\n\r\ndef parse_equipment_code(equipment_string):\r\n    \"\"\"Parse equipment code and return structured information\"\"\"\r\n    try:\r\n        # Expected format: \"PUMP_001_LINE_A\"\r\n        parts = str(equipment_string).split('_')\r\n        \r\n        if len(parts) >= 4:\r\n            return {\r\n                \"equipment_type\": parts[0],\r\n                \"equipment_number\": parts[1],\r\n                \"line_id\": parts[2],\r\n                \"section\": parts[3],\r\n                \"full_code\": equipment_string\r\n            }\r\n        else:\r\n            return {\"error\": \"Invalid equipment code format\"}\r\n    except Exception as e:\r\n        return {\"error\": str(e)}\r\n\r\ndef generate_report_summary(data_json):\r\n    \"\"\"Generate a text summary from JSON data\"\"\"\r\n    try:\r\n        import json\r\n        data = json.loads(data_json) if isinstance(data_json, str) else data_json\r\n        \r\n        summary_parts = []\r\n        \r\n        if 'production_count' in data:\r\n            summary_parts.append(f\"Produced: {data['production_count']} units\")\r\n        \r\n        if 'efficiency' in data:\r\n            summary_parts.append(f\"Efficiency: {data['efficiency']}%\")\r\n        \r\n        if 'quality_rate' in data:\r\n            summary_parts.append(f\"Quality: {data['quality_rate']}%\")\r\n        \r\n        if 'operator' in data:\r\n            summary_parts.append(f\"Operator: {data['operator']}\")\r\n        \r\n        return \" | \".join(summary_parts) if summary_parts else \"No data available\"\r\n    \r\n    except Exception as e:\r\n        return f\"Summary generation error: {str(e)}\""
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "DEFINE ACTION TextProcessingDemo\r\nON TOPIC \"text/+/process\" DO\r\n    SET \"operation\" WITH TOPIC POSITION 2\r\n    \r\n    IF {operation} EQUALS \"clean\" THEN\r\n        // Clean sensor data\r\n        CALL PYTHON \"TextProcessor.clean_sensor_data\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {cleaned_data}\r\n        PUBLISH TOPIC \"text/clean/result\" WITH {cleaned_data}\r\n    \r\n    ELSE IF {operation} EQUALS \"parse\" THEN\r\n        // Parse equipment code\r\n        CALL PYTHON \"TextProcessor.parse_equipment_code\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {parsed_info}\r\n        PUBLISH TOPIC \"text/parse/result\" WITH {parsed_info}\r\n    \r\n    ELSE IF {operation} EQUALS \"summary\" THEN\r\n        // Generate report summary\r\n        CALL PYTHON \"TextProcessor.generate_report_summary\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {summary}\r\n        PUBLISH TOPIC \"text/summary/result\" WITH {summary}"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "**What this does:**\n- Provides text cleaning and validation functions\n- Parses structured equipment codes into components\n- Generates human-readable summaries from JSON data\n- Includes comprehensive error handling\n- Demonstrates practical text processing use cases\n\n**Test it:**\n```\nPublish to: text/parse/process\nPayload: \"PUMP_001_LINE_A\"\nResult in text/parse/result:\n{\n  \"equipment_type\": \"PUMP\",\n  \"equipment_number\": \"001\",\n  \"line_id\": \"LINE\",\n  \"section\": \"A\",\n  \"full_code\": \"PUMP_001_LINE_A\"\n}\n```\n\n---\n\n### Example 3: Data Validation Functions\n\nLet's create Python functions for data validation:"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Script Name: DataValidator\r\ndef validate_sensor_reading(value, min_val, max_val):\r\n    \"\"\"Validate sensor reading against acceptable range\"\"\"\r\n    try:\r\n        reading = float(value)\r\n        min_limit = float(min_val)\r\n        max_limit = float(max_val)\r\n        \r\n        if reading < min_limit:\r\n            return {\r\n                \"valid\": False,\r\n                \"reason\": \"Below minimum\",\r\n                \"value\": reading,\r\n                \"min_limit\": min_limit,\r\n                \"max_limit\": max_limit\r\n            }\r\n        elif reading > max_limit:\r\n            return {\r\n                \"valid\": False,\r\n                \"reason\": \"Above maximum\",\r\n                \"value\": reading,\r\n                \"min_limit\": min_limit,\r\n                \"max_limit\": max_limit\r\n            }\r\n        else:\r\n            return {\r\n                \"valid\": True,\r\n                \"reason\": \"Within range\",\r\n                \"value\": reading,\r\n                \"min_limit\": min_limit,\r\n                \"max_limit\": max_limit\r\n            }\r\n    except (ValueError, TypeError) as e:\r\n        return {\r\n            \"valid\": False,\r\n            \"reason\": f\"Invalid data: {str(e)}\",\r\n            \"value\": value\r\n        }\r\n\r\ndef check_equipment_id_format(equipment_id):\r\n    \"\"\"Validate equipment ID format\"\"\"\r\n    import re\r\n    \r\n    try:\r\n        # Expected format: 3 letters + 3 digits (e.g., PMP001, CNV002)\r\n        pattern = r'^[A-Z]{3}[0-9]{3}$'\r\n        \r\n        if re.match(pattern, str(equipment_id)):\r\n            return {\r\n                \"valid\": True,\r\n                \"format\": \"Standard\",\r\n                \"type_code\": equipment_id[:3],\r\n                \"number\": equipment_id[3:]\r\n            }\r\n        else:\r\n            return {\r\n                \"valid\": False,\r\n                \"format\": \"Invalid\",\r\n                \"expected\": \"3 letters + 3 digits (e.g., PMP001)\"\r\n            }\r\n    except Exception as e:\r\n        return {\"valid\": False, \"error\": str(e)}"
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "DEFINE ACTION DataValidationProcessor\r\nON TOPIC \"validation/+/check\" DO\r\n    SET \"validation_type\" WITH TOPIC POSITION 2\r\n    \r\n    IF {validation_type} EQUALS \"sensor\" THEN\r\n        // Validate sensor reading\r\n        CALL PYTHON \"DataValidator.validate_sensor_reading\"\r\n            WITH (PAYLOAD, GET TOPIC \"validation/sensor/min\", GET TOPIC \"validation/sensor/max\")\r\n            RETURN AS {validation_result}\r\n        \r\n        // Route based on validation result\r\n        SET \"is_valid\" WITH (GET JSON \"valid\" IN {validation_result} AS BOOL)\r\n        IF {is_valid} EQUALS TRUE THEN\r\n            PUBLISH TOPIC \"validation/sensor/passed\" WITH {validation_result}\r\n            PUBLISH TOPIC \"sensors/validated/reading\" WITH PAYLOAD\r\n        ELSE\r\n            PUBLISH TOPIC \"validation/sensor/failed\" WITH {validation_result}\r\n            PUBLISH TOPIC \"alarms/validation/sensor\" WITH (GET JSON \"reason\" IN {validation_result} AS STRING)\r\n    \r\n    ELSE IF {validation_type} EQUALS \"equipment\" THEN\r\n        // Validate equipment ID format\r\n        CALL PYTHON \"DataValidator.check_equipment_id_format\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {format_check}\r\n        \r\n        SET \"format_valid\" WITH (GET JSON \"valid\" IN {format_check} AS BOOL)\r\n        IF {format_valid} EQUALS TRUE THEN\r\n            PUBLISH TOPIC \"validation/equipment/passed\" WITH {format_check}\r\n            PUBLISH TOPIC \"equipment/validated/id\" WITH PAYLOAD\r\n        ELSE\r\n            PUBLISH TOPIC \"validation/equipment/failed\" WITH {format_check}\r\n            PUBLISH TOPIC \"alarms/validation/equipment\" WITH \"Invalid equipment ID format: \" + PAYLOAD"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "**What this does:**\n- Validates sensor readings against acceptable ranges\n- Checks equipment ID format compliance\n- Routes data based on validation results\n- Creates alarms for invalid data\n- Demonstrates Python-based validation logic\n- Shows JSON data extraction from Python returns\n\n**Key Features:**\n- **Range Validation**: Check if sensor values are within acceptable limits\n- **Format Validation**: Ensure equipment IDs follow company standards\n- **Conditional Routing**: Valid data goes to validated topics, invalid to alarms\n- **Structured Returns**: Python returns detailed validation information\n\n**Test it:**\n```\nSet validation limits:\n  validation/sensor/min: 0\n  validation/sensor/max: 100\n\nPublish to: validation/sensor/check\nPayload: 75\nResult in validation/sensor/passed:\n{\n  \"valid\": true,\n  \"reason\": \"Within range\",\n  \"value\": 75,\n  \"min_limit\": 0,\n  \"max_limit\": 100\n}\n```\n\n---\n\n### Example 4: Simple Data Transformation\n\nLet's create Python functions for data transformation:"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Script Name: DataTransformer\r\ndef convert_units(value, from_unit, to_unit):\r\n    \"\"\"Convert between different units\"\"\"\r\n    try:\r\n        val = float(value)\r\n        \r\n        # Temperature conversions\r\n        if from_unit == \"celsius\" and to_unit == \"fahrenheit\":\r\n            return (val * 9/5) + 32\r\n        elif from_unit == \"fahrenheit\" and to_unit == \"celsius\":\r\n            return (val - 32) * 5/9\r\n        \r\n        # Pressure conversions\r\n        elif from_unit == \"psi\" and to_unit == \"bar\":\r\n            return val * 0.0689476\r\n        elif from_unit == \"bar\" and to_unit == \"psi\":\r\n            return val * 14.5038\r\n        \r\n        # Length conversions\r\n        elif from_unit == \"mm\" and to_unit == \"inches\":\r\n            return val * 0.0393701\r\n        elif from_unit == \"inches\" and to_unit == \"mm\":\r\n            return val * 25.4\r\n        \r\n        else:\r\n            return val  # No conversion needed or unknown units\r\n    \r\n    except (ValueError, TypeError):\r\n        return 0\r\n\r\ndef create_equipment_summary(equipment_data):\r\n    \"\"\"Create a summary string from equipment data\"\"\"\r\n    try:\r\n        # equipment_data expected as JSON string\r\n        import json\r\n        data = json.loads(equipment_data) if isinstance(equipment_data, str) else equipment_data\r\n        \r\n        summary_parts = []\r\n        \r\n        if 'name' in data:\r\n            summary_parts.append(f\"Equipment: {data['name']}\")\r\n        \r\n        if 'status' in data:\r\n            summary_parts.append(f\"Status: {data['status']}\")\r\n        \r\n        if 'runtime_hours' in data:\r\n            summary_parts.append(f\"Runtime: {data['runtime_hours']}h\")\r\n        \r\n        if 'efficiency' in data:\r\n            summary_parts.append(f\"Efficiency: {data['efficiency']}%\")\r\n        \r\n        return \" | \".join(summary_parts)\r\n    \r\n    except Exception as e:\r\n        return f\"Summary error: {str(e)}\""
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "DEFINE ACTION DataTransformationProcessor\r\nON TOPIC \"transform/+/request\" DO\r\n    SET \"transform_type\" WITH TOPIC POSITION 2\r\n    \r\n    IF {transform_type} EQUALS \"units\" THEN\r\n        // Convert units using Python\r\n        CALL PYTHON \"DataTransformer.convert_units\"\r\n            WITH (PAYLOAD, GET TOPIC \"transform/units/from\", GET TOPIC \"transform/units/to\")\r\n            RETURN AS {converted_value}\r\n        PUBLISH TOPIC \"transform/units/result\" WITH {converted_value}\r\n        PUBLISH TOPIC \"transform/units/original\" WITH PAYLOAD\r\n        PUBLISH TOPIC \"transform/units/timestamp\" WITH TIMESTAMP \"UTC\"\r\n    \r\n    ELSE IF {transform_type} EQUALS \"summary\" THEN\r\n        // Create equipment summary\r\n        CALL PYTHON \"DataTransformer.create_equipment_summary\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {summary}\r\n        PUBLISH TOPIC \"transform/summary/result\" WITH {summary}\r\n        PUBLISH TOPIC \"transform/summary/generated_at\" WITH TIMESTAMP \"UTC\""
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "**What this does:**\n- Provides unit conversion functions for common industrial units\n- Creates human-readable summaries from JSON data\n- Handles multiple unit types (temperature, pressure, length)\n- Includes comprehensive error handling\n- Demonstrates practical data transformation use cases\n\n**Test it:**\n```\nSet conversion parameters:\n  transform/units/from: \"celsius\"\n  transform/units/to: \"fahrenheit\"\n\nPublish to: transform/units/request\nPayload: 25\nResult in transform/units/result: 77\n```\n\n---\n\n### Example 5: Simple JSON Processing\n\nLet's work with JSON data in Python:"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Script Name: JSONProcessor\r\ndef extract_sensor_values(json_data):\r\n    \"\"\"Extract specific values from sensor JSON\"\"\"\r\n    try:\r\n        import json\r\n        data = json.loads(json_data) if isinstance(json_data, str) else json_data\r\n        \r\n        extracted = {\r\n            \"temperature\": data.get(\"temperature\", 0),\r\n            \"pressure\": data.get(\"pressure\", 0),\r\n            \"flow_rate\": data.get(\"flow_rate\", 0),\r\n            \"timestamp\": data.get(\"timestamp\", \"\"),\r\n            \"sensor_count\": len([k for k in data.keys() if k not in ['timestamp', 'sensor_id']])\r\n        }\r\n        \r\n        return json.dumps(extracted)\r\n    \r\n    except Exception as e:\r\n        return json.dumps({\"error\": str(e)})\r\n\r\ndef calculate_averages(readings_json):\r\n    \"\"\"Calculate averages from array of readings\"\"\"\r\n    try:\r\n        import json\r\n        readings = json.loads(readings_json) if isinstance(readings_json, str) else readings_json\r\n        \r\n        if not isinstance(readings, list) or len(readings) == 0:\r\n            return json.dumps({\"error\": \"No readings provided\"})\r\n        \r\n        # Calculate averages\r\n        total = sum(readings)\r\n        count = len(readings)\r\n        average = total / count\r\n        \r\n        result = {\r\n            \"average\": round(average, 2),\r\n            \"total\": total,\r\n            \"count\": count,\r\n            \"min_value\": min(readings),\r\n            \"max_value\": max(readings)\r\n        }\r\n        \r\n        return json.dumps(result)\r\n    \r\n    except Exception as e:\r\n        return json.dumps({\"error\": str(e)})"
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "DEFINE ACTION JSONProcessingDemo\r\nON TOPIC \"json/+/process\" DO\r\n    SET \"operation\" WITH TOPIC POSITION 2\r\n    \r\n    IF {operation} EQUALS \"extract\" THEN\r\n        // Extract sensor values from JSON\r\n        CALL PYTHON \"JSONProcessor.extract_sensor_values\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {extracted_data}\r\n        PUBLISH TOPIC \"json/extract/result\" WITH {extracted_data}\r\n    \r\n    ELSE IF {operation} EQUALS \"average\" THEN\r\n        // Calculate averages from array\r\n        CALL PYTHON \"JSONProcessor.calculate_averages\"\r\n            WITH (PAYLOAD)\r\n            RETURN AS {averages}\r\n        PUBLISH TOPIC \"json/average/result\" WITH {averages}\r\n        \r\n        // Extract individual values for further processing\r\n        PUBLISH TOPIC \"json/average/value\" WITH (GET JSON \"average\" IN {averages} AS DOUBLE)\r\n        PUBLISH TOPIC \"json/average/count\" WITH (GET JSON \"count\" IN {averages} AS INT)"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "**What this does:**\r\n- Extracts specific values from complex JSON payloads\r\n- Calculates statistical measures (average, min, max) from arrays\r\n- Returns structured JSON results\r\n- Extracts individual values for LoT processing\r\n- Demonstrates JSON handling patterns\r\n\r\n**Test it:**\r\n```\r\nPublish to: json/average/process\r\nPayload: [10, 20, 30, 40, 50]\r\nResult in json/average/result:\r\n{\r\n  \"average\": 30.0,\r\n  \"total\": 150,\r\n  \"count\": 5,\r\n  \"min_value\": 10,\r\n  \"max_value\": 50\r\n}\r\n```\r\n\r\n---\r\n\r\n## 🏋️ Exercises\r\n\r\n### Exercise 1: Simple Calculator\r\n**Task**: Create Python functions and LoT action for:\r\n- `multiply_numbers(a, b)` - multiply two numbers\r\n- `divide_numbers(a, b)` - divide with zero-check\r\n- Action that processes `calc/+/operation` and calls appropriate function"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Exercise 1: Write your Python functions here\n"
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "// Exercise 1: Write your LoT action here\n"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "### Exercise 2: Text Formatter\r\n**Task**: Create Python functions for text formatting:\r\n- `format_sensor_name(raw_name)` - clean and standardize sensor names\r\n- `create_alert_message(sensor, value, threshold)` - generate alert text\r\n- Action that processes formatting requests"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Exercise 2: Write your Python functions here\n"
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "// Exercise 2: Write your LoT action here\n"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "### Exercise 3: Data Quality Checker\r\n**Task**: Create a data quality system:\r\n- Python function to check data completeness, range validity, format compliance\r\n- Return quality score (0-100) and list of issues\r\n- LoT action that routes data based on quality score"
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Exercise 3: Write your Python functions here\n"
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "// Exercise 3: Write your LoT action here\n"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "### Exercise 4: Simple Statistics Calculator\r\n**Task**: Create statistical functions:\r\n- Calculate mean, median, standard deviation from array of values\r\n- Detect outliers and anomalies\r\n- Generate statistical summary reports\r\n\r\n**Challenge**: Include trend analysis (increasing, decreasing, stable)."
  },
  {
    "kind": 2,
    "language": "python",
    "value": "# Exercise 4: Write your Python functions here\n"
  },
  {
    "kind": 2,
    "language": "lot",
    "value": "// Exercise 4: Write your LoT action here\n"
  },
  {
    "kind": 1,
    "language": "markdown",
    "value": "\r\n\r\n---\r\n\r\n## 🎯 Checkpoint Questions\r\n\r\n1. **How do you pass multiple parameters to a Python function?**\r\n   - Answer: Use `WITH (param1, param2, param3)` syntax\r\n\r\n2. **What should Python functions return for LoT integration?**\r\n   - Answer: Simple values (string, number, boolean) or JSON-serializable dictionaries/lists\r\n\r\n3. **How do you extract values from JSON returned by Python?**\r\n   - Answer: Use `GET JSON \"field_name\" IN {variable} AS TYPE`\r\n\r\n4. **When should you use Python instead of pure LoT logic?**\r\n   - Answer: For complex calculations, string processing, external libraries, or advanced algorithms\r\n\r\n---\r\n\r\n## 📝 Summary\r\n\r\n### Key Concepts Learned\r\n✅ **CALL PYTHON** - Integrating Python functions with LoT actions  \r\n✅ **Parameter Passing** - Sending data from LoT to Python  \r\n✅ **Return Handling** - Processing Python function results  \r\n✅ **Error Handling** - Robust error management in Python  \r\n✅ **JSON Processing** - Working with structured data  \r\n✅ **Data Validation** - Using Python for complex validation logic  \r\n\r\n### Python Integration Patterns\r\n- **Calculations**: Mathematical operations beyond basic LoT math\r\n- **Validation**: Complex data validation and format checking\r\n- **Transformation**: Data format conversion and processing\r\n- **Text Processing**: String manipulation and parsing\r\n- **JSON Handling**: Complex JSON data extraction and manipulation\r\n### When to Use Python Or LoT? \r\n\r\n\r\n| Use Case | LoT Actions | Python Functions |\r\n|----------|-------------|------------------|\r\n| **Simple routing** | ✅ Fast, built-in | ❌ Overkill |\r\n| **Basic math** | ✅ Native support | ❌ Unnecessary |\r\n| **Complex calculations** | ❌ Limited | ✅ Full math libraries |\r\n| **String processing** | ❌ Basic only | ✅ Regex, formatting |\r\n| **External libraries** | ❌ Not supported | ✅ Full ecosystem |\r\n| **Data validation** | ❌ Simple checks only | ✅ Complex validation |\r\n\r\n### Advanced Python Features\r\n- External library integration (requests, pandas, numpy)\r\n- File operations and data persistence\r\n- Machine learning model integration\r\n- Image and signal processing\r\n\r\n### Performance Considerations\r\n- Function execution time impact\r\n- Memory usage with large data sets\r\n- Caching strategies for expensive operations\r\n- Asynchronous processing patterns\r\n\r\n\r\n### Next Steps\r\n- Practice creating simple Python functions\r\n- Experiment with different parameter types\r\n- Try JSON data processing\r\n- Move on to [Advanced Python](./advanced-python.lotnb) for complex integrations\r\n\r\n---\r\n\r\n## 🚀 Further Exploration\r\n\r\n### Advanced Python Features\r\n- External library integration (requests, pandas, numpy)\r\n- File operations and data persistence\r\n- Machine learning model integration\r\n- Image and signal processing\r\n\r\n### Performance Considerations\r\n- Function execution time impact\r\n- Memory usage with large data sets\r\n- Caching strategies for expensive operations\r\n- Asynchronous processing patterns\r\n\r\n### Error Handling Strategies\r\n- Graceful degradation on Python errors\r\n- Logging and debugging techniques\r\n- Timeout handling for long-running functions\r\n- Resource cleanup and management\r\n\r\n---\r\n\r\n**Ready for advanced Python integration? Continue with [🚀 Advanced Python](./advanced-python.lotnb)!**\r\n\r\n[⬅️ Previous: Database Routes](../04-routes/database-routes.lotnb) | [🏠 Back to Index](../index.lotnb) | [➡️ Next: Advanced Python](./advanced-python.lotnb)"
  }
]