ai_offline_support
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| ai_offline_support [2025/05/28 19:27] – [Example 5: Supporting CSV Parsing] eagleeyenebula | ai_offline_support [2025/05/28 19:42] (current) – [Class Overview] eagleeyenebula | ||
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| ===== Class Overview ===== | ===== Class Overview ===== | ||
| - | The `OfflineSupport` class directly enables reading and processing of data from files stored on a local disk. | + | The **OfflineSupport** class directly enables reading and processing of data from files stored on a local disk. |
| < | < | ||
| python | python | ||
| Line 206: | Line 206: | ||
| * Processes multiple files in a batch. For missing files, clear error messages are returned rather than halting the workflow. | * Processes multiple files in a batch. For missing files, clear error messages are returned rather than halting the workflow. | ||
| ===== Advanced Examples ===== | ===== Advanced Examples ===== | ||
| - | |||
| - | --- | ||
| ==== Example 5: Supporting CSV Parsing ==== | ==== Example 5: Supporting CSV Parsing ==== | ||
| Line 246: | Line 244: | ||
| Use local saved machine learning models for prediction when offline. | Use local saved machine learning models for prediction when offline. | ||
| - | + | < | |
| - | ```python | + | python |
| import joblib | import joblib | ||
| from ai_offline_support import OfflineSupport | from ai_offline_support import OfflineSupport | ||
| Line 264: | Line 262: | ||
| return f" | return f" | ||
| - | + | </ | |
| - | # Example Usage | + | **Example Usage** |
| + | < | ||
| model_loader = OfflineModelLoader() | model_loader = OfflineModelLoader() | ||
| model_path = " | model_path = " | ||
| model = model_loader.load_model(model_path) | model = model_loader.load_model(model_path) | ||
| print(model) | print(model) | ||
| - | ``` | + | </ |
| **Explanation**: | **Explanation**: | ||
| - | - Demonstrates loading and using offline machine learning models. | + | |
| - | + | ||
| - | --- | + | |
| ===== Extensibility ===== | ===== Extensibility ===== | ||
| 1. **Implement Format-Specific Parsers**: | 1. **Implement Format-Specific Parsers**: | ||
| - | | + | * Extend the class to process files in formats like XML, YAML, or Excel. |
| 2. **Offline Data Validation**: | 2. **Offline Data Validation**: | ||
| - | Add validation checks to ensure file contents match expected structures. | + | * Add validation checks to ensure file contents match expected structures. |
| 3. **Hybrid Data Processing**: | 3. **Hybrid Data Processing**: | ||
| - | | + | * Combine offline and cached online data for hybrid offline-first workflows. |
| 4. **Support for Binary Files**: | 4. **Support for Binary Files**: | ||
| - | Use methods to handle binary data such as images, videos, or serialized objects. | + | * Use methods to handle binary data such as images, videos, or serialized objects. |
| - | + | ||
| - | --- | + | |
| ===== Best Practices ===== | ===== Best Practices ===== | ||
| - | - **Validate File Paths**: | + | **Validate File Paths**: |
| - | Ensure that file paths are correct and accessible before processing. | + | |
| - | + | ||
| - | - **Graceful Fallbacks**: | + | |
| - | Provide default fallback content or error messages when files are missing. | + | |
| - | + | ||
| - | - **Resource Management**: | + | |
| - | Use proper file handling techniques (e.g., context managers) to minimize resource leaks. | + | |
| - | - **Log Errors Clearly**: | + | **Graceful Fallbacks**: |
| - | | + | |
| - | - **Adopt Context-Specific Parsing**: | + | **Resource Management**: |
| - | | + | |
| - | --- | + | **Log Errors Clearly**: |
| + | * Maintain detailed logs of file access errors for easier debugging later. | ||
| + | | ||
| + | * Extend the class to handle domain-specific file types as needed. | ||
| ===== Conclusion ===== | ===== Conclusion ===== | ||
ai_offline_support.1748460463.txt.gz · Last modified: 2025/05/28 19:27 by eagleeyenebula
