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ai_crawling_data_retrieval [2025/05/24 19:58] – [Purpose] eagleeyenebulaai_crawling_data_retrieval [2025/06/08 18:22] (current) – [Overview] eagleeyenebula
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 ===== Overview ===== ===== Overview =====
 The **ai_crawling_data_retrieval.py** module provides a foundation for retrieving external data via web crawling or API calls. With a simple interface and extensible logic, this module enables fetching data from URLs or external APIs for integration into AI workflows. The **ai_crawling_data_retrieval.py** module provides a foundation for retrieving external data via web crawling or API calls. With a simple interface and extensible logic, this module enables fetching data from URLs or external APIs for integration into AI workflows.
 +
 +{{youtube>5jrYeaBN3sQ?large}}
 +
 +-------------------------------------------------------------
  
 The module is a critical component of the **G.O.D. Framework**, as it dynamically collects external resources for machine learning, automation workflows, or real-time decision-making. The companion `ai_crawling_data_retrieval.html` explains how to use the script, provides visual guidelines, and outlines examples of data retrieval tasks. The module is a critical component of the **G.O.D. Framework**, as it dynamically collects external resources for machine learning, automation workflows, or real-time decision-making. The companion `ai_crawling_data_retrieval.html` explains how to use the script, provides visual guidelines, and outlines examples of data retrieval tasks.
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 The goals of this module include: The goals of this module include:
  
-  1. Simplifying external data fetching via a unified interface.+1. Simplifying external data fetching via a unified interface.
      
-  2. Providing dynamic, extensible functionality to retrieve data from remote sources.+2. Providing dynamic, extensible functionality to retrieve data from remote sources.
      
-  3. Logging the fetching process to enable debugging and tracking.+3. Logging the fetching process to enable debugging and tracking.
      
-  4. Creating a framework for scalable web crawling and structured API data acquisition.+4. Creating a framework for scalable web crawling and structured API data acquisition.
  
 ---- ----
  
 ===== Key Features ===== ===== Key Features =====
-The **`ai_crawling_data_retrieval.py`** module offers the following features:+The **ai_crawling_data_retrieval.py** module offers the following features:
  
   * **Data Retrieval API:**   * **Data Retrieval API:**
-    - A single method, `fetch_external_data`, serves as an endpoint for fetching data from URLs or APIs.+    - A single method, **fetch_external_data**, serves as an endpoint for fetching data from URLs or APIs.
   * **Minimal Setup:**   * **Minimal Setup:**
     - Out-of-the-box functionality to return mock data while providing hooks for integration into more advanced crawling workflows.     - Out-of-the-box functionality to return mock data while providing hooks for integration into more advanced crawling workflows.
   * **Extensibility:**   * **Extensibility:**
-    - The module can incorporate parsing libraries (e.g., `BeautifulSoup`) or request frameworks (e.g., `requests`) as needed for crawling or API interactions.+    - The module can incorporate parsing libraries (e.g., **BeautifulSoup**) or request frameworks (e.g., **requests**) as needed for crawling or API interactions.
   * **Built-in Logging:**   * **Built-in Logging:**
-    - Leverages Python's `logging` library to log every step of the data retrieval process.+    - Leverages Python's **logging** library to log every step of the data retrieval process.
   * **Error-Handling Routines:** (Basic, expandable)   * **Error-Handling Routines:** (Basic, expandable)
     - Gracefully handles missing data sources or failed retrieval attempts, enabling robust task execution.     - Gracefully handles missing data sources or failed retrieval attempts, enabling robust task execution.
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 ==== 1. Fetch External Data ==== ==== 1. Fetch External Data ====
-The `fetch_external_data` method: +The **fetch_external_data** method: 
-  1. Receives a `source` parameter, which represents the URL or API endpoint of the external resource. +1. Receives a **source** parameter, which represents the URL or API endpoint of the external resource. 
-  2. Logs the data-fetching operation via Python’s `logging` library. +2. Logs the data-fetching operation via Python’s **logging** library. 
-  3. The current implementation returns a mock JSON object (`Mock data from external source`) but is designed to integrate libraries for real functionality.+3. The current implementation returns a mock JSON object (**Mock data from external source**) but is designed to integrate libraries for real functionality.
  
 Example: Example:
-```python+<code> 
 +python
 data = DataRetrieval.fetch_external_data("https://example.com/api/data") data = DataRetrieval.fetch_external_data("https://example.com/api/data")
-```+</code>
  
 **Returned Data:** **Returned Data:**
-```python+<code> 
 +python
 {"data": "Mock data from external source"} {"data": "Mock data from external source"}
-``` +</code>
- +
-----+
  
 ===== Dependencies ===== ===== Dependencies =====
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 ==== Required Libraries ==== ==== Required Libraries ====
-  * **`logging`:** Logs the progress and success/failure of data retrieval operations.+  * **logging:** Logs the progress and success/failure of data retrieval operations.
  
-To enable future enhancements (e.g., real web crawling and API calls), additional libraries like `requests`, `BeautifulSoup` (from `bs4`), or third-party crawling frameworks (e.g., Scrapy) may be incorporated.+To enable future enhancements (e.g., real web crawling and API calls), additional libraries like **requests**, **BeautifulSoup** (from **bs4**), or third-party crawling frameworks (e.g., Scrapy) may be incorporated.
  
 ==== Installation ==== ==== Installation ====
 For advanced usage requiring external libraries, install dependencies as needed: For advanced usage requiring external libraries, install dependencies as needed:
-```bash+<code> 
 +bash
 pip install requests beautifulsoup4 pip install requests beautifulsoup4
-``` 
  
 +</code>
 ---- ----
  
 ===== Usage ===== ===== Usage =====
  
-The following examples demonstrate how to leverage the **`DataRetrieval`** module.+The following examples demonstrate how to leverage the **Data Retrieval** module.
  
 ==== Basic Example ==== ==== Basic Example ====
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 **Step-by-Step Guide:** **Step-by-Step Guide:**
-1. Import the `DataRetrieval` class: +1. Import the **Data Retrieval** class: 
-   ```python+<code> 
 +   python
    from ai_crawling_data_retrieval import DataRetrieval    from ai_crawling_data_retrieval import DataRetrieval
-   ```+</code>
  
-2. Use the `fetch_external_data` method: +2. Use the **fetch_external_data** method: 
-   ```python+<code>    
 +   python
    source = "https://example.com/api/sample"    source = "https://example.com/api/sample"
    data = DataRetrieval.fetch_external_data(source)    data = DataRetrieval.fetch_external_data(source)
    print(data)    print(data)
-   ```+</code>
  
 **Example Output:** **Example Output:**
-```plaintext+<code> 
 +plaintext
 INFO:root:Fetching external data from https://example.com/api/sample... INFO:root:Fetching external data from https://example.com/api/sample...
 INFO:root:Data retrieved: {'data': 'Mock data from external source'} INFO:root:Data retrieved: {'data': 'Mock data from external source'}
 {'data': 'Mock data from external source'} {'data': 'Mock data from external source'}
-```+</code>
  
 ---- ----
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 ==== Advanced Examples ==== ==== Advanced Examples ====
  
-**1. Real Data Retrieval with `requests`** +**1. Real Data Retrieval with **requests** ** 
-Replace the mock data with real network responses using the `requests` library: +Replace the mock data with real network responses using the **requests** library: 
-```python+<code> 
 +python
 import requests import requests
  
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             logging.error(f"Failed to fetch data: {e}")             logging.error(f"Failed to fetch data: {e}")
             return {"error": str(e)}             return {"error": str(e)}
-```+</code>
  
 **Example Usage:** **Example Usage:**
-```python+<code> 
 +python
 retrieval = RealDataRetrieval() retrieval = RealDataRetrieval()
 data = retrieval.fetch_external_data("https://api.spacexdata.com/v4/launches/latest") data = retrieval.fetch_external_data("https://api.spacexdata.com/v4/launches/latest")
 print(data) print(data)
-```+</code>
  
 **Sample Output:** **Sample Output:**
-```plaintext+<code> 
 +plaintext
 INFO:root:Fetching external data from https://api.spacexdata.com/v4/launches/latest... INFO:root:Fetching external data from https://api.spacexdata.com/v4/launches/latest...
 INFO:root:Data retrieved: {'id': '5eb87d46ffd86e000604b388', 'name': 'Starlink Group 4-17', ...} INFO:root:Data retrieved: {'id': '5eb87d46ffd86e000604b388', 'name': 'Starlink Group 4-17', ...}
 {'id': '5eb87d46ffd86e000604b388', 'name': 'Starlink Group 4-17', ...} {'id': '5eb87d46ffd86e000604b388', 'name': 'Starlink Group 4-17', ...}
-```+</code>
  
 **2. Scraping HTML Data with BeautifulSoup** **2. Scraping HTML Data with BeautifulSoup**
 Extend the module to include web scraping functionality: Extend the module to include web scraping functionality:
-```python+<code> 
 +python
 from bs4 import BeautifulSoup from bs4 import BeautifulSoup
 import requests import requests
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 scraped_data = scraper.fetch_external_data("https://example.com") scraped_data = scraper.fetch_external_data("https://example.com")
 print(scraped_data) print(scraped_data)
-```+</code>
  
 **Example Output:** **Example Output:**
-```plaintext+<code> 
 +plaintext
 INFO:root:Fetching HTML data from https://example.com... INFO:root:Fetching HTML data from https://example.com...
 INFO:root:Data retrieved: {'titles': ['Example Domain']} INFO:root:Data retrieved: {'titles': ['Example Domain']}
 {'titles': ['Example Domain']} {'titles': ['Example Domain']}
-```+</code>
  
 **3. Logging Retrieved Data to a File** **3. Logging Retrieved Data to a File**
 Store data locally for further processing: Store data locally for further processing:
-```python+<code> 
 +python
 data = DataRetrieval.fetch_external_data("https://example.com") data = DataRetrieval.fetch_external_data("https://example.com")
 with open("retrieved_data.json", "w") as file: with open("retrieved_data.json", "w") as file:
     file.write(str(data))     file.write(str(data))
-``` 
  
 +</code>
 ---- ----
  
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 ===== Enhancing Data Retrieval ===== ===== Enhancing Data Retrieval =====
-The following are ways to expand the functionality of the `DataRetrieval` module:+The following are ways to expand the functionality of the **Data Retrieval** module:
  
 1. **Support for Multiple Formats:** 1. **Support for Multiple Formats:**
    - Extend data retrieval to support formats like XML, CSV, or raw HTML.    - Extend data retrieval to support formats like XML, CSV, or raw HTML.
-   - Use libraries such as `pandas` for parsing tabular formats.+   - Use libraries such as **pandas** for parsing tabular formats.
  
 2. **Configurable Retry Logic:** 2. **Configurable Retry Logic:**
-   - Implement retry policies via `urllib3` or similar utilities to handle intermittent connection issues.+   - Implement retry policies via **urllib3** or similar utilities to handle intermittent connection issues.
  
 3. **Authentication for APIs:** 3. **Authentication for APIs:**
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 Example Retry Logic: Example Retry Logic:
-```python+<code> 
 +python
 import time import time
  
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                 time.sleep(delay)                 time.sleep(delay)
         return {"error": "All retries failed"}         return {"error": "All retries failed"}
-```+</code>
  
 ---- ----
  
 ===== Integration Opportunities ===== ===== Integration Opportunities =====
-* **Real-Time Pipelines:** Integrate external data retrieval within data preprocessing stages of an AI pipeline. +**Real-Time Pipelines:** Integrate external data retrieval within data preprocessing stages of an AI pipeline. 
-* **Dashboards:** Feed live metrics data to monitoring dashboards. +**Dashboards:** Feed live metrics data to monitoring dashboards. 
-* **Web Automation:** Scrape dynamic content for real-time insights into market trends, news, etc. +**Web Automation:** Scrape dynamic content for real-time insights into market trends, news, etc.
- +
-----+
  
 ===== Future Enhancements ===== ===== Future Enhancements =====
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 ===== Licensing and Author Information ===== ===== Licensing and Author Information =====
-The **`ai_crawling_data_retrieval.py`** module is part of the **G.O.D. Framework**. Redistribution or modification is subject to platform licensing terms. For integration support, please contact the development team.+The **ai_crawling_data_retrieval.py** module is part of the **G.O.D. Framework**. Redistribution or modification is subject to platform licensing terms. For integration support, please contact the development team.
  
 ---- ----
  
 ===== Conclusion ===== ===== Conclusion =====
-The **`ai_crawling_data_retrieval.py`** module simplifies external data acquisition for AI and automation tasks, offering a foundational interface for web crawling and API integration. With its built-in logging, extensible structure, and numerous enhancement opportunities, this module makes it easy to incorporate real-time data into diverse applications. Whether used for small-scale projects or expanded into larger workflows, its potential is virtually limitless.+The **ai_crawling_data_retrieval.py** module simplifies external data acquisition for AI and automation tasks, offering a foundational interface for web crawling and API integration. With its built-in logging, extensible structure, and numerous enhancement opportunities, this module makes it easy to incorporate real-time data into diverse applications. Whether used for small-scale projects or expanded into larger workflows, its potential is virtually limitless.
ai_crawling_data_retrieval.1748116723.txt.gz · Last modified: 2025/05/24 19:58 by eagleeyenebula