Data validation
- Data Validation in MediaWiki
- Introduction
Data validation is a critical aspect of maintaining the quality and integrity of information within a MediaWiki installation. It ensures that the data entered by users (or through automated processes) conforms to predefined rules and standards. This prevents errors, inconsistencies, and malicious input that could compromise the reliability of your wiki. This article will provide a comprehensive guide to data validation in MediaWiki, aimed at beginners, covering its importance, methods, and best practices. We'll focus on techniques usable within the 1.40 version of MediaWiki, though many concepts apply across versions.
- Why is Data Validation Important?
Imagine a wiki dedicated to stock market analysis. If users can freely enter data for stock prices without validation, you could quickly end up with incorrect information, leading to flawed analysis and potentially harmful investment decisions. This illustrates the core importance of data validation. Here's a more detailed breakdown:
- **Data Accuracy:** Validation guarantees that information is factually correct and consistent with expected values. Incorrect data leads to inaccurate reports, misleading conclusions, and distrust in the wiki's content. Consider the impact of incorrect data on Technical Analysis indicators like Moving Averages or Relative Strength Index (RSI).
- **Data Integrity:** Maintaining the structural soundness of data is crucial. Validation prevents the insertion of data that violates database constraints or disrupts the wiki’s logical organization. For example, preventing a negative value for a stock's volume.
- **Security:** Data validation is a fundamental security measure. It helps prevent malicious attacks such as SQL injection, where attackers try to manipulate the database through user input. By carefully scrutinizing input, you can block potentially harmful code from being executed. Think about preventing users from inserting HTML or JavaScript code into fields meant for plain text.
- **Usability:** Validation provides immediate feedback to users, guiding them to enter data correctly. Clear error messages and input masks improve the user experience and reduce frustration. A well-validated form is easier to use than one that accepts anything.
- **Compliance:** Depending on the wiki’s purpose and the data it stores, compliance with specific regulations (e.g., data privacy laws) may be required. Data validation helps ensure that data collection and storage practices meet these requirements.
- **Report Reliability:** Accurate data is the foundation of reliable reports. If the data feeding your reports is flawed, the reports themselves will be unreliable. Consider the impact on Elliott Wave Theory analysis if the underlying price data is incorrect.
- Methods of Data Validation in MediaWiki
MediaWiki offers several methods for implementing data validation, ranging from simple built-in features to more complex extensions and custom scripting.
- 1. Form Input Types and Attributes (HTML5)
The primary method for front-end data validation relies on HTML5 input types and attributes. While MediaWiki doesn't directly control the rendered HTML, it allows you to utilize these features within forms created using the `<form>` tag and input fields.
- **`type` attribute:** Specifies the type of input expected. Common types include:
* `text`: For general text input. * `number`: For numeric values. Can be combined with `min` and `max` attributes. * `email`: Validates email addresses. * `url`: Validates URLs. * `date`: For dates (requires browser support). * `checkbox`: For boolean values. * `radio`: For selecting one option from a set.
- **`required` attribute:** Forces the user to fill in the field before submitting the form.
- **`pattern` attribute:** Allows you to define a regular expression that the input must match. This is extremely powerful for complex validation rules. For instance, you could use a pattern to ensure a stock ticker symbol follows a specific format.
- **`min` and `max` attributes:** Specify the minimum and maximum allowed values for numeric inputs.
- **`step` attribute:** Specifies the legal number intervals for numeric inputs.
- **`placeholder` attribute:** Provides a hint to the user about the expected input format.
- Example:**
```wiki <form action="...">
<label for="stock_price">Stock Price:</label> <input type="number" id="stock_price" name="stock_price" min="0" step="0.01" required pattern="[0-9.]+" placeholder="Enter price (e.g., 123.45)"> <input type="submit" value="Submit">
</form> ```
This example validates that the stock price is a number, greater than or equal to zero, with a decimal precision of two, and requires the field to be filled. The `pattern` attribute ensures only digits and periods are allowed. This complements Candlestick patterns when analyzing price movements.
- 2. Extension: Validation
The Extension:Validation extension provides a more robust and flexible framework for data validation in MediaWiki. It allows you to define validation rules in a centralized configuration and apply them to form fields. This is particularly useful for complex validation scenarios.
- **Rule Definition:** Validation rules are defined using a specific syntax, allowing you to specify conditions for acceptable input.
- **Error Handling:** The extension provides customizable error messages that are displayed to the user when validation fails.
- **Integration with Forms:** Validation rules are applied to form fields using special attributes or tags.
- **Extensibility:** You can extend the extension with custom validation rules to meet specific needs.
- Installation:**
1. Download the extension from the Extension:Validation page. 2. Place the extension files in the `extensions/` directory of your MediaWiki installation. 3. Add `wfLoadExtension( 'Validation' );` to your `LocalSettings.php` file. 4. Configure the extension through its configuration file.
- 3. Scribunto and Lua Scripting
Scribunto allows you to embed Lua scripts within your wiki. This provides a powerful mechanism for implementing custom data validation logic. Lua scripts can access and manipulate form data before it is submitted to the database.
- **Server-Side Validation:** Lua scripts execute on the server, providing a more secure and reliable validation layer than client-side validation.
- **Complex Logic:** Lua allows you to implement sophisticated validation rules that are difficult or impossible to achieve with HTML5 attributes or the Validation extension. For example, you could validate that a stock ticker symbol exists in a predefined list or that a trading signal aligns with specific Fibonacci retracement levels.
- **Database Interaction:** Lua scripts can interact with the MediaWiki database to perform more complex validation checks.
- Example (Conceptual):**
```lua -- Lua script to validate a stock ticker symbol local stock_ticker = mw.text.unescape(mw.form.get('stock_ticker')) local valid_tickers = { 'AAPL', 'GOOG', 'MSFT', 'AMZN' } -- Example list
if not stock_ticker or table.find(valid_tickers, stock_ticker) == nil then
mw.addError("Invalid stock ticker symbol. Please choose from: " .. table.concat(valid_tickers, ", ")) return
end ```
- 4. Hooks and Custom Code
MediaWiki provides a system of Hooks that allow you to intercept and modify various events within the wiki's workflow. You can use hooks to implement custom data validation logic.
- **`FormEditContentHandler::validateForm` hook:** Allows you to validate data submitted through forms.
- **`ArticleSavePreprocess` hook:** Allows you to validate the content of an article before it is saved.
This method requires more advanced programming skills in PHP, as you'll be directly interacting with the MediaWiki core.
- Best Practices for Data Validation
- **Client-Side and Server-Side Validation:** Implement both client-side (HTML5 attributes) and server-side (Lua, Hooks) validation. Client-side validation provides immediate feedback to the user, while server-side validation ensures data integrity. Never rely solely on client-side validation, as it can be bypassed.
- **Clear Error Messages:** Provide clear, concise, and informative error messages that tell the user exactly what went wrong and how to fix it. Avoid technical jargon.
- **Input Masks:** Use input masks to guide the user to enter data in the correct format.
- **Regular Expressions:** Master the use of regular expressions for complex validation patterns. Tools like Regex101 can help you build and test your expressions.
- **Data Sanitization:** In addition to validation, sanitize user input to remove potentially harmful characters or code. Use functions like `mw.text.escape()` in Lua.
- **Whitelisting:** Whenever possible, use whitelisting instead of blacklisting. Specify the acceptable values or formats, rather than trying to block all invalid ones. For example, provide a dropdown list of allowed stock exchanges instead of trying to validate the exchange name.
- **Testing:** Thoroughly test your validation rules to ensure they work as expected and don’t introduce unintended side effects. Consider edge cases and boundary conditions.
- **Documentation:** Document your validation rules and logic for future maintenance and troubleshooting.
- **Consider Data Types:** Ensure data is stored in appropriate data types within the database. Using the correct data type can prevent errors and improve performance. For example, use numeric types for stock prices and dates for transaction timestamps.
- **Use Established Financial Indicators:** When validating data related to financial analysis, consider established indicators. Validate that data aligns with expected ranges for indicators like Bollinger Bands, MACD, and Stochastic Oscillator.
- **Monitor Market Trends:** Validation rules may need to be adjusted based on changing market conditions and trends. Stay informed about current market dynamics and update your validation accordingly. Tools like TradingView can help with this.
- Conclusion
Data validation is a cornerstone of a reliable and secure MediaWiki installation. By implementing appropriate validation methods and following best practices, you can ensure the accuracy, integrity, and usability of your wiki's data. Remember to choose the validation techniques that best suit your needs and the complexity of your data. Investing in data validation upfront will save you time and effort in the long run.
Help:Forms Help:Extension installation Help:Scribunto Help:Hooks MediaWiki configuration Database administration Regular expressions SQL injection Security best practices Data privacy == Start Trading Now == Sign up at IQ Option (Minimum deposit $10) Open an account at Pocket Option (Minimum deposit $5)
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