# Diagnosing Problems with Dataphyre

**Overview**  
Dataphyre is designed to handle failures gracefully and only fail when necessary, aiming to keep your applications functional even under stress. Instead of using exceptions extensively, Dataphyre relies on custom logging mechanisms and planned fallback behaviors to ensure uninterrupted operations. This document outlines the steps for diagnosing issues within Dataphyre, understanding its various failure modes, and leveraging built-in tools to track and resolve problems.

---

## 1. Understanding Dataphyre's Failure Modes
Dataphyre is equipped with multiple failure modes that trigger specific responses based on the type and severity of the issue:

- **Safemode**: Activates when Dataphyre encounters conditions that immediately disrupts application functionality.
- **Maintenance**: Enables when the application is undergoing maintenance or updates. This mode can be toggled manually or triggered by a detected condition.
- **Country Blocked**: Occurs when access is restricted based on geographic or IP-based rules.

In each of these states, Dataphyre displays an error page to the user, along with a dynamically generated QR code containing an error code. This error code is specific to the application and can be cross-referenced to retrieve detailed diagnostics, preventing unintended exposure of failure details to end-users.

## 2. Accessing Error Logs
Dataphyre maintains detailed logs of all errors and execution paths to facilitate efficient debugging. Key log types and locations include:

- **Exception and Runtime Error Logs**: When an exception or runtime error occurs, Dataphyre catches it and displays a custom error page. All errors are logged to a file that rolls over every hour. These files can be accessed via:
  - The default router configuration at `/dataphyre/logs`
  - The "logs" folder within the application's root directory

- **Trace Logs**: Dataphyre’s tracelog module captures every function call and conditional operation throughout code execution paths. This comprehensive trace provides a real-time view of execution flow, without the need for modifying code specifically for debugging. This can be invaluable in isolating where and why specific operations fail.

## 3. Using Safe Mode Diagnostics
In safemode, maintenance, or country_blocked states, Dataphyre displays an error page and generates a QR code containing an error identifier. This identifier is dynamically created and unique to the specific failure mode. To diagnose this type of error:

1. **Scan the QR Code or Note the Error Code**: Each QR code or error code is unique and can be cross-referenced to quickly find the underlying issue.
2. **Cross-Reference with Known Error Conditions**: Access the `/cache/known_error_conditions.json` file in the application's directory. This file contains a structured list of known error codes, which map to details such as the:
   - **Error string**: Describes the specific error condition
   - **Error type**: Specifies the nature of the error
   - **File, Function, and Class Names**: Provide the exact locations of the issue within the codebase

Using this file allows developers to quickly pinpoint the cause of common issues without extensive investigation.

## 4. Tracelog Module for Execution Flow Analysis
The tracelog module is designed to capture and log every function call and conditional operation within the framework and application code execution paths. This robust logging system can be used to:

- Examine the real-time flow of code execution for various scenarios
- Isolate specific operations or conditions that may be causing unintended behaviors
- Debug without needing to refactor code explicitly for diagnostics

By analyzing the trace logs, you can identify where and why specific code paths are failing, allowing you to resolve issues at the source.

## 5. Custom Error Pages and Error Handling
Dataphyre provides custom error pages for exceptions and runtime errors, logging each instance to assist with post-failure analysis. Key points about error handling:

- **Graceful Fallbacks**: Dataphyre is designed to handle minor issues with fallback mechanisms, maintaining application stability whenever possible.
- **Controlled Exception Management**: Exceptions are caught and logged rather than triggering application termination, allowing developers to address issues without impacting the end-user experience.

## 6. Best Practices for Diagnosing Dataphyre
- **Regularly Check Logs**: Since logs roll over hourly, frequent checks can help you catch patterns and prevent issues before they impact users.
- **Leverage QR Codes in Safe Modes**: The QR codes in safemode, maintenance, and country_blocked states provide direct access to error codes, making it easier to diagnose specific issues.
- **Use Trace Logs for Complex Debugging**: When facing intricate bugs, tracing the execution path can offer insights without needing to refactor or modify your code base.