数据库发生错误。

"""
Verify Module - Handles verification checks.
Used for verifying standby container configuration and reporting problems.
"""
import re
import sys
from ..base import BaseExporter
from ..utils import run_command_silent, parse_json_silent, debug_log


class CustomExporter(BaseExporter):
    """
    Exporter for verification checks.
    Runs verification checks and reports metrics on problems found.
    """
    def metric_config(self):
        """Define metrics for verification checks"""
        return {
            "dp_hactl_verify_problems_total": {"type": "Gauge", "labels": ["machine"]},
            "dp_hactl_verify_problem_details": {"type": "Gauge", "labels": ["machine", "problem"]},
        }

    def generate(self):
        """Run all verification checks and collect metrics"""
        try:
            self._check_verify()
        except Exception:
            # Exit silently on any exception
            sys.exit(1)

    def _categorize_problem(self, problem_text):
        """Categorize the problem based on the text"""
        # Extract the specific problem type from the message
        if "nginx.conf does not exist" in problem_text:
            return "missing_nginx_conf"
        elif "vhosts/*.conf does not exist" in problem_text:
            return "missing_vhost_conf"
        elif "php-fpm.d/*.conf does not exist" in problem_text:
            return "missing_php_fpm_conf"
        elif "systemd unit is not enabled" in problem_text:
            return "systemd_unit_not_enabled"
        else:
            # For any other problems, use a sanitized version of the text
            # Ensure the result follows Prometheus label naming rules
            # Must match regex [a-zA-Z_][a-zA-Z0-9_]*
            
            # Convert to lowercase and replace all non-alphanumeric chars with underscore
            sanitized = re.sub(r'[^a-z0-9_]', '_', problem_text.lower())
            
            # Ensure it starts with a letter or underscore
            if sanitized and not sanitized[0].isalpha() and sanitized[0] != '_':
                sanitized = 'p_' + sanitized
            
            # Handle empty string case
            if not sanitized:
                sanitized = 'unknown_problem'
                
            # Remove consecutive underscores
            sanitized = re.sub(r'_+', '_', sanitized)
            
            # Truncate if too long
            if len(sanitized) > 50:
                sanitized = sanitized[:50]
                
            return sanitized

    def _check_verify(self):
        """Check the output of dp-ha-ctl verify"""
        verify_problems_metric = self.metrics.get("dp_hactl_verify_problems_total")
        verify_problem_details_metric = self.metrics.get("dp_hactl_verify_problem_details")
        
        debug_log("Running dp-ha-ctl verify check")
        
        # Run the command using the silent utility that handles errors
        result = run_command_silent(
            ["dp-ha-ctl", "--format", "json", "verify"],
            timeout=30
        )
        
        # If we get here, the command executed successfully
        
        if result.stdout.strip() in ["All clear", "[]"]:
            debug_log("No problems found in verify check")
            # No problems found - skip setting metric entirely
            return
        
        # Parse the JSON output using the silent utility
        problems = parse_json_silent(result.stdout)
            
        # Process the problems found and set metrics
        for problem in problems:
            machine = problem.get("container", "unknown")
            problem_list = problem.get("problems", [])
            problem_count = len(problem_list)
            
            # Set the total count for this machine
            verify_problems_metric.labels(machine=machine).set(problem_count)
            
            # Process each specific problem
            problem_types = {}
            for problem_text in problem_list:
                # Extract problem type from the message
                problem_type = self._categorize_problem(problem_text)
                
                # Count occurrences of each problem type
                if problem_type in problem_types:
                    problem_types[problem_type] += 1
                else:
                    problem_types[problem_type] = 1
            
            # Set metrics for each problem type
            for problem_type, count in problem_types.items():
                verify_problem_details_metric.labels(
                    machine=machine, 
                    problem=problem_type
                ).set(count)