cef6903cbc
Phase 2.5: Fix Foundation (CRITICAL) - Fixed 4 failing tests by adding cache attribute to mock_client fixture - Created comprehensive cache tests for Pages endpoint (test_pages_cache.py) - Added missing dependencies: pydantic[email] and aiohttp to core requirements - Updated requirements.txt with proper dependency versions - Achieved 82.67% test coverage with 454 passing tests Phase 2.6: Production Essentials - Implemented structured logging (wikijs/logging.py) * JSON and text log formatters * Configurable log levels and output destinations * Integration with client operations - Implemented metrics and telemetry (wikijs/metrics.py) * Request tracking with duration, status codes, errors * Latency percentiles (min, max, avg, p50, p95, p99) * Error rate calculation * Thread-safe metrics collection - Implemented rate limiting (wikijs/ratelimit.py) * Token bucket algorithm for request throttling * Per-endpoint rate limiting support * Configurable timeout handling * Burst capacity management - Created SECURITY.md policy * Vulnerability reporting procedures * Security best practices * Response timelines * Supported versions Documentation - Added comprehensive logging guide (docs/logging.md) - Added metrics and telemetry guide (docs/metrics.md) - Added rate limiting guide (docs/rate_limiting.md) - Updated README.md with production features section - Updated IMPROVEMENT_PLAN_2.md with completed checkboxes Testing - Created test suite for logging (tests/test_logging.py) - Created test suite for metrics (tests/test_metrics.py) - Created test suite for rate limiting (tests/test_ratelimit.py) - All 454 tests passing - Test coverage: 82.67% Breaking Changes: None Dependencies Added: pydantic[email], email-validator, dnspython 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
121 lines
2.3 KiB
Markdown
121 lines
2.3 KiB
Markdown
# Metrics and Telemetry Guide
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## Overview
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The wikijs-python-sdk includes built-in metrics collection for monitoring performance and reliability.
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## Basic Usage
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```python
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from wikijs import WikiJSClient
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# Create client with metrics enabled (default)
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client = WikiJSClient(
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"https://wiki.example.com",
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auth="your-api-key",
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enable_metrics=True
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)
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# Perform operations
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pages = client.pages.list()
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page = client.pages.get(123)
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# Get metrics
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metrics = client.get_metrics()
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print(f"Total requests: {metrics['total_requests']}")
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print(f"Error rate: {metrics['error_rate']:.2f}%")
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print(f"Avg latency: {metrics['latency']['avg']:.2f}ms")
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print(f"P95 latency: {metrics['latency']['p95']:.2f}ms")
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```
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## Available Metrics
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### Counters
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- `total_requests`: Total API requests made
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- `total_errors`: Total errors (4xx, 5xx responses)
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- `total_server_errors`: Server errors (5xx responses)
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### Latency Statistics
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- `min`: Minimum request duration
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- `max`: Maximum request duration
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- `avg`: Average request duration
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- `p50`: 50th percentile (median)
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- `p95`: 95th percentile
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- `p99`: 99th percentile
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### Error Rate
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- Percentage of failed requests
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## Example Output
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```python
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{
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"total_requests": 150,
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"total_errors": 3,
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"error_rate": 2.0,
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"latency": {
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"min": 45.2,
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"max": 523.8,
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"avg": 127.3,
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"p50": 98.5,
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"p95": 312.7,
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"p99": 487.2
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},
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"counters": {
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"total_requests": 150,
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"total_errors": 3,
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"total_server_errors": 1
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},
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"gauges": {}
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}
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```
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## Advanced Usage
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### Custom Metrics
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```python
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from wikijs.metrics import get_metrics
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metrics = get_metrics()
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# Increment custom counter
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metrics.increment("custom_operation_count", 5)
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# Set gauge value
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metrics.set_gauge("cache_hit_rate", 87.5)
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# Get statistics
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stats = metrics.get_stats()
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```
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### Reset Metrics
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```python
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metrics = get_metrics()
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metrics.reset()
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```
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## Monitoring Integration
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Metrics can be exported to monitoring systems:
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```python
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import json
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# Export metrics as JSON
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metrics_json = json.dumps(client.get_metrics())
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# Send to monitoring service
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# send_to_datadog(metrics_json)
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# send_to_prometheus(metrics_json)
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```
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## Best Practices
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1. Monitor error rates regularly
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2. Set up alerts for high latency (p95 > threshold)
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3. Track trends over time
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4. Reset metrics periodically
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5. Export to external monitoring systems
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