106 lines
2.3 KiB
Markdown
106 lines
2.3 KiB
Markdown
# Logging and Monitoring Tools
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This document explains how to use the logging and monitoring tools in this project for effective development and troubleshooting.
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## Log File Specification
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When running the application, you can specify a custom log file name using the `--log-file` parameter:
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```
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python train_rl_with_realtime.py --episodes 1 --no-train --visualize-only --log-file custom_log_name.log
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```
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This makes it easier to identify specific log files for particular runs during development.
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## Log Reader Utility
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The `read_logs.py` script provides a convenient way to read and filter log files:
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### List all log files
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To see all available log files sorted by modification time:
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```
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python read_logs.py --list
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```
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### Read a specific log file
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To read the last 50 lines of a specific log file:
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```
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python read_logs.py --file your_log_file.log
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```
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If you don't specify a file, it will use the most recently modified log file.
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### Filter log content
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To only show lines containing specific text:
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```
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python read_logs.py --file your_log_file.log --filter "trade"
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```
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### Follow log updates in real-time
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To monitor a log file as it grows (similar to `tail -f` in Unix):
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```
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python read_logs.py --file your_log_file.log --follow
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```
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You can also combine filtering with following:
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```
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python read_logs.py --file your_log_file.log --filter "ERROR" --follow
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```
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## Startup Scripts
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### Windows Batch Script
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The `start_app.bat` script starts the application with log monitoring in separate windows:
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```
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start_app.bat
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```
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This will:
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1. Start the application with a timestamped log file
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2. Open a log monitoring window
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3. Open the dashboard in your default browser
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### PowerShell Script
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The `StartApp.ps1` script offers a more advanced monitoring experience:
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```
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.\StartApp.ps1
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```
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This will:
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1. Start the application in the background
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2. Open the dashboard in your default browser
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3. Show log output in the current window with colored formatting
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4. Provide instructions for managing the background application job
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## Common Log Monitoring Patterns
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### Monitor for errors
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```
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python read_logs.py --filter "ERROR|Error|error" --follow
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```
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### Watch trading activity
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```
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python read_logs.py --filter "trade|position|BUY|SELL" --follow
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```
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### Monitor performance metrics
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```
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python read_logs.py --filter "reward|balance|PnL|win rate" --follow
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``` |