hotlog 0.0.4

cli loggging utilities

hotlog

Generalized logging utility for Python projects

Overview

hotlog provides a simple, flexible, and structured logging interface for Python applications and libraries. It wraps structlog and rich to offer:

• Three-level verbosity system for controlling output detail
• Rich colored output with YAML-formatted context
• Live logging support for dynamic status updates (at default level)
• Context-aware logging with prefix-based filtering (_verbose_, _debug_)
• Unified API: from hotlog import get_logger, configure_logging
• Works seamlessly in CLI tools, scripts, and libraries

Features

Three Verbosity Levels

• Level 0 (default): Essential info only, supports live updates that disappear
• Level 1 (-v): More context visible, includes _verbose_ prefixed keys
• Level 2 (-vv): All debug info, includes _debug_ prefixed keys, no live updates

Prefix Filtering

Control which context appears at different verbosity levels by using key prefixes:

• Regular keys (no prefix): Always shown at all levels
• _verbose_key: Only shown at level 1 (-v) or 2 (-vv)
• _debug_key: Only shown at level 2 (-vv)

The prefixes are automatically removed when displayed, so _verbose_source becomes source.

logger.info(
    "Processing dataset",
    records=1000,                    # Always shown
    _verbose_source="data.csv",      # Only at -v or -vv
    _debug_file_size="2.5MB"         # Only at -vv
)

No special configuration needed - just prefix your keys and hotlog handles the rest!

Custom Log Matchers

Configure custom formatting rules for specific log patterns using matchers. Matchers check if a log entry matches certain conditions and apply custom formatting.

Built-in Matchers

ToolMatch: Format tool execution logs (toolbelt style)

from hotlog import configure_logging, get_logger, ToolMatch

# Configure with ToolMatch
configure_logging(
    verbosity=0,
    matchers=[
        ToolMatch(event="executing", prefix="tb")
    ]
)
logger = get_logger(__name__)

# Automatically formats as: tb[ruff-format] => ruff format .
logger.info(
    "executing",
    command="ruff format .",
    tool="ruff-format",
    _verbose_files_changed=14
)

The ToolMatch matcher checks for:

• Event name: "executing" (configurable)
• Log level: "INFO" (configurable)
• Required key: command
• Optional key: tool (shows in brackets)

Customize the matcher:

ToolMatch(
    event="executing",      # Event name to match
    prefix="pkg",          # Prefix shown before tool name
    level="INFO",          # Log level to match
    command_key="command", # Key containing command
    tool_key="tool"        # Key containing tool name
)

Creating Custom Matchers

Extend LogMatcher to create your own formatting rules:

from hotlog import LogMatcher, configure_logging, get_logger
from structlog.typing import EventDict
from typing import Optional

class InstallMatch(LogMatcher):
    """Custom matcher for package installation logs."""
    
    def matches(self, level: str, event: str, event_dict: EventDict) -> bool:
        """Check if this log entry matches our pattern."""
        return (
            level == "INFO" and
            event == "installed" and
            "package" in event_dict
        )
    
    def format(self, level: str, event: str, event_dict: EventDict) -> Optional[str]:
        """Format matching log entries.
        
        Note: Extract and remove keys you use from event_dict.
        Return None to fall back to default formatting.
        """
        package = event_dict.pop("package")
        version = event_dict.pop("version", "unknown")
        
        return f'[green]✓[/green] Installed [bold]{package}[/bold] [dim](version {version})[/dim]'

# Use your custom matcher
configure_logging(
    verbosity=0,
    matchers=[
        InstallMatch(),
        ToolMatch(event="executing", prefix="pkg"),
    ]
)
logger = get_logger(__name__)

# This will use InstallMatch formatting
logger.info("installed", package="requests", version="2.31.0")

# This will use ToolMatch formatting
logger.info("executing", command="uv pip install requests", tool="uv")

# This will use default formatting
logger.info("Build completed")

Key points about custom matchers:

• Matchers are checked in order - first match wins
• Use event_dict.pop() to remove keys you've formatted
• Return None to fall back to default formatting
• Remaining context keys are shown as YAML below the message
• Rich markup is supported in formatted strings

Rich Output

• Colored log levels (INFO=blue, WARNING=yellow, ERROR=red, DEBUG=magenta)
• YAML-formatted context for easy reading
• Syntax highlighting for structured data
• Clean output without log level prefixes (like uv) - set show_levels=True for traditional [INFO] style

Highlighting Important Information

Emphasize specific values in your messages using Rich markup or the highlight() helper:

from hotlog import get_logger, highlight

logger = get_logger(__name__)

# Option 1: Direct Rich markup
logger.info("Installed [bold]5 packages[/bold] in [bold]3ms[/bold]")

# Option 2: Using highlight() helper
logger.info(highlight("Downloaded {} in {}", "14 files", "2.5s"))
# Renders as: "Downloaded [bold]14 files[/bold] in [bold]2.5s[/bold]"

This is perfect for level 0 summaries where you want to emphasize key metrics while keeping the output clean.

Live Logging

Use the live_logging context manager for operations with progress updates (level 0 only):

with live_logging("Downloading..."):
    # Your operation here
    logger.info("Connected", host="example.com")

Usage

Basic Example

from hotlog import configure_logging, get_logger

# Configure logging (verbosity: 0, 1, or 2)
configure_logging(verbosity=0)
logger = get_logger(__name__)

# Log messages
logger.info("Starting process", task_id=123)
logger.info("Processing data", records=100, _verbose_source="db.sqlite")
logger.warning("Rate limit approaching", current=95, limit=100)

With Different Verbosity Levels

# Level 0: Only essential info
configure_logging(verbosity=0)
logger.info("Processing", items=10, _verbose_detail="xyz", _debug_internals="abc")
# Output: items=10 only

# Level 1: Include verbose context
configure_logging(verbosity=1)
logger.info("Processing", items=10, _verbose_detail="xyz", _debug_internals="abc")
# Output: items=10, detail="xyz"

# Level 2: Include all debug context
configure_logging(verbosity=2)
logger.info("Processing", items=10, _verbose_detail="xyz", _debug_internals="abc")
# Output: items=10, detail="xyz", internals="abc"

Live Logging Example

from hotlog import configure_logging, get_logger, live_logging
import time

configure_logging(verbosity=0)
logger = get_logger(__name__)

with live_logging("Downloading repository..."):
    time.sleep(1)
    logger.info("Connected to server")
    time.sleep(1)
    logger.info("Fetching metadata")
    
logger.info("Download completed")

CLI Integration

import argparse
from hotlog import configure_logging, get_logger

parser = argparse.ArgumentParser()
parser.add_argument('-v', '--verbose', action='count', default=0)
args = parser.parse_args()

# Map -v/-vv to verbosity levels
configure_logging(verbosity=min(args.verbose, 2))
logger = get_logger(__name__)

Installation

# Install dependencies (adjust based on your package manager)
pip install structlog rich pyyaml

Why hotlog?

Hotlog standardizes logging across multiple projects and CLIs, making it easy to:

• Provide consistent verbosity control
• Display beautiful, readable logs
• Handle live updates for better UX
• Filter context based on user's needs
• Customize log formatting with matchers

No more reinventing logging configuration for every project!

Examples

See the example_*.py files for more usage patterns:

• example_quickstart.py - Comprehensive quick start guide
• example_cli.py - Full CLI simulation
• example_toolbelt.py - Tool execution logging with ToolMatch
• example_custom_matcher.py - Creating custom matchers
• example_highlight.py - Using highlight() and Rich markup
• example_prefixes.py - Prefix filtering demonstration

Run examples with different verbosity levels:

python example_toolbelt.py      # Level 0 (default)
python example_toolbelt.py -v   # Level 1 (verbose)
python example_toolbelt.py -vv  # Level 2 (debug)