loglit

Lightweight logging for Python. One import, no boilerplate.

The idea

You already know print(). Now use log() to write to a file, or printlog() to write to console and file.

  print  →  console only
+ log    →  file only
= printlog → console + file

That's it.

Without loglit — the standard way:

import logging
import os
from datetime import datetime

log_dir = "logs"
os.makedirs(log_dir, exist_ok=True)

logger = logging.getLogger("myapp")
logger.setLevel(logging.DEBUG)

formatter = logging.Formatter("%(asctime)s - %(message)s", datefmt="%d-%m-%Y %H:%M:%S")

console_handler = logging.StreamHandler()
console_handler.setLevel(logging.DEBUG)
console_handler.setFormatter(formatter)

file_handler = logging.FileHandler(
    os.path.join(log_dir, f"log_{datetime.now().strftime('%Y%m%d_%H%M%S')}.log"),
    encoding="utf-8",
)
file_handler.setLevel(logging.DEBUG)
file_handler.setFormatter(formatter)

logger.addHandler(console_handler)
logger.addHandler(file_handler)

logger.info("Hello World")

With loglit:

from loglit import log, printlog

printlog("Hello World")

Same result. Zero setup.

When to use loglit

• Small scripts, bots, automation
• Quick prototyping and debugging
• Projects where setup should be zero

When NOT to use loglit

• Large applications with multiple modules and a central logger
• Complex logging pipelines (filtering, routing, multiple sinks)
• Centralized logging systems (ELK, Datadog, etc.)

For those cases, use Python's built-in logging module directly.

Installation

pip install loglit

Usage

from loglit import log, printlog

log("Only written to the log file.")
printlog("Written to console and log file.")

• log() → writes to log file only (silent)
• printlog() → writes to console and log file

Log files are created automatically with a timestamp per session.

Workflow

Building a new function? Use printlog() — see what's happening live in your console while everything gets saved to the log file.

Function runs stable? Switch to log() — keeps your console clean, the log file still catches everything silently.

Quick debugging? Just use print() — throw it in, check your loop counter, remove it when you're done.

printlog("Connecting to API...")       # developing — I want to see this
log("Connecting to API...")            # stable — just save it quietly
print("i =", i)                        # debugging — temporary, delete later

One word changes. No extra imports, no handler setup, no config files. Just swap the function name and move on.

Configuration

Configuration is optional. Only call configure() if you want to change something:

from loglit import configure, log

configure(log_dir="my_logs", file_prefix="myapp_", file_extension="txt")

log("Done.")
# → Log file: my_logs/myapp_22-03-2026_12-00-00.txt

The filename is built from these parts:

{file_prefix}{file_timestamp}{file_suffix}.{file_extension}
 myapp_       22-03-2026_12-00-00              .txt

All options with their defaults:

Option	Default	Description
log_dir	loglit/logs/	Directory for log files
encoding	utf-8	Log file encoding
log_level	logging.DEBUG	Minimum log level
log_format	%(asctime)s - %(message)s	Log line format
date_format	%d-%m-%Y %H:%M:%S	Timestamp format in log lines
file_prefix	loglit_	Filename prefix
file_suffix	""	Filename suffix (after timestamp)
file_extension	log	File extension
file_timestamp	%d-%m-%Y_%H-%M-%S	Timestamp format in filename

Log Levels

Standard Python log levels work out of the box:

import logging
from loglit import log, printlog

log("Debug info", level=logging.DEBUG)           # file only
printlog("Something happened", level=logging.INFO)  # file + console
printlog("Watch out", level=logging.WARNING)         # file + console
printlog("Something broke", level=logging.ERROR)     # file + console

Examples

See the examples/ folder for ready-to-run scripts:

• basic.py — minimal usage, no configuration
• configured.py — all options customized

License

MIT

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Author: FMJ