nfo 0.1.12

Automatic function logging with decorators — output to SQLite, CSV, and Markdown

nfo

Automatic function logging with decorators — output to SQLite, CSV, and Markdown.

Zero-dependency Python package that automatically logs function calls using decorators. Captures arguments, types, return values, exceptions, and execution time — writes to SQLite, CSV, or Markdown.

Installation

pip install nfo

Quick Start

from nfo import log_call, catch

@log_call
def add(a: int, b: int) -> int:
    return a + b

@catch
def risky(x: float) -> float:
    return 1 / x

add(3, 7)       # logs: args, types, return value, duration
risky(0)        # logs exception, returns None (no crash)

Output (stderr):

2026-02-11 21:59:34 | DEBUG | nfo | add() | args=(3, 7) | -> 10 | [0.00ms]
2026-02-11 21:59:34 | ERROR | nfo | risky() | args=(0,) | EXCEPTION ZeroDivisionError: division by zero | [0.00ms]

Features

• @log_call — logs entry/exit, args with types, return value, exceptions + traceback, duration
• @catch — like @log_call but suppresses exceptions (returns configurable default)
• SQLiteSink — persist logs to SQLite database
• CSVSink — append logs to CSV file
• MarkdownSink — write human-readable Markdown log files
• Logger — central dispatcher with multiple sinks + optional stdlib logging forwarding
• Zero dependencies — uses only Python standard library
• Thread-safe — all sinks use locks

Sinks

SQLite

from nfo import Logger, log_call, SQLiteSink
from nfo.decorators import set_default_logger

logger = Logger(sinks=[SQLiteSink("logs.db")])
set_default_logger(logger)

@log_call
def fetch_user(user_id: int) -> dict:
    return {"id": user_id, "name": "Alice"}

fetch_user(42)
# Query: SELECT * FROM logs WHERE level = 'ERROR'

CSV

from nfo import Logger, log_call, CSVSink
from nfo.decorators import set_default_logger

logger = Logger(sinks=[CSVSink("logs.csv")])
set_default_logger(logger)

@log_call
def multiply(a: int, b: int) -> int:
    return a * b

multiply(6, 7)

Markdown

from nfo import Logger, log_call, MarkdownSink
from nfo.decorators import set_default_logger

logger = Logger(sinks=[MarkdownSink("logs.md")], propagate_stdlib=False)
set_default_logger(logger)

@log_call
def compute(x: float, y: float) -> float:
    return x ** y

compute(2.0, 10.0)

Multiple Sinks

from nfo import Logger, SQLiteSink, CSVSink, MarkdownSink

logger = Logger(sinks=[
    SQLiteSink("logs.db"),
    CSVSink("logs.csv"),
    MarkdownSink("logs.md"),
])

What Gets Logged

Each @log_call / @catch captures:

Field	Description
timestamp	UTC ISO-8601
level	DEBUG (success) or ERROR (exception)
function_name	Qualified function name
module	Python module
args / kwargs	Positional and keyword arguments
arg_types / kwarg_types	Type names of each argument
return_value / return_type	Return value and its type
exception / exception_type	Exception message and class
traceback	Full traceback on error
duration_ms	Wall-clock execution time

Examples

See the examples/ directory:

• basic_usage.py — @log_call and @catch basics
• sqlite_sink.py — logging to SQLite + querying
• csv_sink.py — logging to CSV
• markdown_sink.py — logging to Markdown
• multi_sink.py — all three sinks at once

Run any example:

pip install nfo
python examples/basic_usage.py

Development

git clone https://github.com/wronai/lg.git
cd lg
python -m venv venv && source venv/bin/activate
pip install -e ".[dev]"
pytest tests/ -v

License

Apache-2.0