logfunc 1.7.0

An EASY TO USE function decorator for advanced logging of function execution, including arguments, return values, and execution time.

logfunc - @logf()

CURRENT VERSION: v1.7.0 | Last Change: Fixed Async exec time calc bug

@logf() is a Python decorator designed for uncomplicated and immediate addition of logging to functions. Its main goal is to provide developers with a tool that can be added quickly to any function and left in place without further adjustments.

I originally made @logf() for my own use, but I hope it can be useful to others as well.

Highlights

• Async Support: Incorporated from version 1.6 onwards.
• Broad Python 3 Compatibility: Designed to work seamlessly across multiple Python 3 versions.
• Effortless Logging: Implement logging without disrupting the flow of your code.
• Leave-and-Forget: Once integrated, no further adjustments are needed.
• Encourages Logic Compartmentalization.
• Customizable: Numerous settings available for tailoring logging behavior to specific needs.
• Environment Variables: Overriding default settings made easy with environment variables.

Usage

Installation

To integrate @logf() into your projects:

pip install logfunc

Importing

Simply import the decorator to start using it:

from logfunc import logf

Basic Usage

Apply the @logf() decorator to functions you intend to log:

from logfunc import logf

@logf()
def concatenate_strings(str1: str, str2: str) -> str:
    return str1 + str2

This setup ensures automatic logging of function name, parameters, return values, and execution time.

@logf() args

• level: Set the log level (DEBUG, INFO, WARNING, etc.).
• log_args & log_return: Control whether to log arguments and return values.
• max_str_len: Limit the length of logged strings.
• log_exec_time: Option to log the execution time.
• single_msg: Consolidate all log data into a single message.
• use_print: Choose to print() log messages instead of using standard logging.

Environment Variables

Modify the behavior of @logf() using environment variables:

Env Var	Example Values
LOGF_LEVEL	DEBUG, INFO, WARNING
LOGF_MAX_STR_LEN	10, 50, 10000000
LOGF_SINGLE_MSG	True, False
LOGF_USE_PRINT	True, False

Real-world Examples

To demonstrate its practicality, here are a few scenarios where @logf() can be beneficial:

from logfunc import logf


# Database operations
@logf(level='ERROR')
def db_insert(item):
    # Insert item into database
    pass

# Asynchronous tasks in an application
@logf()
async def fetch_data(url):
    # Fetch data from URL asynchronously
    return data

Testing

To ensure reliability, @logf() comes equipped with a test suite. To run the tests:

python tests.py

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue.

License

MIT

Contact

[e-mail]