| Name | smpl-logger JSON |
| Version |
0.1.5
JSON |
| download |
| home_page | None |
| Summary | A simple logging library with colored output and file rotation support |
| upload_time | 2025-08-11 11:21:56 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.6 |
| license | None |
| keywords |
logging
logger
colored
rotation
python
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# SiMPLe Logger
A simple logging library with colored output and file rotation support
## Installation
```bash
pip install smpl-logger
```
Or install from source:
```bash
pip install git+https://github.com/greengoblinalex/simple-logger.git
```
## Usage
```python
from smpl_logger import get_logger
# It is recommended to use __name__ as the logger name —
# this is convenient for structuring logs in large projects
logger = get_logger(__name__)
# You can also explicitly pass a string, for example:
# logger = get_logger("my_app")
logger.info("This is an info message")
logger.error("This is an error message")
# Logging to file and console
file_logger = get_logger(__name__, log_file="app.log")
file_logger.info("This message will appear in both file and console")
```
## Configuration
You can configure the logger using additional parameters:
```python
logger = get_logger(
name=__name__, # Recommended to use __name__, but you can use a string
log_file="app.log",
level="DEBUG", # Logging level
rotation_size=5 * 1024 * 1024, # 5 MB for rotation
backup_count=3 # Keep 3 backup files
)
```
## Configuration via .env file
You can also configure logging parameters via a `.env` file in your project root:
```
LOG_DIR=logs # Directory for log files
LOG_LEVEL=INFO # Logging level
LOG_ROTATION_SIZE=5242880 # File size for rotation (5MB)
LOG_BACKUP_COUNT=3 # Number of backup files
```
## Features
- 🎨 **Colored output** - different log levels are highlighted with different colors
- 🔄 **File rotation** - automatic log rotation when the file reaches the maximum size
- ⚙️ **Flexible configuration** - configure via function parameters or environment variables
- 📦 **Lightweight** - no external dependencies, uses only the Python standard library
- 🔧 **Easy to use** - minimal code to get started
## Example of colored output
When using console logging, you will see:
- 🟢 **INFO** - green for informational messages
- 🟡 **WARNING** - yellow for warnings
- 🔴 **ERROR** - red for errors
- 🔵 **DEBUG** - cyan for debug information
- 🟥 **CRITICAL** - red background for critical errors
Raw data
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