Encapsulating Log Recording in Pytest: Date-Based Log Files, Colored Levels, and Utility Functions

In interface automation testing, logging is essential for tracing execution, debugging, and analyzing results; this article explains how to encapsulate logging in the Pytest framework, including daily log file rotation and colored log levels for clearer console output.

Logging encapsulation goals : generate a separate log file for each day, assign distinct colors to different log levels, and allow flexible configuration of log level and format.

Implementation steps :

(1) Import logging libraries :

import logging
import colorlog
from datetime import datetime
import os

(2) Define a logger : logger = logging.getLogger(__name__) (3) Configure the logger – set up a log‑color map, create a logs directory, build a filename based on the current date, and create file and console handlers with appropriate formatters:

# Log color configuration
log_colors_config = {
    'DEBUG': 'cyan',
    'INFO': 'green',
    'WARNING': 'yellow',
    'ERROR': 'red',
    'CRITICAL': 'bold_red',
}

log_path = os.path.join(os.path.dirname(__file__), 'logs')
if not os.path.exists(log_path):
    os.mkdir(log_path)

log_file_name = datetime.now().strftime("%Y-%m-%d") + '.log'
log_file_path = os.path.join(log_path, log_file_name)

file_handler = logging.FileHandler(log_file_path, mode='a', encoding='utf-8')
file_formatter = logging.Formatter('[%(asctime)s] %(filename)s -> %(funcName)s line:%(lineno)d [%(levelname)s] : %(message)s', datefmt='%Y-%m-%d %H:%M:%S')
file_handler.setFormatter(file_formatter)

console_handler = logging.StreamHandler()
console_formatter = colorlog.ColoredFormatter('%(log_color)s[%(asctime)s] %(filename)s -> %(funcName)s line:%(lineno)d [%(levelname)s] : %(message)s', datefmt='%Y-%m-%d %H:%M:%S', log_colors=log_colors_config)
console_handler.setFormatter(console_formatter)

logger.setLevel(logging.DEBUG)
console_handler.setLevel(logging.DEBUG)
file_handler.setLevel(logging.INFO)
logger.addHandler(console_handler)
logger.addHandler(file_handler)

(4) Wrap logging calls in a utility class :

class ApiLog:
    @staticmethod
    def debug(message):
        logger.debug(message)

    @staticmethod
    def info(message):
        logger.info(message)

    @staticmethod
    def warning(message):
        logger.warning(message)

    @staticmethod
    def error(message):
        logger.error(message)

    @staticmethod
    def critical(message):
        logger.critical(message)

(5) Use the wrapper in test cases :

def test_example():
    ApiLog.info("测试开始")
    ApiLog.debug("执行测试步骤")
    ApiLog.warning("这是一个警告")
    ApiLog.error("这是一个错误")
    ApiLog.critical("这是一个严重错误")

By following these steps, developers can integrate a robust, color‑enhanced logging system into their Pytest‑based API automation framework, improving readability, maintainability, and debugging efficiency.