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8.2 日志

本节对日志模块(logging module)进行简单的介绍。

logging 模块

logging 模块是用于记录诊断信息的 Python 标准库模块。日志模块非常庞大,具有许多复杂的功能。我们将会展示一个简单的例子来说明其用处。

再探异常

在本节练习中,我们创建这样一个 parse() 函数:

# fileparse.py
def parse(f, types=None, names=None, delimiter=None):
    records = []
    for line in f:
        line = line.strip()
        if not line: continue
        try:
            records.append(split(line,types,names,delimiter))
        except ValueError as e:
            print("Couldn't parse :", line)
            print("Reason :", e)
    return records

请看到 try-except 语句,在 except 块中,我们应该做什么?

应该打印警告消息(warning message)?

try:
    records.append(split(line,types,names,delimiter))
except ValueError as e:
    print("Couldn't parse :", line)
    print("Reason :", e)

还是默默忽略警告消息?

try:
    records.append(split(line,types,names,delimiter))
except ValueError as e:
    pass

任何一种方式都无法令人满意,通常情况下,两种方式我们都需要(用户可选)。

使用 logging

logging 模块可以解决这个问题:

# fileparse.py
import logging
log = logging.getLogger(__name__)

def parse(f,types=None,names=None,delimiter=None):
    ...
    try:
        records.append(split(line,types,names,delimiter))
    except ValueError as e:
        log.warning("Couldn't parse : %s", line)
        log.debug("Reason : %s", e)

修改代码以使程序能够遇到问题的时候发出警告消息,或者特殊的 Logger 对象。 Logger 对象使用 logging.getLogger(__name__) 创建。

日志基础

创建一个记录器对象(logger object)。

log = logging.getLogger(name)   # name is a string

发出日志消息:

log.critical(message [, args])
log.error(message [, args])
log.warning(message [, args])
log.info(message [, args])
log.debug(message [, args])

不同方法代表不同级别的严重性。

所有的方法都创建格式化的日志消息。args% 运算符 一起使用以创建消息。

logmsg = message % args # Written to the log

日志配置

配置:

# main.py

...

if __name__ == '__main__':
    import logging
    logging.basicConfig(
        filename  = 'app.log',      # Log output file
        level     = logging.INFO,   # Output level
    )

通常,在程序启动时,日志配置是一次性的(译注:程序启动后无法重新配置)。该配置与日志调用是分开的。

说明

日志是可以任意配置的。你可以对日志配置的任何一方面进行调整:如输出文件,级别,消息格式等等,不必担心对使用日志模块的代码造成影响。

练习

练习 8.2:将日志添加到模块中

fileparse.py 中,有一些与异常有关的错误处理,这些异常是由错误输入引起的。如下所示:

# fileparse.py
import csv

def parse_csv(lines, select=None, types=None, has_headers=True, delimiter=',', silence_errors=False):
    '''
    Parse a CSV file into a list of records with type conversion.
    '''
    if select and not has_headers:
        raise RuntimeError('select requires column headers')

    rows = csv.reader(lines, delimiter=delimiter)

    # Read the file headers (if any)
    headers = next(rows) if has_headers else []

    # If specific columns have been selected, make indices for filtering and set output columns
    if select:
        indices = [ headers.index(colname) for colname in select ]
        headers = select

    records = []
    for rowno, row in enumerate(rows, 1):
        if not row:     # Skip rows with no data
            continue

        # If specific column indices are selected, pick them out
        if select:
            row = [ row[index] for index in indices]

        # Apply type conversion to the row
        if types:
            try:
                row = [func(val) for func, val in zip(types, row)]
            except ValueError as e:
                if not silence_errors:
                    print(f"Row {rowno}: Couldn't convert {row}")
                    print(f"Row {rowno}: Reason {e}")
                continue

        # Make a dictionary or a tuple
        if headers:
            record = dict(zip(headers, row))
        else:
            record = tuple(row)
        records.append(record)

    return records

请注意发出诊断消息的 print 语句。使用日志操作来替换这些 print 语句相对来说更简单。请像下面这样修改代码:

# fileparse.py
import csv
import logging
log = logging.getLogger(__name__)

def parse_csv(lines, select=None, types=None, has_headers=True, delimiter=',', silence_errors=False):
    '''
    Parse a CSV file into a list of records with type conversion.
    '''
    if select and not has_headers:
        raise RuntimeError('select requires column headers')

    rows = csv.reader(lines, delimiter=delimiter)

    # Read the file headers (if any)
    headers = next(rows) if has_headers else []

    # If specific columns have been selected, make indices for filtering and set output columns
    if select:
        indices = [ headers.index(colname) for colname in select ]
        headers = select

    records = []
    for rowno, row in enumerate(rows, 1):
        if not row:     # Skip rows with no data
            continue

        # If specific column indices are selected, pick them out
        if select:
            row = [ row[index] for index in indices]

        # Apply type conversion to the row
        if types:
            try:
                row = [func(val) for func, val in zip(types, row)]
            except ValueError as e:
                if not silence_errors:
                    log.warning("Row %d: Couldn't convert %s", rowno, row)
                    log.debug("Row %d: Reason %s", rowno, e)
                continue

        # Make a dictionary or a tuple
        if headers:
            record = dict(zip(headers, row))
        else:
            record = tuple(row)
        records.append(record)

    return records

完成修改后,尝试在错误的数据上使用这些代码:

>>> import report
>>> a = report.read_portfolio('Data/missing.csv')
Row 4: Bad row: ['MSFT', '', '51.23']
Row 7: Bad row: ['IBM', '', '70.44']
>>>

如果你什么都不做,则只会获得 WARNING 级别以上的日志消息。输出看起来像简单的打印语句。但是,如果你配置了日志模块,你将会获得有关日志级别,模块等其它信息。请按以下步骤操作查看:

>>> import logging
>>> logging.basicConfig()
>>> a = report.read_portfolio('Data/missing.csv')
WARNING:fileparse:Row 4: Bad row: ['MSFT', '', '51.23']
WARNING:fileparse:Row 7: Bad row: ['IBM', '', '70.44']
>>>

你会发现,看不到来自于 log.debug() 操作的输出。请按以下步骤修改日志级别(译注:因为日志配置是一次性的,所以该操作需要重启命令行窗口):

>>> logging.getLogger('fileparse').level = logging.DEBUG
>>> a = report.read_portfolio('Data/missing.csv')
WARNING:fileparse:Row 4: Bad row: ['MSFT', '', '51.23']
DEBUG:fileparse:Row 4: Reason: invalid literal for int() with base 10: ''
WARNING:fileparse:Row 7: Bad row: ['IBM', '', '70.44']
DEBUG:fileparse:Row 7: Reason: invalid literal for int() with base 10: ''
>>>

只留下 critical 级别的日志消息,关闭其它级别的日志消息。

>>> logging.getLogger('fileparse').level=logging.CRITICAL
>>> a = report.read_portfolio('Data/missing.csv')
>>>

练习 8.3:向程序添加日志

要添加日志到应用中,你需要某种机制来实现在主模块中初始化日志。其中一种方式使用看起来像下面这样的代码:

# This file sets up basic configuration of the logging module.
# Change settings here to adjust logging output as needed.
import logging
logging.basicConfig(
    filename = 'app.log',            # Name of the log file (omit to use stderr)
    filemode = 'w',                  # File mode (use 'a' to append)
    level    = logging.WARNING,      # Logging level (DEBUG, INFO, WARNING, ERROR, or CRITICAL)
)

再次说明,你需要将日志配置代码放到程序启动步骤中。例如,将其放到 report.py 程序里的什么位置?

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注:完整翻译见 https://github.com/codists/practical-python-zh

04-11 08:59