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关于python:翻译实用的Python编程0802Logging

jiezi

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8.2 日志

本节对日志模块（logging module）进行简略的介绍。

logging 模块

logging 模块是用于记录诊断信息的 Python 规范库模块。日志模块十分宏大，具备许多简单的性能。咱们将会展现一个简略的例子来阐明其用途。

再探异样

在本节练习中，咱们创立这样一个 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，咱们应该做什么？

应该打印正告音讯（warning message）？

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

还是默默疏忽正告音讯？

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

任何一种形式都无奈令人满意，通常状况下，两种形式咱们都须要（用户可选）。

应用 logging

logging 模块能够解决这个问题：

# 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)

批改代码以使程序可能遇到问题的时候收回正告音讯，或者非凡的 Logger 对象。Logger 对象应用 logging.getLogger(__name__) 创立。

日志根底

创立一个记录器对象（logger object）。

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

收回日志音讯：

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

不同办法代表不同级别的严重性。

所有的办法都创立格式化的日志音讯。args 和 % 运算符 一起应用以创立音讯。

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：程序启动后无奈重新配置）。该配置与日志调用是离开的。

阐明

日志是能够任意配置的。你能够对日志配置的任何一方面进行调整：如输入文件，级别，音讯格局等等，不用放心对应用日志模块的代码造成影响。

练习

练习 8.2：将日志增加到模块中

在 fileparse.py 中，有一些与异样无关的错误处理，这些异样是由谬误输出引起的。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

请留神收回诊断音讯的 print 语句。应用日志操作来替换这些 print 语句相对来说更简略。请像上面这样批改代码：

# 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

实现批改后，尝试在谬误的数据上应用这些代码：

>>> 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，则只会取得 WARNING 级别以上的日志音讯。输入看起来像简略的打印语句。然而，如果你配置了日志模块，你将会取得无关日志级别，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() 操作的输入。请按以下步骤批改日志级别（译注：因为日志配置是一次性的，所以该操作须要重启命令行窗口）：

>>> 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 级别的日志音讯，敞开其它级别的日志音讯。

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

练习 8.3：向程序增加日志

要增加日志到利用中，你须要某种机制来实现在主模块中初始化日志。其中一种形式应用看起来像上面这样的代码：

# 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)
)

再次阐明，你须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 程序里的什么地位？

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注：残缺翻译见 https://github.com/codists/practical-python-zh

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