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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.pydef 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.pyimport logginglog = 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.pyimport csvdef 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.pyimport csvimport logginglog = 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 logginglogging.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