Note of 《Effective Python》(第六章)

记得以前上大学的时候, 去图书馆借了一本《代码简洁之道》. 虽然大部分的内容都忘得差不多了, 但里边的一些思想至今还是收益颇深.
最近开始看一本书叫做《Effective Python: 59 Specific Ways to Write Better Python》, 把里边一些印象深刻的东西记录在这篇日志里.
这篇文章记录的是第六章: <>

###Chapter 6: Built-in modules:

• Item 42: Define Function Decorators with functools.wraps.
  主要就是Python中要是用decorator的话, 会有一些小问题.
  比如用一个helper去装饰fibonacci函数提高性能的话, help(fibonacci)显示的是decorator的信息.
  我写的一个wraps在fibonacci中应用例子方便理解:

  from functools import wraps
  
  
  def memo(f):
      c = {}
  
      '''wrapper function will copy all of the important metadata about the inner function to the outer function.
         ref: effective python - item 42
         print(fibonacci.__name__)
      '''
      @wraps(f)
      def helper(*args):
          if args not in c:
              c[args] = f(*args)
          return c[args]
  
      return helper
  
  
  @memo
  def fibonacci(n):
      if n <= 2:
          return 1
      else:
          return fibonacci(n-1) + fibonacci(n-2)

• Item 43: Consider contextlib and with Statements for Reusable try/finally Behavior
  这个和之前看到的一个面试题挺有关系的, 就是with语句为什么会自己关闭. The with statement in Python is used to indecate when code is running in a special context. with 语句的诞生其实就是为了不重复写try/finally.
  这章讲的主要是上下文管理器, 我之前也很迷惑, 上下文管理器(context manager)到底是什么呢?
  我把我的理解写到下边这个自定义的方法里:

  from contextlib import contextmanager
  from urllib.request import urlopen
  
  @contextmanager
  def closing(thing):
      try:
          yield thing
      finally:
          thing.close()
  
  
  with closing(urlopen('http://www.python.org')) as page:
      for line in page:
          print(line)

  上下文大致的意思就是: 代码块执行前的准备，代码块执行后的收拾.
  一个类的实现:

  # Implementing the Context Manager as a Class
  class Saved(object):
      def __init__(self, cr):
          self.cr = cr
  
      def __enter__(self):
          self.cr.save()
          return self.cr
  
      def __exit__(self, type, value, traceback):
          self.cr.restore()

• Item 44: Make pickle Reliable with copyreg
  "The pickle built-in module can serialize Python objects into a stream of bytes and deserialize bytes back into objects. "
  有时候你要是看书看得云里雾里的时候不妨实践一下代码, 就能很快地理解了:

  import pickle
  
  class GameState(object):
      def __init__(self):
          self.level = 0
          self.lives = 4
  
  state = GameState()
  state.level += 1
  state.lives -= 1
  
  state_path = '/tmp/game_state.bin'
  with open(state_path, 'wb') as f:
      pickle.dump(state, f)
  
  with open(state_path, 'rb') as f:
      state_r = pickle.load(f)
  
  print(state_r.__dict__)  # {'level': 1, 'lives': 3}
  
  
  # 但是问题来了, 如果类的属性扩展了, 那些旧的已保存的类要怎么办呢?
  # solution就是用copyreg built-in module.
  import copyreg
  
  class GameState(object):
      def __init__(self, level=0, lives=4, points=0):
          self.level = level
          self.lives = lives
          self.points = points
  
  
  def pickle_game_state(game_state):
      kwargs = game_state.__dict__
      return unpickle_game_state, (kwargs,)
  
  
  def unpickle_game_state(kwargs):
      return GameState(**kwargs)
  
  
  copyreg.pickle(GameState, pickle_game_state)
  
  state = GameState()
  state.points += 1000
  serialized = pickle.dumps(state)
  state_after = pickle.loads(serialized)
  print(state_after.__dict__)  # {'level': 0, 'points': 1000, 'lives': 4}
  
  
  class GameState(object):
      def __init__(self, level=0, lives=4, points=0, magic=5):
          self.level = level
          self.lives = lives
          self.points = points
          self.magic = magic
  
  # deserializing an old GameState object:
  state_after = pickle.loads(serialized)
  print(state_after.__dict__)  # {'points': 1000, 'level': 0, 'lives': 4, 'magic': 5}

  Versioning Classes(略).
  Stable Import Paths(略).

• Item 45: Use datetime Instead of time for Local Clocks.
  Python有两种处理time zone的方法:

  • 旧方法: time built-in method, but is disastrously error conversions.
  • 新方法: datetime built-in module, work greatly with community-built package named pytz

    from time import mktime
    from datetime import datetime, timezone
    
    # convert UTC to computer's local time
    now = datetime(2017, 2, 13, 15, 00, 00)
    now_utc = now.replace(tzinfo=timezone.utc)
    now_local = now_utc.astimezone()
    print(now_local)
    
    # convert local time back to a UNIX timestamp in UTC
    time_str = '2017-02-14 12:00:00'
    parse_format = '%Y-%m-%d %H:%M:%S'
    
    now = datetime.strptime(time_str, parse_format)
    time_tuple = now.timetuple()
    utc_now = mktime(time_tuple)
    print(utc_now)
    
    
    # pytz
    import pytz
    
    # Step 1: Convert local times to UTC first
    arrival_nyc = '2014-05-01 23:33:24'
    nyc_dt_naive = datetime.strptime(arrival_nyc, parse_format)
    eastern = pytz.timezone('US/Eastern')
    nyc_dt = eastern.localize(nyc_dt_naive)
    utc_dt = pytz.utc.normalize(nyc_dt.astimezone(pytz.utc))
    print(utc_dt)
    
    # Step 2: Convert to local time
    pacific = pytz.timezone('US/Pacific')
    sf_dt = pacific.normalize(utc_dt.astimezone(pacific))
    print(sf_dt)