最新国产好看的视频,伊人天堂AV在线,国产Aaaaaa视频,蜜臀视频在线观看一区,人妻av色图,密臀久久久精品影片,青青视频免费观看毛片,久草在线观看视,国产三级精品色情在线

python隊列queue模塊詳解

 更新時間:2018年04月27日 09:50:49   作者:菜鳥磊子  
這篇文章主要為大家詳細介紹了python隊列queue模塊的相關(guān)資料,具有一定的參考價值,感興趣的小伙伴們可以參考一下

隊列queue 多應(yīng)用在多線程應(yīng)用中,多線程訪問共享變量。對于多線程而言,訪問共享變量時,隊列queue是線程安全的。從queue隊列的具體實現(xiàn)中,可以看出queue使用了1個線程互斥鎖(pthread.Lock()),以及3個條件標(biāo)量(pthread.condition()),來保證了線程安全。

queue隊列的互斥鎖和條件變量,可以參考另一篇文章:python線程中同步鎖

queue的用法如下:

import Queque 
a=[1,2,3] 
device_que=Queque.queue() 
device_que.put(a) 
device=device_que.get() 

先看看它的初始化函數(shù)__init__(self,maxsize=0):

def __init__(self, maxsize=0): 
 self.maxsize = maxsize 
 self._init(maxsize) 
 # mutex must be held whenever the queue is mutating. All methods 
 # that acquire mutex must release it before returning. mutex 
 # is shared between the three conditions, so acquiring and 
 # releasing the conditions also acquires and releases mutex. 
 self.mutex = _threading.Lock() 
 # Notify not_empty whenever an item is added to the queue; a 
 # thread waiting to get is notified then. 
 self.not_empty = _threading.Condition(self.mutex) 
 # Notify not_full whenever an item is removed from the queue; 
 # a thread waiting to put is notified then. 
 self.not_full = _threading.Condition(self.mutex) 
 # Notify all_tasks_done whenever the number of unfinished tasks 
 # drops to zero; thread waiting to join() is notified to resume 
 self.all_tasks_done = _threading.Condition(self.mutex) 
 self.unfinished_tasks = 0 

定義隊列時有一個默認的參數(shù)maxsize, 如果不指定隊列的長度,即manxsize=0,那么隊列的長度為無限長,如果定義了大于0的值,那么隊列的長度就是maxsize。

self._init(maxsize):使用了python自帶的雙端隊列deque,來存儲元素。

self.mutex互斥鎖:任何獲取隊列的狀態(tài)(empty(),qsize()等),或者修改隊列的內(nèi)容的操作(get,put等)都必須持有該互斥鎖。共有兩種操作require獲取鎖,release釋放鎖。同時該互斥鎖被三個共享變量同時享有,即操作conditiond時的require和release操作也就是操作了該互斥鎖。

self.not_full條件變量:當(dāng)隊列中有元素添加后,會通知notify其他等待添加元素的線程,喚醒等待require互斥鎖,或者有線程從隊列中取出一個元素后,通知其它線程喚醒以等待require互斥鎖。

self.not empty條件變量:線程添加數(shù)據(jù)到隊列中后,會調(diào)用self.not_empty.notify()通知其它線程,喚醒等待require互斥鎖后,讀取隊列。

self.all_tasks_done條件變量:消費者線程從隊列中g(shù)et到任務(wù)后,任務(wù)處理完成,當(dāng)所有的隊列中的任務(wù)處理完成后,會使調(diào)用queue.join()的線程返回,表示隊列中任務(wù)以處理完畢。

queue.put(self, item, block=True, timeout=None)函數(shù):

申請獲得互斥鎖,獲得后,如果隊列未滿,則向隊列中添加數(shù)據(jù),并通知notify其它阻塞的某個線程,喚醒等待獲取require互斥鎖。如果隊列已滿,則會wait等待。最后處理完成后釋放互斥鎖。其中還有阻塞block以及非阻塞,超時等邏輯,可以自己看一下:

def put(self, item, block=True, timeout=None): 
 """Put an item into the queue. 
 
 If optional args 'block' is true and 'timeout' is None (the default), 
 block if necessary until a free slot is available. If 'timeout' is 
 a non-negative number, it blocks at most 'timeout' seconds and raises 
 the Full exception if no free slot was available within that time. 
 Otherwise ('block' is false), put an item on the queue if a free slot 
 is immediately available, else raise the Full exception ('timeout' 
 is ignored in that case). 
 """ 
 self.not_full.acquire() 
 try: 
  if self.maxsize > 0: 
   if not block: 
    if self._qsize() == self.maxsize: 
     raise Full 
   elif timeout is None: 
    while self._qsize() == self.maxsize: 
     self.not_full.wait() 
   elif timeout < 0: 
    raise ValueError("'timeout' must be a non-negative number") 
   else: 
    endtime = _time() + timeout 
    while self._qsize() == self.maxsize: 
     remaining = endtime - _time() 
     if remaining <= 0.0: 
      raise Full 
     self.not_full.wait(remaining) 
  self._put(item) 
  self.unfinished_tasks += 1 
  self.not_empty.notify() 
 finally: 
  self.not_full.release() 

queue.get(self, block=True, timeout=None)函數(shù):

從隊列中獲取任務(wù),并且從隊列中移除此任務(wù)。首先嘗試獲取互斥鎖,獲取成功則隊列中g(shù)et任務(wù),如果此時隊列為空,則wait等待生產(chǎn)者線程添加數(shù)據(jù)。get到任務(wù)后,會調(diào)用self.not_full.notify()通知生產(chǎn)者線程,隊列可以添加元素了。最后釋放互斥鎖。

def get(self, block=True, timeout=None): 
 """Remove and return an item from the queue. 
 
 If optional args 'block' is true and 'timeout' is None (the default), 
 block if necessary until an item is available. If 'timeout' is 
 a non-negative number, it blocks at most 'timeout' seconds and raises 
 the Empty exception if no item was available within that time. 
 Otherwise ('block' is false), return an item if one is immediately 
 available, else raise the Empty exception ('timeout' is ignored 
 in that case). 
 """ 
 self.not_empty.acquire() 
 try: 
  if not block: 
   if not self._qsize(): 
    raise Empty 
  elif timeout is None: 
   while not self._qsize(): 
    self.not_empty.wait() 
  elif timeout < 0: 
   raise ValueError("'timeout' must be a non-negative number") 
  else: 
   endtime = _time() + timeout 
   while not self._qsize(): 
    remaining = endtime - _time() 
    if remaining <= 0.0: 
     raise Empty 
    self.not_empty.wait(remaining) 
  item = self._get() 
  self.not_full.notify() 
  return item 
 finally: 
  self.not_empty.release() 

queue.put_nowait():無阻塞的向隊列中添加任務(wù),當(dāng)隊列為滿時,不等待,而是直接拋出full異常,重點是理解block=False:

def put_nowait(self, item): 
 """Put an item into the queue without blocking. 
 
 Only enqueue the item if a free slot is immediately available. 
 Otherwise raise the Full exception. 
 """ 
 return self.put(item, False) 

queue.get_nowait():無阻塞的向隊列中g(shù)et任務(wù),當(dāng)隊列為空時,不等待,而是直接拋出empty異常,重點是理解block=False:

def get_nowait(self): 
  """Remove and return an item from the queue without blocking. 
 
  Only get an item if one is immediately available. Otherwise 
  raise the Empty exception. 
  """ 
  return self.get(False) 

queue.qsize empty full 分別獲取隊列的長度,是否為空,是否已滿等:

def qsize(self): 
 """Return the approximate size of the queue (not reliable!).""" 
 self.mutex.acquire() 
 n = self._qsize() 
 self.mutex.release() 
 return n 
 
def empty(self): 
 """Return True if the queue is empty, False otherwise (not reliable!).""" 
 self.mutex.acquire() 
 n = not self._qsize() 
 self.mutex.release() 
 return n 
 
def full(self): 
 """Return True if the queue is full, False otherwise (not reliable!).""" 
 self.mutex.acquire() 
 n = 0 < self.maxsize == self._qsize() 
 self.mutex.release() 
 return n 

queue.join()阻塞等待隊列中任務(wù)全部處理完畢,需要配合queue.task_done使用:

def task_done(self): 
 """Indicate that a formerly enqueued task is complete. 
 
 Used by Queue consumer threads. For each get() used to fetch a task, 
 a subsequent call to task_done() tells the queue that the processing 
 on the task is complete. 
 
 If a join() is currently blocking, it will resume when all items 
 have been processed (meaning that a task_done() call was received 
 for every item that had been put() into the queue). 
 
 Raises a ValueError if called more times than there were items 
 placed in the queue. 
 """ 
 self.all_tasks_done.acquire() 
 try: 
  unfinished = self.unfinished_tasks - 1 
  if unfinished <= 0: 
   if unfinished < 0: 
    raise ValueError('task_done() called too many times') 
   self.all_tasks_done.notify_all() 
  self.unfinished_tasks = unfinished 
 finally: 
  self.all_tasks_done.release() 
 
def join(self): 
 """Blocks until all items in the Queue have been gotten and processed. 
 
 The count of unfinished tasks goes up whenever an item is added to the 
 queue. The count goes down whenever a consumer thread calls task_done() 
 to indicate the item was retrieved and all work on it is complete. 
 
 When the count of unfinished tasks drops to zero, join() unblocks. 
 """ 
 self.all_tasks_done.acquire() 
 try: 
  while self.unfinished_tasks: 
   self.all_tasks_done.wait() 
 finally: 
  self.all_tasks_done.release() 

Queue模塊除了queue線性安全隊列(先進先出),還有優(yōu)先級隊列LifoQueue(后進先出),也就是新添加的先被get到。PriorityQueue具有優(yōu)先級的隊列,即隊列中的元素是一個元祖類型,(優(yōu)先級級別,數(shù)據(jù))。

class PriorityQueue(Queue): 
 '''''Variant of Queue that retrieves open entries in priority order (lowest first). 
 
 Entries are typically tuples of the form: (priority number, data). 
 ''' 
 
 def _init(self, maxsize): 
  self.queue = [] 
 
 def _qsize(self, len=len): 
  return len(self.queue) 
 
 def _put(self, item, heappush=heapq.heappush): 
  heappush(self.queue, item) 
 
 def _get(self, heappop=heapq.heappop): 
  return heappop(self.queue) 
 
 
class LifoQueue(Queue): 
 '''''Variant of Queue that retrieves most recently added entries first.''' 
 
 def _init(self, maxsize): 
  self.queue = [] 
 
 def _qsize(self, len=len): 
  return len(self.queue) 
 
 def _put(self, item): 
  self.queue.append(item) 
 
 def _get(self): 
  return self.queue.pop() 

至此queue模塊介紹完畢,重點是理解互斥鎖,條件變量如果協(xié)同工作,保證隊列的線程安全。

下面是queue的完全代碼:

class Queue: 
 """Create a queue object with a given maximum size. 
 
 If maxsize is <= 0, the queue size is infinite. 
 """ 
 def __init__(self, maxsize=0): 
  self.maxsize = maxsize 
  self._init(maxsize) 
  # mutex must be held whenever the queue is mutating. All methods 
  # that acquire mutex must release it before returning. mutex 
  # is shared between the three conditions, so acquiring and 
  # releasing the conditions also acquires and releases mutex. 
  self.mutex = _threading.Lock() 
  # Notify not_empty whenever an item is added to the queue; a 
  # thread waiting to get is notified then. 
  self.not_empty = _threading.Condition(self.mutex) 
  # Notify not_full whenever an item is removed from the queue; 
  # a thread waiting to put is notified then. 
  self.not_full = _threading.Condition(self.mutex) 
  # Notify all_tasks_done whenever the number of unfinished tasks 
  # drops to zero; thread waiting to join() is notified to resume 
  self.all_tasks_done = _threading.Condition(self.mutex) 
  self.unfinished_tasks = 0 
 
 def task_done(self): 
  """Indicate that a formerly enqueued task is complete. 
 
  Used by Queue consumer threads. For each get() used to fetch a task, 
  a subsequent call to task_done() tells the queue that the processing 
  on the task is complete. 
 
  If a join() is currently blocking, it will resume when all items 
  have been processed (meaning that a task_done() call was received 
  for every item that had been put() into the queue). 
 
  Raises a ValueError if called more times than there were items 
  placed in the queue. 
  """ 
  self.all_tasks_done.acquire() 
  try: 
   unfinished = self.unfinished_tasks - 1 
   if unfinished <= 0: 
    if unfinished < 0: 
     raise ValueError('task_done() called too many times') 
    self.all_tasks_done.notify_all() 
   self.unfinished_tasks = unfinished 
  finally: 
   self.all_tasks_done.release() 
 
 def join(self): 
  """Blocks until all items in the Queue have been gotten and processed. 
 
  The count of unfinished tasks goes up whenever an item is added to the 
  queue. The count goes down whenever a consumer thread calls task_done() 
  to indicate the item was retrieved and all work on it is complete. 
 
  When the count of unfinished tasks drops to zero, join() unblocks. 
  """ 
  self.all_tasks_done.acquire() 
  try: 
   while self.unfinished_tasks: 
    self.all_tasks_done.wait() 
  finally: 
   self.all_tasks_done.release() 
 
 def qsize(self): 
  """Return the approximate size of the queue (not reliable!).""" 
  self.mutex.acquire() 
  n = self._qsize() 
  self.mutex.release() 
  return n 
 
 def empty(self): 
  """Return True if the queue is empty, False otherwise (not reliable!).""" 
  self.mutex.acquire() 
  n = not self._qsize() 
  self.mutex.release() 
  return n 
 
 def full(self): 
  """Return True if the queue is full, False otherwise (not reliable!).""" 
  self.mutex.acquire() 
  n = 0 < self.maxsize == self._qsize() 
  self.mutex.release() 
  return n 
 
 def put(self, item, block=True, timeout=None): 
  """Put an item into the queue. 
 
  If optional args 'block' is true and 'timeout' is None (the default), 
  block if necessary until a free slot is available. If 'timeout' is 
  a non-negative number, it blocks at most 'timeout' seconds and raises 
  the Full exception if no free slot was available within that time. 
  Otherwise ('block' is false), put an item on the queue if a free slot 
  is immediately available, else raise the Full exception ('timeout' 
  is ignored in that case). 
  """ 
  self.not_full.acquire() 
  try: 
   if self.maxsize > 0: 
    if not block: 
     if self._qsize() == self.maxsize: 
      raise Full 
    elif timeout is None: 
     while self._qsize() == self.maxsize: 
      self.not_full.wait() 
    elif timeout < 0: 
     raise ValueError("'timeout' must be a non-negative number") 
    else: 
     endtime = _time() + timeout 
     while self._qsize() == self.maxsize: 
      remaining = endtime - _time() 
      if remaining <= 0.0: 
       raise Full 
      self.not_full.wait(remaining) 
   self._put(item) 
   self.unfinished_tasks += 1 
   self.not_empty.notify() 
  finally: 
   self.not_full.release() 
 
 def put_nowait(self, item): 
  """Put an item into the queue without blocking. 
 
  Only enqueue the item if a free slot is immediately available. 
  Otherwise raise the Full exception. 
  """ 
  return self.put(item, False) 
 
 def get(self, block=True, timeout=None): 
  """Remove and return an item from the queue. 
 
  If optional args 'block' is true and 'timeout' is None (the default), 
  block if necessary until an item is available. If 'timeout' is 
  a non-negative number, it blocks at most 'timeout' seconds and raises 
  the Empty exception if no item was available within that time. 
  Otherwise ('block' is false), return an item if one is immediately 
  available, else raise the Empty exception ('timeout' is ignored 
  in that case). 
  """ 
  self.not_empty.acquire() 
  try: 
   if not block: 
    if not self._qsize(): 
     raise Empty 
   elif timeout is None: 
    while not self._qsize(): 
     self.not_empty.wait() 
   elif timeout < 0: 
    raise ValueError("'timeout' must be a non-negative number") 
   else: 
    endtime = _time() + timeout 
    while not self._qsize(): 
     remaining = endtime - _time() 
     if remaining <= 0.0: 
      raise Empty 
     self.not_empty.wait(remaining) 
   item = self._get() 
   self.not_full.notify() 
   return item 
  finally: 
   self.not_empty.release() 
 
 def get_nowait(self): 
  """Remove and return an item from the queue without blocking. 
 
  Only get an item if one is immediately available. Otherwise 
  raise the Empty exception. 
  """ 
  return self.get(False) 
 
 # Override these methods to implement other queue organizations 
 # (e.g. stack or priority queue). 
 # These will only be called with appropriate locks held 
 
 # Initialize the queue representation 
 def _init(self, maxsize): 
  self.queue = deque() 
 
 def _qsize(self, len=len): 
  return len(self.queue) 
 
 # Put a new item in the queue 
 def _put(self, item): 
  self.queue.append(item) 
 
 # Get an item from the queue 
 def _get(self): 
  return self.queue.popleft() 

以上就是本文的全部內(nèi)容,希望對大家的學(xué)習(xí)有所幫助,也希望大家多多支持腳本之家。

相關(guān)文章

  • Python批量修改文件后綴的方法

    Python批量修改文件后綴的方法

    這篇文章主要介紹了Python批量修改文件后綴的方法,有需要的朋友可以參考一下
    2014-01-01
  • Python實現(xiàn)隨機漫步的詳細過程

    Python實現(xiàn)隨機漫步的詳細過程

    隨機漫步顧名思義每一步都是隨機的,假設(shè)有一個點,下一步往哪里走,走多遠,這些都沒有明確的表示,完全是隨機的,最后走到哪里,是由一系列隨機決策決定的,這篇文章主要給大家介紹了關(guān)于Python實現(xiàn)隨機漫步的相關(guān)資料,需要的朋友可以參考下
    2023-03-03
  • Python利用pandas對數(shù)據(jù)進行特定排序

    Python利用pandas對數(shù)據(jù)進行特定排序

    本文主要介紹了Python利用pandas對數(shù)據(jù)進行特定排序,主要使用?pandas.DataFrame.sort_values?方法,文中通過示例代碼介紹的非常詳細,需要的朋友們下面隨著小編來一起學(xué)習(xí)學(xué)習(xí)吧
    2024-03-03
  • 一文教你學(xué)會使用Python中的多處理模塊

    一文教你學(xué)會使用Python中的多處理模塊

    Python?多處理模塊是一個強大的工具,用于實現(xiàn)并行處理,提高程序的性能和效率,本文將詳細介紹?Python?中多處理模塊的使用方法,希望對大家有所幫助
    2024-01-01
  • 手把手教你Python抓取數(shù)據(jù)并可視化

    手把手教你Python抓取數(shù)據(jù)并可視化

    很多小伙伴在提到python數(shù)據(jù)可視化的時候第一反應(yīng)就是matplotlib庫,但實際上python還有很多很好用的數(shù)據(jù)可視化的庫,下面這篇文章主要給大家介紹了關(guān)于如何利用Python抓取數(shù)據(jù)并可視化的相關(guān)資料,需要的朋友可以參考下
    2022-05-05
  • Flask緩存靜態(tài)文件的具體方法

    Flask緩存靜態(tài)文件的具體方法

    在本篇文章中小編給大家整理的是一篇關(guān)于Flask緩存靜態(tài)文件的具體方法,有需要的朋友們可以參考下。
    2020-08-08
  • python PyQt5對象類型的判定及對象刪除操作詳細解讀

    python PyQt5對象類型的判定及對象刪除操作詳細解讀

    PyQt5主要是用來判定一個對象的類型,或者說是否繼承自某個類,本文給大家介紹python PyQt5對象類型的判定,對象刪除操作詳細解讀,感興趣的朋友一起看看吧
    2024-07-07
  • 樹莓派極簡安裝OpenCv的方法步驟

    樹莓派極簡安裝OpenCv的方法步驟

    這篇文章主要介紹了樹莓派極簡安裝OpenCv的方法步驟,文中通過示例代碼介紹的非常詳細,對大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價值,需要的朋友們下面隨著小編來一起學(xué)習(xí)學(xué)習(xí)吧
    2019-10-10
  • python添加命令行參數(shù)的詳細過程

    python添加命令行參數(shù)的詳細過程

    Click 是 Flask 的開發(fā)團隊 Pallets 的另一款開源項目,它是用于快速創(chuàng)建命令行的第三方模塊,這篇文章主要介紹了python怎么添加命令行參數(shù),需要的朋友可以參考下
    2023-06-06
  • Python控制線程和函數(shù)超時處理

    Python控制線程和函數(shù)超時處理

    這篇文章主要介紹了Python控制線程和函數(shù)超時處理,文中利用兩種方法進行eventlet庫和@func_set_timeout修飾器,文章具體詳細介紹,需要的小伙伴可以參考一下
    2022-06-06

最新評論

洛阳市| 岳阳县| 理塘县| 博兴县| 博白县| 苏尼特左旗| 金华市| 登封市| 厦门市| 商水县| 玉山县| 郸城县| 长寿区| 兰西县| 永和县| 和顺县| 大田县| 米林县| 丽水市| 西充县| 电白县| 全南县| 新巴尔虎右旗| 余干县| 依安县| 黄平县| 得荣县| 张家口市| 闽侯县| 天峨县| 依安县| 乐安县| 民权县| 娱乐| 夏河县| 双牌县| 鄂托克前旗| 陵水| 延寿县| 泗阳县| 永仁县|