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Python advanced 3.the python std lib by example –data structures

Python advanced 3.the python std lib by example –data structures






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Python advanced 3.the python std lib by example –data structures Python advanced 3.the python std lib by example –data structures Presentation Transcript

  • THE PYTHON STD LIB BY EXAMPLE – DATA STRUCTURES John Saturday, December 21, 2013
  • Overview of this class • Python already include several standard programming data structures, such as list,tuple,dict and set. • The collection module include other several data structures, such as Deque, defaultdict, OrderDict and namedtuple. • For large amount of data, an array module is more efficient
  • Data type Counter • A container tracks how many times equivalent values are added.
  • Update() method of Counter • The count value will be increased based on the new data, rather than replaced.
  • More functions in Counter class • c[i]: return the count of i. • c.elements(): return an iterator • c.most_common(3): produce a list in order of frequency • c.update({‘a’:1,’b’:5}): The count value will be increased based on the new data, rather than replaced.
  • Data type defaultdict Similar as dict.It can let the caller specify the default value when container is initialized.
  • Data type deque • Support adding and removing elements from either end.
  • More method in deque • • • • Method extend,extendleft Method append,appendleft Method pop,popleft Method rotate: rotate the deque to the right direction
  • Data type namedtuple • Similar as regular tuple, but can use instance.attr to access the elements
  • Data type OrderDict • A dictionary subclass that remember the order.
  • Data type heapq • A min-heap: a tree like data structure that the parent should be less than or equal to its children. • Binary heap use a list or array represent it. The children of element N is 2*N+1 and 2*N+2( zero based indexes).
  • Function of heapq class Heap =[] •method: heapq.heappush(Heap,n): add n into heap. •Method: heapq.heapify(list): sort list as a heap •Method heapq.heappop(Heap): pop the smallest item •Method heapq.heapreplace(heap,n): replace the smallest item with n.
  • Data type bitsect • Purpose is maintain a list in sorted order without having to call sort each time adding new item.
  • Method of bitsect • Method insort(alias of insort_right): insert after the existing value • Method insort_left: insert before the existing value. • Method bisect(alias bisect_right): return the position after the existing value. • Method bisect_left: return the position before the existing value.
  • Data type Queue • The Queue module provides FIFO (first in, first out) data structure suitable for multithreaded programming.
  • Data type LIFO Queue (Stack) • LifoQueue use LIFO (Last in, first out) (normally we call it stack data structure).
  • Data type PriorityQueue • The process order is based on characteristics of those items, rather than the order. Example code see here: Import Queue q = Queue.PriorityQueue()
  • Brief introduction • The weakref module support weak references to objects. • A normal reference increase the reference count on the object and prevent it from being garbage collected.
  • Example of weakref • Class ref to create a weak reference • Ref will return None if obj is deleted.
  • Brief introduction • Provide functions for duplicating objects using shallow or deep copy semantics • The copy module include two functions, copy() and deepcopy().
  • Shallow copy: copy() • A new container populated with references to the contents of the original object.
  • Deep copies: deepcopy() • A New container populated with copies of the contents of the original object. • It is possible to control hwo copies are made using the __copy__() and __deepcopy__() special methods.
  • Quick example of pprint • The pprint module contains a “pretty printer”
  • Work with custom classes • If class define __repr__() method, pprint() can also work.
  • More options • Option depth: control the print depth for very deep data strctures. >>> pprint(data,depth=1) • Option width: default output width is 80 columns. >>> pprint(data, width=5)
  • Reference • Source code https://bitbucket.org/qzhang03022/py_stdlib_by