|
| 1 | + |
| 2 | +from __future__ import print_function, division |
| 3 | +from pydatastructs.linear_data_structures import OneDimensionalArray |
| 4 | +from copy import deepcopy as dc |
| 5 | + |
| 6 | +__all__ = [ |
| 7 | + 'Stack' |
| 8 | +] |
| 9 | + |
| 10 | +_check_type = lambda a, t: isinstance(a, t) |
| 11 | +NoneType = type(None) |
| 12 | + |
| 13 | +class Stack(object): |
| 14 | + """Respresentation of stack data structure |
| 15 | +
|
| 16 | + Parameters |
| 17 | + ========== |
| 18 | +
|
| 19 | + implementation : str |
| 20 | + Implementation to be used for stack. |
| 21 | + By default, 'array' |
| 22 | + Currently only supports 'array' |
| 23 | + implementation. |
| 24 | + maxsize : int |
| 25 | + The maximum size of the stack. |
| 26 | + For array implementation. |
| 27 | + top : int |
| 28 | + The top element of the stack. |
| 29 | + For array implementation. |
| 30 | + items : OneDimensionalArray |
| 31 | + Optional, by default, None |
| 32 | + The inital items in the stack. |
| 33 | + For array implementation. |
| 34 | + dtype : A valid python type |
| 35 | + Optional, by default int if item |
| 36 | + is None, otherwise takes the data |
| 37 | + type of OneDimensionalArray |
| 38 | + For array implementation. |
| 39 | +
|
| 40 | + Example |
| 41 | + ======= |
| 42 | +
|
| 43 | + >>> from pydatastructs import Stack |
| 44 | + >>> s = Stack(maxsize=5, top=0) |
| 45 | + >>> s.push(1) |
| 46 | + >>> s.push(2) |
| 47 | + >>> s.push(3) |
| 48 | + >>> str(s) |
| 49 | + '[1, 2, 3, None, None]' |
| 50 | + >>> s.pop() |
| 51 | + 3 |
| 52 | +
|
| 53 | + References |
| 54 | + ========== |
| 55 | +
|
| 56 | + .. [1] https://en.wikipedia.org/wiki/Stack_(abstract_data_type) |
| 57 | + """ |
| 58 | + |
| 59 | + def __new__(cls, implementation='array', **kwargs): |
| 60 | + if implementation == 'array': |
| 61 | + return ArrayStack( |
| 62 | + kwargs.get('maxsize', None), |
| 63 | + kwargs.get('top', None), |
| 64 | + kwargs.get('items', None), |
| 65 | + kwargs.get('dtype', int)) |
| 66 | + raise NotImplementedError( |
| 67 | + "%s hasn't been implemented yet."%(implementation)) |
| 68 | + |
| 69 | + def push(self, *args, **kwargs): |
| 70 | + raise NotImplementedError( |
| 71 | + "This is an abstract method.") |
| 72 | + |
| 73 | + def pop(self, *args, **kwargs): |
| 74 | + raise NotImplementedError( |
| 75 | + "This is an abstract method.") |
| 76 | + |
| 77 | +class ArrayStack(Stack): |
| 78 | + |
| 79 | + def __new__(cls, maxsize=None, top=0, items=None, dtype=int): |
| 80 | + if not _check_type(maxsize, int): |
| 81 | + raise ValueError("maxsize is missing.") |
| 82 | + if not _check_type(top, int): |
| 83 | + raise ValueError("top is missing.") |
| 84 | + if items == None: |
| 85 | + items = OneDimensionalArray(dtype, maxsize) |
| 86 | + if not _check_type(items, OneDimensionalArray): |
| 87 | + raise ValueError("items is not of type, OneDimensionalArray") |
| 88 | + if items._size > maxsize: |
| 89 | + raise ValueError("Overflow, size of items %s is greater " |
| 90 | + "than maxsize, %s"%(items._size, maxsize)) |
| 91 | + obj = object.__new__(cls) |
| 92 | + obj.maxsize, obj.top, obj.items, obj.dtype = \ |
| 93 | + maxsize, top, items, items._dtype |
| 94 | + return obj |
| 95 | + |
| 96 | + def push(self, x): |
| 97 | + if self.top == self.maxsize: |
| 98 | + raise ValueError("Stack is full.") |
| 99 | + self.items[self.top] = self.dtype(x) |
| 100 | + self.top += 1 |
| 101 | + |
| 102 | + def pop(self): |
| 103 | + if self.top == 0: |
| 104 | + raise ValueError("Stack is already empty.") |
| 105 | + self.top -= 1 |
| 106 | + r = self.items[self.top] |
| 107 | + self.items[self.top] = None |
| 108 | + return r |
| 109 | + |
| 110 | + def __str__(self): |
| 111 | + """ |
| 112 | + Used for printing. |
| 113 | + """ |
| 114 | + return str(self.items._data) |
0 commit comments