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‎16_优先级队列/priority_queue.py

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@@ -132,7 +132,10 @@ def test_priority_queue():
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def test_buildin_PriorityQueue(): # python3
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# https://pythonguides.com/priority-queue-in-python/
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"""
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测试内置的 PriorityQueue
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https://pythonguides.com/priority-queue-in-python/
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"""
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from queue import PriorityQueue
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q = PriorityQueue()
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q.put((10, 'Red balls'))
@@ -145,6 +148,9 @@ def test_buildin_PriorityQueue(): # python3
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def test_buildin_heapq_as_PriorityQueue():
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"""
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测试使用 heapq 实现优先级队列，保存一个 tuple 比较元素(tuple第一个元素是优先级)
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"""
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import heapq
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s_roll = []
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heapq.heappush(s_roll, (4, "Tom"))
@@ -172,6 +178,10 @@ def __str__(self):
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def test_heap_item():
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"""
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测试使用 Item 类实现优先级队列，因为 heapq 内置使用的是小于运算法，
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重写魔术 < 比较方法即可实现
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"""
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import heapq
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pq = []
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heapq.heappush(pq, Item('c', 3))

‎19_python内置常用算法和数据结构/builtins/index.html

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<li class="toctree-l2"><a href="#_2">链表题目调试函数</a></li>
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<li class="toctree-l2"><a href="#_3">内置库实现优先级队列的三种方式</a></li>
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</ul>
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</li>
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@@ -291,6 +294,7 @@ <h1 id="_1">一些坑</h1>
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<li>正确初始化一个二维数组：<code>dp = [[0 for _ in range(col)] for _ in range(row)]</code>，不要用 <code>dp = [[0] * n] * m</code>， 否则里边都
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引用的同一个 list，修改一个都会变</li>
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<li>python在数值范围建议用：<code>MAXINT = 2**63-1; MININT = -2**63</code> 。因为 python2 sys.maxint 和 python3 sys.maxsize 不统一</li>
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<li>优先级队列：使用内置的 heapq ，定义一个 Item 类实现"小于" 魔术方法就可以实现</li>
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</ul>
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<h1 id="_2">链表题目调试函数</h1>
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<pre><code class="language-py"># 编写链表题目经常用到的一些通用函数和调试函数，定义等，方便代码调试
@@ -345,6 +349,66 @@ <h1 id="_2">链表题目调试函数</h1>
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res += &quot;nil&quot;
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print(res)
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</code></pre>
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<h1 id="_3">内置库实现优先级队列的三种方式</h1>
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<pre><code class="language-py">def test_buildin_PriorityQueue(): # python3
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&quot;&quot;&quot;
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测试内置的 PriorityQueue
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https://pythonguides.com/priority-queue-in-python/
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&quot;&quot;&quot;
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from queue import PriorityQueue
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q = PriorityQueue()
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q.put((10, 'Red balls'))
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q.put((8, 'Pink balls'))
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q.put((5, 'White balls'))
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q.put((4, 'Green balls'))
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while not q.empty():
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item = q.get()
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print(item)
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def test_buildin_heapq_as_PriorityQueue():
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&quot;&quot;&quot;
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测试使用 heapq 实现优先级队列，保存一个 tuple 比较元素(tuple第一个元素是优先级)
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&quot;&quot;&quot;
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import heapq
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s_roll = []
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heapq.heappush(s_roll, (4, &quot;Tom&quot;))
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heapq.heappush(s_roll, (1, &quot;Aruhi&quot;))
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heapq.heappush(s_roll, (3, &quot;Dyson&quot;))
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heapq.heappush(s_roll, (2, &quot;Bob&quot;))
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while s_roll:
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deque_r = heapq.heappop(s_roll)
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print(deque_r)
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# python3 没有了 __cmp__ 魔法函数 https://stackoverflow.com/questions/8276983/why-cant-i-use-the-method-cmp-in-python-3-as-for-python-2
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class Item:
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def __init__(self, key, weight):
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self.key, self.weight = key, weight
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def __lt__(self, other): # 看其来 heapq 实现只用了 小于 比较，这里定义了就可以 push 一个 item 类
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return self.weight &lt; other.weight
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def __eq__(self, other):
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return self.weight == other.weight
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def __str__(self):
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return '{}:{}'.format(self.key,self.weight)
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def test_heap_item():
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&quot;&quot;&quot;
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测试使用 Item 类实现优先级队列，因为 heapq 内置使用的是小于运算法，
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重写魔术 &lt; 比较方法即可实现
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&quot;&quot;&quot;
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import heapq
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pq = []
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heapq.heappush(pq, Item('c', 3))
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heapq.heappush(pq, Item('a', 1))
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heapq.heappush(pq, Item('b', 2))
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while pq:
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print(heapq.heappop(pq))
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</code></pre>
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</div>
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</div>

‎index.html

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@@ -599,5 +599,5 @@ <h2 id="_22">本电子书制作和写作方式</h2>
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<!--
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MkDocs version : 1.0.4
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Build Date UTC : 2022-01-24 15:29:58
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Build Date UTC : 2022-01-26 13:16:15
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-->

‎search/search_index.json

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‎sitemap.xml

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<urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<changefreq>daily</changefreq>
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</url>
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<lastmod>2022-01-24</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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</url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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<loc>None</loc>
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<lastmod>2022-01-24</lastmod>
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<lastmod>2022-01-26</lastmod>
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<changefreq>daily</changefreq>
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</url>
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</urlset>

‎sitemap.xml.gz

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