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d-heap-0.0.2


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توضیحات

Python functions for working with D-ary Heap (Heap with more than 2 child nodes)
ویژگی مقدار
سیستم عامل -
نام فایل d-heap-0.0.2
نام d-heap
نسخه کتابخانه 0.0.2
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Ramesh RV
ایمیل نویسنده rameshrvr@outlook.com
آدرس صفحه اصلی https://github.com/rameshrvr/d-ary_heap
آدرس اینترنتی https://pypi.org/project/d-heap/
مجوز MIT License
D-ary Heap ########## .. image:: https://img.shields.io/badge/d_heap-0.0.2-green.svg :target: https://pypi.org/project/d-heap/ .. image:: https://travis-ci.org/rameshrvr/d-ary_heap.svg?branch=master :target: https://travis-ci.org/rameshrvr/d-ary_heap Python functions for working with D-ary Heap (Heap with more than 2 child nodes). For more info about this Data Structure Please gothrough: https://en.wikipedia.org/wiki/D-ary_heap This library provides the below Heap specific functions. *heapify* Convert list of elements to Heap data structure (MinHeap/MaxHeap) *add_element* Add single/list of elements to Heap *get_root_value* Returns root value of the Heap without removing the element Minimum value for Min Heap, Maximum value for Max Heap *extract_root* Extract root element from Heap and reform the Heap *search_value* Searches the value in heap and returns index. if same element is present multiple times, first occurring index is returned *delete_element_at_index* Remove the element at the specified index and reform the Heap For example function invocations, plesae see the tutorial. .. contents:: Installation ============ install from pypi using pip:: $ pip install d_heap or install from source using:: $ git clone https://github.com/rameshrvr/d-ary_heap.git $ cd d-ary_heap $ pip install . Tutorial ======== 1. Min Heap (Heap where the data in parent node is lesser than the data in child node) .. code-block:: python Rameshs-MacBook-Pro:d-ary_heap rameshrv$ python3 Python 3.7.2 (default, Dec 27 2018, 07:35:06) [Clang 10.0.0 (clang-1000.11.45.5)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> >>> from d_heap import MinHeap, MaxHeap >>> >>> array = [4, 3, 6, 8, 11, 1, 5, 14, 10, 7, 2, 12, 9, 13, 15] >>> >>> min_heap_4_children = MinHeap(4, array) # Convert array to 4 children Heap >>> >>> min_heap_4_children.elements() [1, 3, 2, 8, 11, 4, 5, 14, 10, 7, 6, 12, 9, 13, 15] >>> >>> min_heap_5_children = MinHeap(5, array) # Convert array to 5 children Heap >>> >>> min_heap_5_children.elements() [1, 2, 6, 8, 11, 4, 5, 14, 10, 7, 3, 12, 9, 13, 15] >>> >>> min_heap_4_children.add_element(0) # Add single element to Heap >>> >>> min_heap_4_children.elements() [0, 3, 2, 1, 11, 4, 5, 14, 10, 7, 6, 12, 9, 13, 15, 8] >>> >>> min_heap_5_children.add_element([0, 24, 17, 55]) # Add list of elements to heap >>> >>> min_heap_5_children.elements() [0, 2, 1, 8, 11, 4, 5, 14, 10, 7, 3, 12, 9, 13, 15, 6, 24, 17, 55] >>> >>> min_heap_4_children.extract_root() # Extract root element from Heap and retrun it. In this case its the minimum element 0 >>> >>> min_heap_4_children.elements() [1, 3, 2, 8, 11, 4, 5, 14, 10, 7, 6, 12, 9, 13, 15] >>> >>> min_heap_4_children.get_root_value() # Returns the root value (minimum value) without removing it from Heap 1 >>> >>> min_heap_4_children.search_value(5) # Returns index of the searched value. -1 if there is no such value in Heap 6 >>> min_heap_4_children.search_value(7) 9 >>> min_heap_4_children.search_value(21) -1 >>> >>> min_heap_4_children.delete_element_at_index(4) # Remove the element at the specified index >>> >>> min_heap_4_children.elements() [1, 3, 2, 8, 15, 4, 5, 14, 10, 7, 6, 12, 9, 13] >>> 2. Max Heap (Heap where the data in parent node is greater than the data in child node) .. code-block:: python Rameshs-MacBook-Pro:d-ary_heap rameshrv$ python3 Python 3.7.2 (default, Dec 27 2018, 07:35:06) [Clang 10.0.0 (clang-1000.11.45.5)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> >>> from d_heap import MinHeap, MaxHeap >>> >>> array = [4, 3, 6, 8, 11, 1, 5, 14, 10, 7, 2, 12, 9, 13, 15] >>> >>> max_heap_4_children = MaxHeap(4, array) # Convert array to 4 children Heap >>> >>> max_heap_4_children.elements() [15, 14, 12, 13, 11, 1, 5, 3, 10, 7, 2, 6, 9, 4, 8] >>> >>> max_heap_5_children = MaxHeap(5, array) # Convert array to 5 children Heap >>> >>> max_heap_5_children.elements() [15, 14, 13, 8, 11, 1, 5, 3, 10, 7, 2, 12, 9, 4, 6] >>> >>> max_heap_4_children.add_element(21) # Add single element to Heap >>> >>> max_heap_4_children.elements() [21, 14, 12, 15, 11, 1, 5, 3, 10, 7, 2, 6, 9, 4, 8, 13] >>> >>> >>> max_heap_5_children.add_element([21, 14, 27, 35]) # Add list of elements to heap >>> >>> max_heap_5_children.elements() [35, 14, 15, 27, 11, 1, 5, 3, 10, 7, 2, 12, 9, 4, 6, 13, 8, 14, 21] >>> >>> max_heap_4_children.extract_root() # Extract root element from Heap and retrun it. In this case its the maximum element 21 >>> >>> max_heap_4_children.elements() [15, 14, 12, 13, 11, 1, 5, 3, 10, 7, 2, 6, 9, 4, 8] >>> >>> max_heap_4_children.get_root_value() # Returns the root value (maximum value) without removing it from Heap 15 >>> >>> max_heap_4_children.search_value(5) # Returns index of the searched value. -1 if there is no such value in Heap 6 >>> max_heap_4_children.search_value(11) 4 >>> max_heap_4_children.search_value(21) -1 >>> >>> max_heap_4_children.delete_element_at_index(2) # Remove the element at the specified index >>> >>> max_heap_4_children.elements() [15, 14, 9, 13, 11, 1, 5, 3, 10, 7, 2, 6, 8, 4] >>> Development =========== After checking out the repo, `cd` to the repository. Then, run `pip install .` to install the package locally. You can also run `python (or) python3` for an interactive prompt that will allow you to experiment. To install this package onto your local machine, `cd` to the repository then run `pip install .`. To release a new version, update the version number in `setup.py`, and then run `python setup.py register`, which will create a git tag for the version, push git commits and tags, and push the package file to [PyPI](https://pypi.org). Contributing ============ Bug reports and pull requests are welcome on GitHub at https://github.com/rameshrvr/d-ary_heap. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant]<http://contributor-covenant.org> code of conduct. License ======== The package is available as open source under the terms of the [MIT License]<https://opensource.org/licenses/MIT>. Code of Conduct =============== Everyone interacting in the Binary Heap project’s codebases, issue trackers, chat rooms and mailing lists is expected to follow the [code of conduct](https://github.com/rameshrvr/d-ary_heap/blob/master/CODE_OF_CONDUCT.md). misc ======== :license: * MIT License :authors: * Ramesh RV * Adithya KS


نحوه نصب


نصب پکیج whl d-heap-0.0.2:

    pip install d-heap-0.0.2.whl


نصب پکیج tar.gz d-heap-0.0.2:

    pip install d-heap-0.0.2.tar.gz