Python functions for working with Binary Heap
Project description
Binary Heap
###########
Python library which helps in forming Binary Heaps (Min, Max) using list data structure.
This library provides the below Heap specific functions.
1. heapify  Convert list of elements to Heap data structure
2. add_element  Add single/list of elements to Heap
3. extract_root  Extract root element from Heap and reform the Heap
Installation
========
install from pypi using pip::
$ pip install binary_heap
or easy_install::
$ easy_install binary_heap
or install from source using::
$ git clone https://github.com/rameshrvr/binary_heap.git
$ cd binary_heap
$ pip install .
Tutorial
========
1. Min Heap (Heap where the data in parent node is lesser than the data in child node)
.. codeblock:: python
RameshsMBPead8:binary_heap rameshrv$ python3
Python 3.7.2 (default, Dec 27 2018, 07:35:06)
[Clang 10.0.0 (clang1000.11.45.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> from binary_heap import MinHeap
>>> min_heap = MinHeap([4, 3, 6, 8, 11])
>>> min_heap.length()
5
>>> min_heap.elements()
[3, 4, 6, 8, 11]
>>> min_heap.add_element(1)
>>> min_heap.elements()
[1, 4, 3, 8, 11, 6]
>>> min_heap.add_element([1, 14, 7, 5])
>>> min_heap.elements()
[1, 4, 1, 7, 5, 6, 3, 14, 8, 11]
>>> min_heap.extract_root()
1
>>> min_heap.elements()
[1, 4, 3, 7, 5, 6, 11, 14, 8]
>>> min_heap.get_root_value()
1
>>>
2. Max Heap (Heap where the data in parent node is greater than the data in child node)
.. codeblock:: python
RameshsMBPead8:binary_heap rameshrv$ python3
Python 3.7.2 (default, Dec 27 2018, 07:35:06)
[Clang 10.0.0 (clang1000.11.45.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> from binary_heap import MinHeap
>>> max_heap = MaxHeap([4, 3, 6, 8, 11])
>>> max_heap.elements()
[11, 8, 6, 4, 3]
>>> max_heap.add_element(13)
>>> max_heap.elements()
[13, 8, 11, 4, 3, 6]
>>> max_heap.add_element([1, 14, 7, 5])
>>> max_heap.elements()
[14, 13, 11, 8, 5, 6, 1, 4, 7, 3]
>>> max_heap.extract_root()
14
>>> max_heap.elements()
[13, 8, 11, 7, 5, 6, 1, 4, 3]
>>> max_heap.get_root_value()
13
>>>
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/binary_heap. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](http://contributorcovenant.org) code of conduct.
License
========
The package is available as open source under the terms of the [GPL3.0 License](https://opensource.org/licenses/GPL3.0).
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/binary_heap/blob/master/CODE_OF_CONDUCT.md).
###########
Python library which helps in forming Binary Heaps (Min, Max) using list data structure.
This library provides the below Heap specific functions.
1. heapify  Convert list of elements to Heap data structure
2. add_element  Add single/list of elements to Heap
3. extract_root  Extract root element from Heap and reform the Heap
Installation
========
install from pypi using pip::
$ pip install binary_heap
or easy_install::
$ easy_install binary_heap
or install from source using::
$ git clone https://github.com/rameshrvr/binary_heap.git
$ cd binary_heap
$ pip install .
Tutorial
========
1. Min Heap (Heap where the data in parent node is lesser than the data in child node)
.. codeblock:: python
RameshsMBPead8:binary_heap rameshrv$ python3
Python 3.7.2 (default, Dec 27 2018, 07:35:06)
[Clang 10.0.0 (clang1000.11.45.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> from binary_heap import MinHeap
>>> min_heap = MinHeap([4, 3, 6, 8, 11])
>>> min_heap.length()
5
>>> min_heap.elements()
[3, 4, 6, 8, 11]
>>> min_heap.add_element(1)
>>> min_heap.elements()
[1, 4, 3, 8, 11, 6]
>>> min_heap.add_element([1, 14, 7, 5])
>>> min_heap.elements()
[1, 4, 1, 7, 5, 6, 3, 14, 8, 11]
>>> min_heap.extract_root()
1
>>> min_heap.elements()
[1, 4, 3, 7, 5, 6, 11, 14, 8]
>>> min_heap.get_root_value()
1
>>>
2. Max Heap (Heap where the data in parent node is greater than the data in child node)
.. codeblock:: python
RameshsMBPead8:binary_heap rameshrv$ python3
Python 3.7.2 (default, Dec 27 2018, 07:35:06)
[Clang 10.0.0 (clang1000.11.45.5)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>>
>>> from binary_heap import MinHeap
>>> max_heap = MaxHeap([4, 3, 6, 8, 11])
>>> max_heap.elements()
[11, 8, 6, 4, 3]
>>> max_heap.add_element(13)
>>> max_heap.elements()
[13, 8, 11, 4, 3, 6]
>>> max_heap.add_element([1, 14, 7, 5])
>>> max_heap.elements()
[14, 13, 11, 8, 5, 6, 1, 4, 7, 3]
>>> max_heap.extract_root()
14
>>> max_heap.elements()
[13, 8, 11, 7, 5, 6, 1, 4, 3]
>>> max_heap.get_root_value()
13
>>>
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/binary_heap. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](http://contributorcovenant.org) code of conduct.
License
========
The package is available as open source under the terms of the [GPL3.0 License](https://opensource.org/licenses/GPL3.0).
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/binary_heap/blob/master/CODE_OF_CONDUCT.md).
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