Skip to main content

Python functions for working with Binary Heap

Project description

https://img.shields.io/badge/binary_heap-1.0.2-green.svg https://travis-ci.org/rameshrvr/binary_heap.svg?branch=master

Python library which helps in forming Binary Heaps (Min, Max) using list data structure. 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.

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)
Rameshs-MBP-ead8:binary_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 binary_heap import MinHeap
>>>
>>> min_heap = MinHeap([4, 3, 6, 8, 11])  # Create an object for Min Heap
>>>
>>> min_heap.length()  # Returns size of the heap
5
>>> min_heap.elements()
[3, 4, 6, 8, 11]
>>>
>>> min_heap.add_element(1)  # Add a single element to Heap
>>>
>>> min_heap.elements()
[1, 4, 3, 8, 11, 6]
>>>
>>> min_heap.add_element([1, 14, 7, 5])  # Add list of elements to Heap
>>>
>>> min_heap.elements()
[1, 4, 1, 7, 5, 6, 3, 14, 8, 11]
>>>
>>> min_heap.extract_root()  # Extract root element from Heap and retrun it. In this case its the minimum element
1
>>>
>>> min_heap.elements()
[1, 4, 3, 7, 5, 6, 11, 14, 8]
>>>
>>> min_heap.get_root_value()  # Returns the root value (minimum value) without removing it from Heap
1
>>>
>>> min_heap.search_value(value=5)  # Returns index of the searched value. -1 if there is no such value in Heap
4
>>> min_heap.search_value(value=7)
3
>>> min_heap.search_value(value=16)
-1
>>>
>>> min_heap.delete_element_at_index(3)  # Remove the element at the specified index
>>>
>>> min_heap.elements()
[1, 4, 3, 8, 5, 6, 11, 14]
>>>
  1. Max Heap (Heap where the data in parent node is greater than the data in child node)
Rameshs-MBP-ead8:binary_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 binary_heap import MaxHeap
>>>
>>> max_heap = MaxHeap([4, 3, 6, 8, 11])  # Create an object for Max Heap
>>>
>>> max_heap.elements()  # Returns size of the heap
[11, 8, 6, 4, 3]
>>>
>>> max_heap.add_element(13)  # Add a single element to Heap
>>>
>>> max_heap.elements()
[13, 8, 11, 4, 3, 6]
>>>
>>> max_heap.add_element([1, 14, 7, 5])  # Add list of elements to Heap
>>>
>>> max_heap.elements()
[14, 13, 11, 8, 5, 6, 1, 4, 7, 3]
>>>
>>> max_heap.extract_root()  # Extract root element from Heap and retrun it. In this case its the maximum element
14
>>>
>>> max_heap.elements()
[13, 8, 11, 7, 5, 6, 1, 4, 3]
>>>
>>> max_heap.get_root_value()  # Returns the root value (maximum value) without removing it from Heap
13
>>>
>>> max_heap.search_value(value=11)  # Returns index of the searched value. -1 if there is no such value in Heap
2
>>> max_heap.search_value(value=1)
6
>>> max_heap.search_value(value=14)
-1
>>>
>>> max_heap.delete_element_at_index(3)  # Remove the element at the specified index
>>>
>>> max_heap.elements()
[13, 8, 11, 4, 5, 6, 1, 3]

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://contributor-covenant.org) code of conduct.

License

The package is available as open source under the terms of the [GPL-3.0 License](https://opensource.org/licenses/GPL-3.0).

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).

misc

license:
  • GPL-3.0
authors:
  • Ramesh RV
  • Adithya KS

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
binary_heap-1.0.3.tar.gz (5.0 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page