This library is a collection of data structures that are not included in the Python standard library. The goal is to provide a Pythonic interface to these data structures, making them easier to use and more intuitive.

I created this library because I wanted to learn more about data structures and algorithms. I also wanted to create a library that would be useful to other Python developers. I hope that this library will help you learn more about data structures and algorithms, and that it will be useful in your own projects.

• Custom Data Structures: Implementations of data structures like heaps, tries, and graphs that are not part of the standard library.
• Pythonic Interfaces: Designed with a focus on usability and readability, following Python's idiomatic conventions.
• Efficiency: Optimized for performance with a focus on minimizing time and space complexity.
• Extensibility: Easily extendable to include new data structures or modify existing ones.

You can clone the repository and install it manually:

git clone https://github.com/nicholasadamou/databricks.git
cd databricks
python setup.py install

This library is not part of PyPI because the name databricks has already been used.

Here's a quick example of how to use one of the data structures in this library:

from databricks import Heap

# By default, the heap is a min-heap

heap = Heap[int]()
heap.insert(10)
heap.insert(5)
heap.insert(20)

print(heap.pop())  # Outputs: 5

To ensure the reliability and correctness of the library, a comprehensive suite of tests is included. You can run the tests using pytest:

1. Install pytest if you haven't already:

   pip install pytest

2. Run the tests:

   pytest

This will find and execute all the test cases and provide a summary of the results.

This project is licensed under the MIT License. See the LICENSE file for more details.