.. _header:

*********
flat_tree
*********

.. image:: https://img.shields.io/badge/license-MIT-brightgreen.svg
   :target: LICENSE
   :alt: Repository license

.. image:: https://badge.fury.io/py/flat_tree.svg
   :target: https://badge.fury.io/py/flat_tree
   :alt: PyPI Package

.. image:: https://readthedocs.org/projects/flat-tree/badge/?version=latest
   :target: https://flat-tree.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status

.. image:: https://img.shields.io/badge/support-maintainers-brightgreen.svg
   :target: https://decentral1.se/
   :alt: Support badge

.. _introduction:

Utilities for navigating flat trees
-----------------------------------

From `The Dat Protocol`_: 

.. _The Dat Protocol: https://datprotocol.github.io/book/ch01-01-flat-tree.html

    Flat Trees are the core data structure that power Dat's Hypercore feeds. They
    allow us to deterministically represent a tree structure as a vector. This is
    particularly useful because vectors map elegantly to disk and memory.

    Because Flat Trees are deterministic and pre-computed, there is no overhead
    to using them. In effect this means that Flat Trees are a specific way of
    indexing into a vector more than they are their own data structure. This makes
    them uniquely efficient and convenient to implement in a wide range of
    languages.

.. _documentation:

Documentation
*************

* https://flat_tree.readthedocs.io

.. _mirroring:

Mirroring
*********

* https://hack.decentral1.se/datpy/flat_tree (primary)
* https://github.com/datpy/flat_tree