datreant: persistent, pythonic trees for heterogeneous data

In many fields of science, especially those analyzing experimental or simulation data, there is often an existing ecosystem of specialized tools and file formats which new tools must work around, for better or worse. Furthermore, centralized database solutions may be suboptimal for data storage for a number of reasons, including insufficient hardware infrastructure, variety and heterogeneity of raw data, the need for data portability, etc. This is particularly the case for fields centered around simulation: simulation systems can vary widely in size, composition, rules, paramaters, and starting conditions. And with increases in computational power, it is often necessary to store intermediate results obtained from large amounts of simulation data so it can be accessed and explored interactively.

These problems make data management difficult, and serve as a barrier to answering scientific questions. To make things easier, datreant is a Python package that addresses the tedious and time-consuming logistics of intermediate data storage and retrieval. It solves a boring problem, so we can focus on interesting ones.

For more information on what datreant is and what it does, check out the official documentation.

git clone https://github.com/datreant/datreant.core.git