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pymatgen is the Python materials analysis library powering the Materials Project (www.materialsproject.org).

Project description

Pymatgen-db is a database add-on for the Python Materials Genomics (pymatgen) materials analysis library. It enables the creation of Materials Project-style databases for management of materials data.

For now, the creation of a MongoDB database is supported and a rudimentary query engine is provided to enable the easy translation of MongoDB docs to useful pymatgen objects for analysis purposes. A simple web-based interface is planned for the future.

Getting pymatgen-db

Stable version

The version at the Python Package Index (PyPI) is always the latest stable release that will be hopefully, be relatively bug-free. The easiest way to install pymatgen on any system is to use easy_install or pip, as follows:

easy_install pymatgen-db

or:

pip install pymatgen-db

Developmental version

The bleeding edge developmental version is at the pymatgen-db’s Github repo. The developmental version is likely to be more buggy, but may contain new features. The Github version include test files as well for complete unit testing. After cloning the source, you can type:

python setup.py install

or to install the package in developmental mode:

python setup.py develop

Requirements

All required python dependencies should be automatically taken care of if you install pymatgen-db using easy_install or pip. Otherwise, these packages should be available on PyPI. Please note that if you do not already have pymatgen installed, you should refer to the pymatgen docs for detailed instructions.

  1. Python 2.7+ required. New default modules such as json are used, as well as new unittest features in Python 2.7.
  2. pymatgen 2.5+, including all dependencies associated with it.
  3. pymongo 2.4+: For interfacing with MongoDb.
  4. MongoDB 2.2+: Get it at the MongoDB website.

Usage

Initial setup

In this step, it is assumed that you have already installed and setup MongoDB on a server of your choice.

A db initialization/insertion script has been written (mgdb) has been written and will be automatically installed as part of the installation process. Type:

mgdb --help

to see all the options.

Before use, first create a database config file by doing:

mgdb init -c db.json

This creates an example json config file, which you should modify as needed for your database.

Inserting calculations

To insert an entire directory of runs (where the topmost directory is “dir_name”) into the database, use the following command:

mgdb insert -c db.json dir_name

Querying a database

The mgdb script allows you to make simple queries from the command line:

# Query for the task id and energy per atom of all calculations with
# formula Li2O. Note that the criteria has to be specified in the form of
# a json string.
mgdb query -c db.json --crit '{"pretty_formula": "Li2O"}' --props task_id energy_per_atom

For more advanced queries, you can use the QueryEngine class. Some examples are as follows:

>>> from matgendb.query_engine import QueryEngine

#Print the task id and formula of all entries in the database.
>>> for r in qe.query(properties=["pretty_formula", "task_id"]):
...     print "{task_id} - {pretty_formula}".format(**r)
...
12 - Li2O

# Get a pymatgen Structure from the task_id.
>>> structure = qe.get_structure_from_id(12)

# Get pymatgen ComputedEntries using a criteria.
>>> entries = qe.get_entries({})

The language follows very closely to pymongo/MongoDB syntax, except that QueryEngine provides useful aliases for commonly used fields as well as translation to commonly used pymatgen objects like Structure and ComputedEntries.

How to cite pymatgen-db

If you use pymatgen and pymatgen-db in your research, please consider citing the following work:

Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy Hautier, Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent Chevrier, Kristin A. Persson, Gerbrand Ceder. Python Materials Genomics (pymatgen) : A Robust, Open-Source Python Library for Materials Analysis. Computational Materials Science, 2013, 68, 314-319. doi:10.1016/j.commatsci.2012.10.028

Project details


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