A library of tools for implementing and consuming OPTiMaDe APIs in Python.
The aim of OPTiMaDe is to develop a common API, compliant with the JSON API 1.0 spec, to enable interoperability among databases that contain calculated properties of existing and hypothetical materials.
This library is under development. Progress is expected during the CECAM Workshop on Open Databases Integration for Materials Design during the week of June 11, 2018 to June 15, 2018.
# Clone this repository to your computer
git clone git@github.com:Materials-Consortia/optimade-python-tools.git
cd optimade-python-tools
# Ensure a Python>=3.6 (virtual) environment (example below using Anaconda/Miniconda)
conda create -n optimade python=3.6
conda activate optimade
# Install package and requirements in editable mode.
pip install -e .
# Optional: Install MongoDB (and set `USE_REAL_MONGO = yes` in optimade/server/congig.ini)
# Below method installs in conda environment and
# - starts server in background
# - ensures and uses ~/dbdata directory to store data
conda install -c anaconda mongodb
mkdir -p ~/dbdata && mongod --dbpath ~/dbdata --syslog --fork
# Start a development server (auto-reload on file changes at http://localhost:5000
# You can also execute ./run.sh
uvicorn optimade.server.main:app --reload --port 5000
# View auto-generated docs
open http://localhost:5000/docs
# View Open API Schema
open http://localhost:5000/openapi.json
Example use:
from optimade.filterparser import Parser
p = Parser(version=(0,9,7))
tree = p.parse("nelements<3")
print(tree)Tree(start, [Token(KEYWORD, 'filter='), Tree(expression, [Tree(term, [Tree(atom, [Tree(comparison, [Token(VALUE, 'a'), Token(OPERATOR, '<'), Token(VALUE, '3')])])])])])
print(tree.pretty())start
expression
term
atom
comparison
nelements
<
3
tree = p.parse('_mp_bandgap > 5.0 AND _cod_molecular_weight < 350')
print(tree.pretty())start
expression
term
term
atom
comparison
_mp_bandgap
>
5.0
AND
atom
comparison
_cod_molecular_weight
<
350
# Assumes graphviz installed on system (e.g. `conda install -c anaconda graphviz`) and `pip install pydot`
from lark.tree import pydot__tree_to_png
pydot__tree_to_png(tree, "exampletree.png")
optimade.filterparser.Parser will take user input to generate a lark.Tree and feed that to a lark.Transformer
(for example, optimade.filtertransformers.mongo.MongoTransformer), which will turn that tree into something useful
to your backend (for example, a MongoDB query dict.)
# Example: Converting to MongoDB Query Syntax
from optimade.filtertransformers.mongo import MongoTransformer
transformer = MongoTransformer()
tree = p.parse('_mp_bandgap > 5.0 AND _cod_molecular_weight < 350')
query = transformer.transform(tree)
print(query){'$and': [{'_mp_bandgap': {'$gt': 5.0}}, {'_cod_molecular_weight': {'$lt': 350.0}}]}
If you would like to add a new transformer, please add
- a module (.py file) in the
optimade/filtertransformersfolder, - any additional Python requirements in
setup.pyandrequirements.txt, - tests in
optimade/filtertransformers/tests.