Source code for pymatgen.util.provenance

# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.

Classes and methods related to the Structure Notation Language (SNL)

import sys
import re
import datetime
from collections import namedtuple
import json
from io import StringIO
from monty.json import MontyDecoder, MontyEncoder
from monty.string import remove_non_ascii

from pymatgen.core.structure import Structure, Molecule
from pybtex.database.input import bibtex
from pybtex import errors

__author__ = 'Anubhav Jain, Shyue Ping Ong'
__credits__ = 'Dan Gunter'
__copyright__ = 'Copyright 2013, The Materials Project'
__version__ = '0.1'
__maintainer__ = 'Anubhav Jain'
__email__ = ''
__date__ = 'Feb 11, 2013'

MAX_HNODE_SIZE = 64000  # maximum size (bytes) of SNL HistoryNode
MAX_DATA_SIZE = 256000  # maximum size (bytes) of SNL data field
MAX_HNODES = 100  # maximum number of HistoryNodes in SNL file
MAX_BIBTEX_CHARS = 20000  # maximum number of characters for BibTeX reference

[docs]def is_valid_bibtex(reference): """ Use pybtex to validate that a reference is in proper BibTeX format Args: reference: A String reference in BibTeX format. Returns: Boolean indicating if reference is valid bibtex. """ # str is necessary since pybtex seems to have an issue with unicode. The # filter expression removes all non-ASCII characters. sio = StringIO(remove_non_ascii(reference)) parser = bibtex.Parser() errors.set_strict_mode(False) bib_data = parser.parse_stream(sio) return len(bib_data.entries) > 0
[docs]class HistoryNode(namedtuple('HistoryNode', ['name', 'url', 'description'])): """ A HistoryNode represents a step in the chain of events that lead to a Structure. HistoryNodes leave 'breadcrumbs' so that you can trace back how a Structure was created. For example, a HistoryNode might represent pulling a Structure from an external database such as the ICSD or CSD. Or, it might represent the application of a code (e.g. pymatgen) to the Structure, with a custom description of how that code was applied (e.g. a site removal Transformation was applied). A HistoryNode contains three fields: .. attribute:: name The name of a code or resource that this Structure encountered in its history (String) .. attribute:: url The URL of that code/resource (String) .. attribute:: description A free-form description of how the code/resource is related to the Structure (dict). """
[docs] def as_dict(self): """ Returns: Dict """ return {"name":, "url": self.url, "description": self.description}
[docs] @staticmethod def from_dict(h_node): """ Args: d (dict): Dict representation Returns: HistoryNode """ return HistoryNode(h_node['name'], h_node['url'], h_node['description'])
[docs] @staticmethod def parse_history_node(h_node): """ Parses a History Node object from either a dict or a tuple. Args: h_node: A dict with name/url/description fields or a 3-element tuple. Returns: History node. """ if isinstance(h_node, dict): return HistoryNode.from_dict(h_node) else: if len(h_node) != 3: raise ValueError("Invalid History node, " "should be dict or (name, version, " "description) tuple: {}".format(h_node)) return HistoryNode(h_node[0], h_node[1], h_node[2])
[docs]class Author(namedtuple('Author', ['name', 'email'])): """ An Author contains two fields: .. attribute:: name Name of author (String) .. attribute:: email Email of author (String) """ def __str__(self): """ String representation of an Author """ return '{} <{}>'.format(,
[docs] def as_dict(self): """ Returns: MSONable dict. """ return {"name":, "email":}
[docs] @staticmethod def from_dict(d): """ Args: d (dict): Dict representation Returns: Author """ return Author(d['name'], d['email'])
[docs] @staticmethod def parse_author(author): """ Parses an Author object from either a String, dict, or tuple Args: author: A String formatted as "NAME <>", (name, email) tuple, or a dict with name and email keys. Returns: An Author object. """ if isinstance(author, str): # Regex looks for whitespace, (any name), whitespace, <, (email), # >, whitespace m = re.match(r'\s*(.*?)\s*<(.*?@.*?)>\s*', author) if not m or m.start() != 0 or m.end() != len(author): raise ValueError("Invalid author format! {}".format(author)) return Author(m.groups()[0], m.groups()[1]) elif isinstance(author, dict): return Author.from_dict(author) else: if len(author) != 2: raise ValueError("Invalid author, should be String or (name, " "email) tuple: {}".format(author)) return Author(author[0], author[1])
[docs]class StructureNL: """ The Structure Notation Language (SNL, pronounced 'snail') is container for a pymatgen Structure/Molecule object with some additional fields for enhanced provenance. It is meant to be imported/exported in a JSON file format with the following structure: - about - created_at - authors - projects - references - remarks - data - history - lattice (optional) - sites """ def __init__(self, struct_or_mol, authors, projects=None, references='', remarks=None, data=None, history=None, created_at=None): """ Args: struct_or_mol: A pymatgen.core.structure Structure/Molecule object authors: *List* of {"name":'', "email":''} dicts, *list* of Strings as 'John Doe <>', or a single String with commas separating authors projects: List of Strings ['Project A', 'Project B'] references: A String in BibTeX format remarks: List of Strings ['Remark A', 'Remark B'] data: A free form dict. Namespaced at the root level with an underscore, e.g. {"_materialsproject": <custom data>} history: List of dicts - [{'name':'', 'url':'', 'description':{}}] created_at: A datetime object """ # initialize root-level structure keys self.structure = struct_or_mol # turn authors into list of Author objects authors = authors.split(',')\ if isinstance(authors, str) else authors self.authors = [Author.parse_author(a) for a in authors] # turn projects into list of Strings projects = projects if projects else [] self.projects = [projects] if isinstance(projects, str) else projects # check that references are valid BibTeX if not isinstance(references, str): raise ValueError("Invalid format for SNL reference! Should be " "empty string or BibTeX string.") if references and not is_valid_bibtex(references): raise ValueError("Invalid format for SNL reference! Should be " "BibTeX string.") if len(references) > MAX_BIBTEX_CHARS: raise ValueError("The BibTeX string must be fewer than {} chars " ", you have {}" .format(MAX_BIBTEX_CHARS, len(references))) self.references = references # turn remarks into list of Strings remarks = remarks if remarks else [] self.remarks = [remarks] if isinstance(remarks, str) else remarks # check remarks limit for r in self.remarks: if len(r) > 140: raise ValueError("The remark exceeds the maximum size of" "140 characters: {}".format(r)) # check data limit = data if data else {} if not sys.getsizeof( < MAX_DATA_SIZE: raise ValueError("The data dict exceeds the maximum size limit of" " {} bytes (you have {})" .format(MAX_DATA_SIZE, sys.getsizeof(data))) for k, v in if not k.startswith("_"): raise ValueError("data must contain properly namespaced data " "with keys starting with an underscore. The " "key {} does not start with an underscore.", format(k)) # check for valid history nodes history = history if history else [] # initialize null fields if len(history) > MAX_HNODES: raise ValueError("A maximum of {} History nodes are supported, " "you have {}!".format(MAX_HNODES, len(history))) self.history = [HistoryNode.parse_history_node(h) for h in history] if not all([sys.getsizeof(h) < MAX_HNODE_SIZE for h in history]): raise ValueError("One or more history nodes exceeds the maximum " "size limit of {} bytes".format(MAX_HNODE_SIZE)) self.created_at = created_at if created_at \ else datetime.datetime.utcnow()
[docs] def as_dict(self): """ Returns: MSONable dict """ d = self.structure.as_dict() d["@module"] = self.__class__.__module__ d["@class"] = self.__class__.__name__ d["about"] = {"authors": [a.as_dict() for a in self.authors], "projects": self.projects, "references": self.references, "remarks": self.remarks, "history": [h.as_dict() for h in self.history], "created_at": json.loads(json.dumps(self.created_at, cls=MontyEncoder))} d["about"].update(json.loads(json.dumps(, cls=MontyEncoder))) return d
[docs] @classmethod def from_dict(cls, d): """ Args: d (dict): Dict representation Returns: Class """ a = d["about"] dec = MontyDecoder() created_at = dec.process_decoded(a.get("created_at")) data = {k: v for k, v in d["about"].items() if k.startswith("_")} data = dec.process_decoded(data) structure = Structure.from_dict(d) if "lattice" in d \ else Molecule.from_dict(d) return cls(structure, a["authors"], projects=a.get("projects", None), references=a.get("references", ""), remarks=a.get("remarks", None), data=data, history=a.get("history", None), created_at=created_at)
[docs] @classmethod def from_structures(cls, structures, authors, projects=None, references='', remarks=None, data=None, histories=None, created_at=None): """ A convenience method for getting a list of StructureNL objects by specifying structures and metadata separately. Some of the metadata is applied to all of the structures for ease of use. Args: structures: A list of Structure objects authors: *List* of {"name":'', "email":''} dicts, *list* of Strings as 'John Doe <>', or a single String with commas separating authors projects: List of Strings ['Project A', 'Project B']. This applies to all structures. references: A String in BibTeX format. Again, this applies to all structures. remarks: List of Strings ['Remark A', 'Remark B'] data: A list of free form dict. Namespaced at the root level with an underscore, e.g. {"_materialsproject":<custom data>} . The length of data should be the same as the list of structures if not None. histories: List of list of dicts - [[{'name':'', 'url':'', 'description':{}}], ...] The length of histories should be the same as the list of structures if not None. created_at: A datetime object """ data = [{}] * len(structures) if data is None else data histories = [[]] * len(structures) if histories is None else \ histories snl_list = [] for i, struct in enumerate(structures): snl = StructureNL(struct, authors, projects=projects, references=references, remarks=remarks, data=data[i], history=histories[i], created_at=created_at) snl_list.append(snl) return snl_list
def __str__(self): return "\n".join(["{}\n{}".format(k, getattr(self, k)) for k in ("structure", "authors", "projects", "references", "remarks", "data", "history", "created_at")]) def __eq__(self, other): return all(map(lambda n: getattr(self, n) == getattr(other, n), ("structure", "authors", "projects", "references", "remarks", "data", "history", "created_at"))) def __ne__(self, other): return not self.__eq__(other)