import functools
import json
import numbers
import operator
import os
import re
import warnings
from time import time
from typing import List, Dict, Any
import numpy as np
from ase.atoms import Atoms
from ase.calculators.calculator import all_properties, all_changes
from ase.data import atomic_numbers
from ase.db.row import AtomsRow
from ase.formula import Formula
from ase.io.jsonio import create_ase_object
from ase.parallel import world, DummyMPI, parallel_function, parallel_generator
from ase.utils import Lock, PurePath
T2000 = 946681200.0 # January 1. 2000
YEAR = 31557600.0 # 365.25 days
# Format of key description: ('short', 'long', 'unit')
default_key_descriptions = {
'id': ('ID', 'Uniqe row ID', ''),
'age': ('Age', 'Time since creation', ''),
'formula': ('Formula', 'Chemical formula', ''),
'pbc': ('PBC', 'Periodic boundary conditions', ''),
'user': ('Username', '', ''),
'calculator': ('Calculator', 'ASE-calculator name', ''),
'energy': ('Energy', 'Total energy', 'eV'),
'natoms': ('Number of atoms', '', ''),
'fmax': ('Maximum force', '', 'eV/Ang'),
'smax': ('Maximum stress', 'Maximum stress on unit cell',
'`\\text{eV/Ang}^3`'),
'charge': ('Charge', 'Net charge in unit cell', '|e|'),
'mass': ('Mass', 'Sum of atomic masses in unit cell', 'au'),
'magmom': ('Magnetic moment', '', 'au'),
'unique_id': ('Unique ID', 'Random (unique) ID', ''),
'volume': ('Volume', 'Volume of unit cell', '`\\text{Ang}^3`')}
def now():
"""Return time since January 1. 2000 in years."""
return (time() - T2000) / YEAR
seconds = {'s': 1,
'm': 60,
'h': 3600,
'd': 86400,
'w': 604800,
'M': 2629800,
'y': YEAR}
longwords = {'s': 'second',
'm': 'minute',
'h': 'hour',
'd': 'day',
'w': 'week',
'M': 'month',
'y': 'year'}
ops = {'<': operator.lt,
'<=': operator.le,
'=': operator.eq,
'>=': operator.ge,
'>': operator.gt,
'!=': operator.ne}
invop = {'<': '>=', '<=': '>', '>=': '<', '>': '<=', '=': '!=', '!=': '='}
word = re.compile('[_a-zA-Z][_0-9a-zA-Z]*$')
reserved_keys = set(all_properties +
all_changes +
list(atomic_numbers) +
['id', 'unique_id', 'ctime', 'mtime', 'user',
'fmax', 'smax',
'momenta', 'constraints', 'natoms', 'formula', 'age',
'calculator', 'calculator_parameters',
'key_value_pairs', 'data'])
numeric_keys = set(['id', 'energy', 'magmom', 'charge', 'natoms'])
def check(key_value_pairs):
for key, value in key_value_pairs.items():
if key == "external_tables":
# Checks for external_tables are not
# performed
continue
if not word.match(key) or key in reserved_keys:
raise ValueError('Bad key: {}'.format(key))
try:
Formula(key, strict=True)
except ValueError:
pass
else:
warnings.warn(
'It is best not to use keys ({0}) that are also a '
'chemical formula. If you do a "db.select({0!r})",'
'you will not find rows with your key. Instead, you wil get '
'rows containing the atoms in the formula!'.format(key))
if not isinstance(value, (numbers.Real, str, np.bool_)):
raise ValueError('Bad value for {!r}: {}'.format(key, value))
if isinstance(value, str):
for t in [int, float]:
if str_represents(value, t):
raise ValueError(
'Value ' + value + ' is put in as string ' +
'but can be interpreted as ' +
'{}! Please convert '.format(t.__name__) +
'to {} using '.format(t.__name__) +
'{}(value) before '.format(t.__name__) +
'writing to the database OR change ' +
'to a different string.')
def str_represents(value, t=int):
try:
t(value)
except ValueError:
return False
return True
[docs]def connect(name, type='extract_from_name', create_indices=True,
use_lock_file=True, append=True, serial=False):
"""Create connection to database.
name: str
Filename or address of database.
type: str
One of 'json', 'db', 'postgresql',
(JSON, SQLite, PostgreSQL).
Default is 'extract_from_name', which will guess the type
from the name.
use_lock_file: bool
You can turn this off if you know what you are doing ...
append: bool
Use append=False to start a new database.
"""
if isinstance(name, PurePath):
name = str(name)
if type == 'extract_from_name':
if name is None:
type = None
elif not isinstance(name, str):
type = 'json'
elif (name.startswith('postgresql://') or
name.startswith('postgres://')):
type = 'postgresql'
elif name.startswith('mysql://') or name.startswith('mariadb://'):
type = 'mysql'
else:
type = os.path.splitext(name)[1][1:]
if type == '':
raise ValueError('No file extension or database type given')
if type is None:
return Database()
if not append and world.rank == 0:
if isinstance(name, str) and os.path.isfile(name):
os.remove(name)
if type not in ['postgresql', 'mysql'] and isinstance(name, str):
name = os.path.abspath(name)
if type == 'json':
from ase.db.jsondb import JSONDatabase
return JSONDatabase(name, use_lock_file=use_lock_file, serial=serial)
if type == 'db':
from ase.db.sqlite import SQLite3Database
return SQLite3Database(name, create_indices, use_lock_file,
serial=serial)
if type == 'postgresql':
from ase.db.postgresql import PostgreSQLDatabase
return PostgreSQLDatabase(name)
if type == 'mysql':
from ase.db.mysql import MySQLDatabase
return MySQLDatabase(name)
raise ValueError('Unknown database type: ' + type)
def lock(method):
"""Decorator for using a lock-file."""
@functools.wraps(method)
def new_method(self, *args, **kwargs):
if self.lock is None:
return method(self, *args, **kwargs)
else:
with self.lock:
return method(self, *args, **kwargs)
return new_method
def convert_str_to_int_float_or_str(value):
"""Safe eval()"""
try:
return int(value)
except ValueError:
try:
value = float(value)
except ValueError:
value = {'True': True, 'False': False}.get(value, value)
return value
def parse_selection(selection, **kwargs):
if selection is None or selection == '':
expressions = []
elif isinstance(selection, int):
expressions = [('id', '=', selection)]
elif isinstance(selection, list):
expressions = selection
else:
expressions = [w.strip() for w in selection.split(',')]
keys = []
comparisons = []
for expression in expressions:
if isinstance(expression, (list, tuple)):
comparisons.append(expression)
continue
if expression.count('<') == 2:
value, expression = expression.split('<', 1)
if expression[0] == '=':
op = '>='
expression = expression[1:]
else:
op = '>'
key = expression.split('<', 1)[0]
comparisons.append((key, op, value))
for op in ['!=', '<=', '>=', '<', '>', '=']:
if op in expression:
break
else: # no break
if expression in atomic_numbers:
comparisons.append((expression, '>', 0))
else:
try:
count = Formula(expression).count()
except ValueError:
keys.append(expression)
else:
comparisons.extend((symbol, '>', n - 1)
for symbol, n in count.items())
continue
key, value = expression.split(op)
comparisons.append((key, op, value))
cmps = []
for key, value in kwargs.items():
comparisons.append((key, '=', value))
for key, op, value in comparisons:
if key == 'age':
key = 'ctime'
op = invop[op]
value = now() - time_string_to_float(value)
elif key == 'formula':
if op != '=':
raise ValueError('Use fomula=...')
f = Formula(value)
count = f.count()
cmps.extend((atomic_numbers[symbol], '=', n)
for symbol, n in count.items())
key = 'natoms'
value = len(f)
elif key in atomic_numbers:
key = atomic_numbers[key]
value = int(value)
elif isinstance(value, str):
value = convert_str_to_int_float_or_str(value)
if key in numeric_keys and not isinstance(value, (int, float)):
msg = 'Wrong type for "{}{}{}" - must be a number'
raise ValueError(msg.format(key, op, value))
cmps.append((key, op, value))
return keys, cmps
[docs]class Database:
"""Base class for all databases."""
def __init__(self, filename=None, create_indices=True,
use_lock_file=False, serial=False):
"""Database object.
serial: bool
Let someone else handle parallelization. Default behavior is
to interact with the database on the master only and then
distribute results to all slaves.
"""
if isinstance(filename, str):
filename = os.path.expanduser(filename)
self.filename = filename
self.create_indices = create_indices
if use_lock_file and isinstance(filename, str):
self.lock = Lock(filename + '.lock', world=DummyMPI())
else:
self.lock = None
self.serial = serial
# Decription of columns and other stuff:
self._metadata: Dict[str, Any] = None
@property
def metadata(self) -> Dict[str, Any]:
raise NotImplementedError
[docs] @parallel_function
@lock
def write(self, atoms, key_value_pairs={}, data={}, id=None, **kwargs):
"""Write atoms to database with key-value pairs.
atoms: Atoms object
Write atomic numbers, positions, unit cell and boundary
conditions. If a calculator is attached, write also already
calculated properties such as the energy and forces.
key_value_pairs: dict
Dictionary of key-value pairs. Values must be strings or numbers.
data: dict
Extra stuff (not for searching).
id: int
Overwrite existing row.
Key-value pairs can also be set using keyword arguments::
connection.write(atoms, name='ABC', frequency=42.0)
Returns integer id of the new row.
"""
if atoms is None:
atoms = Atoms()
kvp = dict(key_value_pairs) # modify a copy
kvp.update(kwargs)
id = self._write(atoms, kvp, data, id)
return id
def _write(self, atoms, key_value_pairs, data, id=None):
check(key_value_pairs)
return 1
[docs] @parallel_function
@lock
def reserve(self, **key_value_pairs):
"""Write empty row if not already present.
Usage::
id = conn.reserve(key1=value1, key2=value2, ...)
Write an empty row with the given key-value pairs and
return the integer id. If such a row already exists, don't write
anything and return None.
"""
for dct in self._select([],
[(key, '=', value)
for key, value in key_value_pairs.items()]):
return None
atoms = Atoms()
calc_name = key_value_pairs.pop('calculator', None)
if calc_name:
# Allow use of calculator key
assert calc_name.lower() == calc_name
# Fake calculator class:
class Fake:
name = calc_name
def todict(self):
return {}
def check_state(self, atoms):
return ['positions']
atoms.calc = Fake()
id = self._write(atoms, key_value_pairs, {}, None)
return id
def __delitem__(self, id):
self.delete([id])
[docs] def get_atoms(self, selection=None, attach_calculator=False,
add_additional_information=False, **kwargs):
"""Get Atoms object.
selection: int, str or list
See the select() method.
attach_calculator: bool
Attach calculator object to Atoms object (default value is
False).
add_additional_information: bool
Put key-value pairs and data into Atoms.info dictionary.
In addition, one can use keyword arguments to select specific
key-value pairs.
"""
row = self.get(selection, **kwargs)
return row.toatoms(attach_calculator, add_additional_information)
def __getitem__(self, selection):
return self.get(selection)
[docs] def get(self, selection=None, **kwargs):
"""Select a single row and return it as a dictionary.
selection: int, str or list
See the select() method.
"""
rows = list(self.select(selection, limit=2, **kwargs))
if not rows:
raise KeyError('no match')
assert len(rows) == 1, 'more than one row matched'
return rows[0]
[docs] @parallel_generator
def select(self, selection=None, filter=None, explain=False,
verbosity=1, limit=None, offset=0, sort=None,
include_data=True, columns='all', **kwargs):
"""Select rows.
Return AtomsRow iterator with results. Selection is done
using key-value pairs and the special keys:
formula, age, user, calculator, natoms, energy, magmom
and/or charge.
selection: int, str or list
Can be:
* an integer id
* a string like 'key=value', where '=' can also be one of
'<=', '<', '>', '>=' or '!='.
* a string like 'key'
* comma separated strings like 'key1<value1,key2=value2,key'
* list of strings or tuples: [('charge', '=', 1)].
filter: function
A function that takes as input a row and returns True or False.
explain: bool
Explain query plan.
verbosity: int
Possible values: 0, 1 or 2.
limit: int or None
Limit selection.
offset: int
Offset into selected rows.
sort: str
Sort rows after key. Prepend with minus sign for a decending sort.
include_data: bool
Use include_data=False to skip reading data from rows.
columns: 'all' or list of str
Specify which columns from the SQL table to include.
For example, if only the row id and the energy is needed,
queries can be speeded up by setting columns=['id', 'energy'].
"""
if sort:
if sort == 'age':
sort = '-ctime'
elif sort == '-age':
sort = 'ctime'
elif sort.lstrip('-') == 'user':
sort += 'name'
keys, cmps = parse_selection(selection, **kwargs)
for row in self._select(keys, cmps, explain=explain,
verbosity=verbosity,
limit=limit, offset=offset, sort=sort,
include_data=include_data,
columns=columns):
if filter is None or filter(row):
yield row
[docs] def count(self, selection=None, **kwargs):
"""Count rows.
See the select() method for the selection syntax. Use db.count() or
len(db) to count all rows.
"""
n = 0
for row in self.select(selection, **kwargs):
n += 1
return n
def __len__(self):
return self.count()
[docs] @parallel_function
@lock
def update(self, id, atoms=None, delete_keys=[], data=None,
**add_key_value_pairs):
"""Update and/or delete key-value pairs of row(s).
id: int
ID of row to update.
atoms: Atoms object
Optionally update the Atoms data (positions, cell, ...).
data: dict
Data dict to be added to the existing data.
delete_keys: list of str
Keys to remove.
Use keyword arguments to add new key-value pairs.
Returns number of key-value pairs added and removed.
"""
if not isinstance(id, numbers.Integral):
if isinstance(id, list):
err = ('First argument must be an int and not a list.\n'
'Do something like this instead:\n\n'
'with db:\n'
' for id in ids:\n'
' db.update(id, ...)')
raise ValueError(err)
raise TypeError('id must be an int')
check(add_key_value_pairs)
row = self._get_row(id)
kvp = row.key_value_pairs
n = len(kvp)
for key in delete_keys:
kvp.pop(key, None)
n -= len(kvp)
m = -len(kvp)
kvp.update(add_key_value_pairs)
m += len(kvp)
moredata = data
data = row.get('data', {})
if moredata:
data.update(moredata)
if not data:
data = None
if atoms:
oldrow = row
row = AtomsRow(atoms)
# Copy over data, kvp, ctime, user and id
row._data = oldrow._data
row.__dict__.update(kvp)
row._keys = list(kvp)
row.ctime = oldrow.ctime
row.user = oldrow.user
row.id = id
if atoms or os.path.splitext(self.filename)[1] == '.json':
self._write(row, kvp, data, row.id)
else:
self._update(row.id, kvp, data)
return m, n
[docs] def delete(self, ids):
"""Delete rows."""
raise NotImplementedError
def time_string_to_float(s):
if isinstance(s, (float, int)):
return s
s = s.replace(' ', '')
if '+' in s:
return sum(time_string_to_float(x) for x in s.split('+'))
if s[-2].isalpha() and s[-1] == 's':
s = s[:-1]
i = 1
while s[i].isdigit():
i += 1
return seconds[s[i:]] * int(s[:i]) / YEAR
def float_to_time_string(t, long=False):
t *= YEAR
for s in 'yMwdhms':
x = t / seconds[s]
if x > 5:
break
if long:
return '{:.3f} {}s'.format(x, longwords[s])
else:
return '{:.0f}{}'.format(round(x), s)
def object_to_bytes(obj: Any) -> bytes:
"""Serialize Python object to bytes."""
parts = [b'12345678']
obj = o2b(obj, parts)
offset = sum(len(part) for part in parts)
x = np.array(offset, np.int64)
if not np.little_endian:
x.byteswap(True)
parts[0] = x.tobytes()
parts.append(json.dumps(obj, separators=(',', ':')).encode())
return b''.join(parts)
def bytes_to_object(b: bytes) -> Any:
"""Deserialize bytes to Python object."""
x = np.frombuffer(b[:8], np.int64)
if not np.little_endian:
x = x.byteswap()
offset = x.item()
obj = json.loads(b[offset:].decode())
return b2o(obj, b)
def o2b(obj: Any, parts: List[bytes]):
if isinstance(obj, (int, float, bool, str, type(None))):
return obj
if isinstance(obj, dict):
return {key: o2b(value, parts) for key, value in obj.items()}
if isinstance(obj, (list, tuple)):
return [o2b(value, parts) for value in obj]
if isinstance(obj, np.ndarray):
assert obj.dtype != object, \
'Cannot convert ndarray of type "object" to bytes.'
offset = sum(len(part) for part in parts)
if not np.little_endian:
obj = obj.byteswap()
parts.append(obj.tobytes())
return {'__ndarray__': [obj.shape,
obj.dtype.name,
offset]}
if isinstance(obj, complex):
return {'__complex__': [obj.real, obj.imag]}
objtype = getattr(obj, 'ase_objtype')
if objtype:
dct = o2b(obj.todict(), parts)
dct['__ase_objtype__'] = objtype
return dct
raise ValueError('Objects of type {type} not allowed'
.format(type=type(obj)))
def b2o(obj: Any, b: bytes) -> Any:
if isinstance(obj, (int, float, bool, str, type(None))):
return obj
if isinstance(obj, list):
return [b2o(value, b) for value in obj]
assert isinstance(obj, dict)
x = obj.get('__complex__')
if x is not None:
return complex(*x)
x = obj.get('__ndarray__')
if x is not None:
shape, name, offset = x
dtype = np.dtype(name)
size = dtype.itemsize * np.prod(shape).astype(int)
a = np.frombuffer(b[offset:offset + size], dtype)
a.shape = shape
if not np.little_endian:
a = a.byteswap()
return a
dct = {key: b2o(value, b) for key, value in obj.items()}
objtype = dct.pop('__ase_objtype__', None)
if objtype is None:
return dct
return create_ase_object(objtype, dct)