Source code for monty.json

"""
JSON serialization and deserialization utilities.
"""

import datetime
import json
import os
import types
from collections import OrderedDict, defaultdict
from enum import Enum
from hashlib import sha1
from importlib import import_module
from inspect import getfullargspec
from uuid import UUID

try:
    import numpy as np
except ImportError:
    np = None  # type: ignore

try:
    import pandas as pd
except ImportError:
    pd = None  # type: ignore

try:
    import pydantic
except ImportError:
    pydantic = None  # type: ignore

try:
    import bson
except ImportError:
    bson = None

try:
    from ruamel.yaml import YAML
except ImportError:
    YAML = None  # type: ignore

try:
    import orjson
except ImportError:
    orjson = None  # type: ignore

__version__ = "3.0.0"


def _load_redirect(redirect_file):
    try:
        with open(redirect_file) as f:
            yaml = YAML()
            d = yaml.load(f)
    except OSError:
        # If we can't find the file
        # Just use an empty redirect dict
        return {}

    # Convert the full paths to module/class
    redirect_dict = defaultdict(dict)
    for old_path, new_path in d.items():
        old_class = old_path.split(".")[-1]
        old_module = ".".join(old_path.split(".")[:-1])

        new_class = new_path.split(".")[-1]
        new_module = ".".join(new_path.split(".")[:-1])

        redirect_dict[old_module][old_class] = {
            "@module": new_module,
            "@class": new_class,
        }

    return dict(redirect_dict)


[docs]class MSONable: """ This is a mix-in base class specifying an API for msonable objects. MSON is Monty JSON. Essentially, MSONable objects must implement an as_dict method, which must return a json serializable dict and must also support no arguments (though optional arguments to finetune the output is ok), and a from_dict class method that regenerates the object from the dict generated by the as_dict method. The as_dict method should contain the "@module" and "@class" keys which will allow the MontyEncoder to dynamically deserialize the class. E.g.:: d["@module"] = self.__class__.__module__ d["@class"] = self.__class__.__name__ A default implementation is provided in MSONable, which automatically determines if the class already contains self.argname or self._argname attributes for every arg. If so, these will be used for serialization in the dict format. Similarly, the default from_dict will deserialization classes of such form. An example is given below:: class MSONClass(MSONable): def __init__(self, a, b, c, d=1, **kwargs): self.a = a self.b = b self._c = c self._d = d self.kwargs = kwargs For such classes, you merely need to inherit from MSONable and you do not need to implement your own as_dict or from_dict protocol. New to Monty V2.0.6.... Classes can be redirected to moved implementations by putting in the old fully qualified path and new fully qualified path into .monty.yaml in the home folder Example: old_module.old_class: new_module.new_class """ REDIRECT = _load_redirect(os.path.join(os.path.expanduser("~"), ".monty.yaml"))
[docs] def as_dict(self) -> dict: """ A JSON serializable dict representation of an object. """ d = {"@module": self.__class__.__module__, "@class": self.__class__.__name__} try: parent_module = self.__class__.__module__.split(".", maxsplit=1)[0] module_version = import_module(parent_module).__version__ # type: ignore d["@version"] = str(module_version) except (AttributeError, ImportError): d["@version"] = None # type: ignore spec = getfullargspec(self.__class__.__init__) args = spec.args def recursive_as_dict(obj): if isinstance(obj, (list, tuple)): return [recursive_as_dict(it) for it in obj] if isinstance(obj, dict): return {kk: recursive_as_dict(vv) for kk, vv in obj.items()} if hasattr(obj, "as_dict"): return obj.as_dict() return obj for c in args: if c != "self": try: a = self.__getattribute__(c) except AttributeError: try: a = self.__getattribute__("_" + c) except AttributeError: raise NotImplementedError( "Unable to automatically determine as_dict " "format from class. MSONAble requires all " "args to be present as either self.argname or " "self._argname, and kwargs to be present under" "a self.kwargs variable to automatically " "determine the dict format. Alternatively, " "you can implement both as_dict and from_dict." ) d[c] = recursive_as_dict(a) if hasattr(self, "kwargs"): # type: ignore d.update(**getattr(self, "kwargs")) # pylint: disable=E1101 if spec.varargs is not None and getattr(self, spec.varargs, None) is not None: d.update({spec.varargs: getattr(self, spec.varargs)}) if hasattr(self, "_kwargs"): d.update(**getattr(self, "_kwargs")) # pylint: disable=E1101 if isinstance(self, Enum): d.update({"value": self.value}) # pylint: disable=E1101 return d
[docs] @classmethod def from_dict(cls, d): """ :param d: Dict representation. :return: MSONable class. """ decoded = {k: MontyDecoder().process_decoded(v) for k, v in d.items() if not k.startswith("@")} return cls(**decoded)
[docs] def to_json(self) -> str: """ Returns a json string representation of the MSONable object. """ return json.dumps(self, cls=MontyEncoder)
[docs] def unsafe_hash(self): """ Returns an hash of the current object. This uses a generic but low performance method of converting the object to a dictionary, flattening any nested keys, and then performing a hash on the resulting object """ def flatten(obj, seperator="."): # Flattens a dictionary flat_dict = {} for key, value in obj.items(): if isinstance(value, dict): flat_dict.update({seperator.join([key, _key]): _value for _key, _value in flatten(value).items()}) elif isinstance(value, list): list_dict = {f"{key}{seperator}{num}": item for num, item in enumerate(value)} flat_dict.update(flatten(list_dict)) else: flat_dict[key] = value return flat_dict ordered_keys = sorted(flatten(jsanitize(self.as_dict())).items(), key=lambda x: x[0]) ordered_keys = [item for item in ordered_keys if "@" not in item[0]] return sha1(json.dumps(OrderedDict(ordered_keys)).encode("utf-8"))
@classmethod def __get_validators__(cls): """Return validators for use in pydantic""" yield cls.validate_monty
[docs] @classmethod def validate_monty(cls, v): """ pydantic Validator for MSONable pattern """ if isinstance(v, cls): return v if isinstance(v, dict): new_obj = MontyDecoder().process_decoded(v) if isinstance(new_obj, cls): return new_obj new_obj = cls(**v) return new_obj raise ValueError(f"Must provide {cls.__name__}, the as_dict form, or the proper")
@classmethod def __modify_schema__(cls, field_schema): """JSON schema for MSONable pattern""" field_schema.update( { "type": "object", "properties": { "@class": {"enum": [cls.__name__], "type": "string"}, "@module": {"enum": [cls.__module__], "type": "string"}, "@version": {"type": "string"}, }, "required": ["@class", "@module"], } )
[docs]class MontyEncoder(json.JSONEncoder): """ A Json Encoder which supports the MSONable API, plus adds support for numpy arrays, datetime objects, bson ObjectIds (requires bson). Usage:: # Add it as a *cls* keyword when using json.dump json.dumps(object, cls=MontyEncoder) """
[docs] def default(self, o) -> dict: # pylint: disable=E0202 """ Overriding default method for JSON encoding. This method does two things: (a) If an object has a to_dict property, return the to_dict output. (b) If the @module and @class keys are not in the to_dict, add them to the output automatically. If the object has no to_dict property, the default Python json encoder default method is called. Args: o: Python object. Return: Python dict representation. """ if isinstance(o, datetime.datetime): return {"@module": "datetime", "@class": "datetime", "string": o.__str__()} if isinstance(o, UUID): return {"@module": "uuid", "@class": "UUID", "string": o.__str__()} if np is not None: if isinstance(o, np.ndarray): if str(o.dtype).startswith("complex"): return { "@module": "numpy", "@class": "array", "dtype": o.dtype.__str__(), "data": [o.real.tolist(), o.imag.tolist()], } return { "@module": "numpy", "@class": "array", "dtype": o.dtype.__str__(), "data": o.tolist(), } if isinstance(o, np.generic): return o.item() if pd is not None: if isinstance(o, pd.DataFrame): return { "@module": "pandas", "@class": "DataFrame", "data": o.to_json(default_handler=MontyEncoder().encode), } if isinstance(o, pd.Series): return { "@module": "pandas", "@class": "Series", "data": o.to_json(default_handler=MontyEncoder().encode), } if bson is not None: if isinstance(o, bson.objectid.ObjectId): return {"@module": "bson.objectid", "@class": "ObjectId", "oid": str(o)} if callable(o) and not isinstance(o, MSONable): return _serialize_callable(o) try: if pydantic is not None and isinstance(o, pydantic.BaseModel): d = o.dict() else: d = o.as_dict() if "@module" not in d: d["@module"] = str(o.__class__.__module__) if "@class" not in d: d["@class"] = str(o.__class__.__name__) if "@version" not in d: try: parent_module = o.__class__.__module__.split(".")[0] module_version = import_module(parent_module).__version__ # type: ignore d["@version"] = str(module_version) except (AttributeError, ImportError): d["@version"] = None return d except AttributeError: return json.JSONEncoder.default(self, o)
[docs]class MontyDecoder(json.JSONDecoder): """ A Json Decoder which supports the MSONable API. By default, the decoder attempts to find a module and name associated with a dict. If found, the decoder will generate a Pymatgen as a priority. If that fails, the original decoded dictionary from the string is returned. Note that nested lists and dicts containing pymatgen object will be decoded correctly as well. Usage: # Add it as a *cls* keyword when using json.load json.loads(json_string, cls=MontyDecoder) """
[docs] def process_decoded(self, d): """ Recursive method to support decoding dicts and lists containing pymatgen objects. """ if isinstance(d, dict): if "@module" in d and "@class" in d: modname = d["@module"] classname = d["@class"] if classname in MSONable.REDIRECT.get(modname, {}): modname = MSONable.REDIRECT[modname][classname]["@module"] classname = MSONable.REDIRECT[modname][classname]["@class"] elif "@module" in d and "@callable" in d: modname = d["@module"] objname = d["@callable"] classname = None if d.get("@bound", None) is not None: # if the function is bound to an instance or class, first # deserialize the bound object and then remove the object name # from the function name. obj = self.process_decoded(d["@bound"]) objname = objname.split(".")[1:] else: # if the function is not bound to an object, import the # function from the module name obj = __import__(modname, globals(), locals(), [objname], 0) objname = objname.split(".") try: # the function could be nested. e.g., MyClass.NestedClass.function # so iteratively access the nesting for attr in objname: obj = getattr(obj, attr) return obj except AttributeError: pass else: modname = None classname = None if classname: if modname and modname not in ["bson.objectid", "numpy", "pandas"]: if modname == "datetime" and classname == "datetime": try: dt = datetime.datetime.strptime(d["string"], "%Y-%m-%d %H:%M:%S.%f") except ValueError: dt = datetime.datetime.strptime(d["string"], "%Y-%m-%d %H:%M:%S") return dt if modname == "uuid" and classname == "UUID": return UUID(d["string"]) mod = __import__(modname, globals(), locals(), [classname], 0) if hasattr(mod, classname): cls_ = getattr(mod, classname) data = {k: v for k, v in d.items() if not k.startswith("@")} if hasattr(cls_, "from_dict"): return cls_.from_dict(data) if pydantic is not None and issubclass(cls_, pydantic.BaseModel): return cls_(**data) elif np is not None and modname == "numpy" and classname == "array": if d["dtype"].startswith("complex"): return np.array( [np.array(r) + np.array(i) * 1j for r, i in zip(*d["data"])], dtype=d["dtype"], ) return np.array(d["data"], dtype=d["dtype"]) elif pd is not None and modname == "pandas": if classname == "DataFrame": decoded_data = MontyDecoder().decode(d["data"]) return pd.DataFrame(decoded_data) if classname == "Series": decoded_data = MontyDecoder().decode(d["data"]) return pd.Series(decoded_data) elif (bson is not None) and modname == "bson.objectid" and classname == "ObjectId": return bson.objectid.ObjectId(d["oid"]) return {self.process_decoded(k): self.process_decoded(v) for k, v in d.items()} if isinstance(d, list): return [self.process_decoded(x) for x in d] return d
[docs] def decode(self, s): """ Overrides decode from JSONDecoder. :param s: string :return: Object. """ if orjson is not None: try: d = orjson.loads(s) # pylint: disable=E1101 except orjson.JSONDecodeError: # pylint: disable=E1101 d = json.loads(s) else: d = json.loads(s) return self.process_decoded(d)
[docs]class MSONError(Exception): """ Exception class for serialization errors. """
[docs]def jsanitize(obj, strict=False, allow_bson=False, enum_values=False, recursive_msonable=False): """ This method cleans an input json-like object, either a list or a dict or some sequence, nested or otherwise, by converting all non-string dictionary keys (such as int and float) to strings, and also recursively encodes all objects using Monty's as_dict() protocol. Args: obj: input json-like object. strict (bool): This parameters sets the behavior when jsanitize encounters an object it does not understand. If strict is True, jsanitize will try to get the as_dict() attribute of the object. If no such attribute is found, an attribute error will be thrown. If strict is False, jsanitize will simply call str(object) to convert the object to a string representation. allow_bson (bool): This parameters sets the behavior when jsanitize encounters a bson supported type such as objectid and datetime. If True, such bson types will be ignored, allowing for proper insertion into MongoDB databases. enum_values (bool): Convert Enums to their values. recursive_msonable (bool): If True, uses .as_dict() for MSONables regardless of the value of strict. Returns: Sanitized dict that can be json serialized. """ if isinstance(obj, Enum) and enum_values: return obj.value if allow_bson and ( isinstance(obj, (datetime.datetime, bytes)) or (bson is not None and isinstance(obj, bson.objectid.ObjectId)) ): return obj if isinstance(obj, (list, tuple)): return [jsanitize(i, strict=strict, allow_bson=allow_bson, enum_values=enum_values) for i in obj] if np is not None and isinstance(obj, np.ndarray): return [jsanitize(i, strict=strict, allow_bson=allow_bson, enum_values=enum_values) for i in obj.tolist()] if np is not None and isinstance(obj, np.generic): return obj.item() if pd is not None and isinstance(obj, (pd.Series, pd.DataFrame)): return obj.to_dict() if isinstance(obj, dict): return { k.__str__(): jsanitize( v, strict=strict, allow_bson=allow_bson, enum_values=enum_values, recursive_msonable=recursive_msonable, ) for k, v in obj.items() } if isinstance(obj, (int, float)): return obj if obj is None: return None if callable(obj) and not isinstance(obj, MSONable): try: return _serialize_callable(obj) except TypeError: pass if recursive_msonable and isinstance(obj, MSONable): return obj.as_dict() if not strict: return obj.__str__() if isinstance(obj, str): return obj.__str__() if pydantic is not None and isinstance(obj, pydantic.BaseModel): return jsanitize( MontyEncoder().default(obj), strict=strict, allow_bson=allow_bson, enum_values=enum_values, recursive_msonable=recursive_msonable, ) return jsanitize( obj.as_dict(), strict=strict, allow_bson=allow_bson, enum_values=enum_values, recursive_msonable=recursive_msonable, )
def _serialize_callable(o): if isinstance(o, types.BuiltinFunctionType): # don't care about what builtin functions (sum, open, etc) are bound to bound = None else: # bound methods (i.e., instance methods) have a __self__ attribute # that points to the class/module/instance bound = getattr(o, "__self__", None) # we are only able to serialize bound methods if the object the method is # bound to is itself serializable if bound is not None: try: bound = MontyEncoder().default(bound) except TypeError: raise TypeError("Only bound methods of classes or MSONable instances are supported.") return { "@module": o.__module__, "@callable": getattr(o, "__qualname__", o.__name__), "@bound": bound, }