"""
Spawner
The spawner takes input files containing object definitions in
dictionary forms. These use a prototype architecture to define
unique objects without having to make a Typeclass for each.
There main function is `spawn(*prototype)`, where the `prototype`
is a dictionary like this:
```python
from evennia.prototypes import prototypes, spawner
prot = {
"prototype_key": "goblin",
"typeclass": "types.objects.Monster",
"key": "goblin grunt",
"health": lambda: randint(20,30),
"resists": ["cold", "poison"],
"attacks": ["fists"],
"weaknesses": ["fire", "light"]
"tags": ["mob", "evil", ('greenskin','mob')]
"attrs": [("weapon", "sword")]
}
# spawn something with the prototype
goblin = spawner.spawn(prot)
# make this into a db-saved prototype (optional)
prot = prototypes.create_prototype(prot)
```
Possible keywords are:
prototype_key (str): name of this prototype. This is used when storing prototypes and should
be unique. This should always be defined but for prototypes defined in modules, the
variable holding the prototype dict will become the prototype_key if it's not explicitly
given.
prototype_desc (str, optional): describes prototype in listings
prototype_locks (str, optional): locks for restricting access to this prototype. Locktypes
supported are 'edit' and 'use'.
prototype_tags(list, optional): List of tags or tuples (tag, category) used to group prototype
in listings
prototype_parent (str, tuple or callable, optional): name (prototype_key) of eventual parent
prototype, or a list of parents, for multiple left-to-right inheritance.
prototype: Deprecated. Same meaning as 'parent'.
typeclass (str or callable, optional): if not set, will use typeclass of parent prototype or use
`settings.BASE_OBJECT_TYPECLASS`
key (str or callable, optional): the name of the spawned object. If not given this will set to a
random hash
location (obj, str or callable, optional): location of the object - a valid object or #dbref
home (obj, str or callable, optional): valid object or #dbref
destination (obj, str or callable, optional): only valid for exits (object or #dbref)
permissions (str, list or callable, optional): which permissions for spawned object to have
locks (str or callable, optional): lock-string for the spawned object
aliases (str, list or callable, optional): Aliases for the spawned object
exec (str or callable, optional): this is a string of python code to execute or a list of such
codes. This can be used e.g. to trigger custom handlers on the object. The execution
namespace contains 'evennia' for the library and 'obj'. All default spawn commands limit
this functionality to Developer/superusers. Usually it's better to use callables or
prototypefuncs instead of this.
tags (str, tuple, list or callable, optional): string or list of strings or tuples
`(tagstr, category)`. Plain strings will be result in tags with no category (default tags).
attrs (tuple, list or callable, optional): tuple or list of tuples of Attributes to add. This
form allows more complex Attributes to be set. Tuples at least specify `(key, value)`
but can also specify up to `(key, value, category, lockstring)`. If you want to specify a
lockstring but not a category, set the category to `None`.
ndb_<name> (any): value of a nattribute (ndb_ is stripped) - this is of limited use.
other (any): any other name is interpreted as the key of an Attribute with
its value. Such Attributes have no categories.
Each value can also be a callable that takes no arguments. It should
return the value to enter into the field and will be called every time
the prototype is used to spawn an object. Note, if you want to store
a callable in an Attribute, embed it in a tuple to the `args` keyword.
By specifying the "prototype_parent" key, the prototype becomes a child of
the given prototype, inheritng all prototype slots it does not explicitly
define itself, while overloading those that it does specify.
```python
import random
{
"prototype_key": "goblin_wizard",
"prototype_parent": "GOBLIN",
"key": "goblin wizard",
"spells": ["fire ball", "lighting bolt"]
}
GOBLIN_ARCHER = {
"prototype_parent": "GOBLIN",
"key": "goblin archer",
"attack_skill": (random, (5, 10))"
"attacks": ["short bow"]
}
```
One can also have multiple prototypes. These are inherited from the
left, with the ones further to the right taking precedence.
```python
ARCHWIZARD = {
"attack": ["archwizard staff", "eye of doom"]
GOBLIN_ARCHWIZARD = {
"key" : "goblin archwizard"
"prototype_parent": ("GOBLIN_WIZARD", "ARCHWIZARD"),
}
```
The *goblin archwizard* will have some different attacks, but will
otherwise have the same spells as a *goblin wizard* who in turn shares
many traits with a normal *goblin*.
Storage mechanism:
This sets up a central storage for prototypes. The idea is to make these
available in a repository for buildiers to use. Each prototype is stored
in a Script so that it can be tagged for quick sorting/finding and locked for limiting
access.
This system also takes into consideration prototypes defined and stored in modules.
Such prototypes are considered 'read-only' to the system and can only be modified
in code. To replace a default prototype, add the same-name prototype in a
custom module read later in the settings.PROTOTYPE_MODULES list. To remove a default
prototype, override its name with an empty dict.
"""
import copy
import hashlib
import time
from django.conf import settings
from django.utils.translation import gettext as _
import evennia
from evennia.objects.models import ObjectDB
from evennia.prototypes import prototypes as protlib
from evennia.prototypes.prototypes import (
PROTOTYPE_TAG_CATEGORY,
init_spawn_value,
search_prototype,
value_to_obj,
value_to_obj_or_any,
)
from evennia.utils import logger
from evennia.utils.utils import class_from_module, is_iter, make_iter
_CREATE_OBJECT_KWARGS = ("key", "location", "home", "destination")
_PROTOTYPE_META_NAMES = (
"prototype_key",
"prototype_desc",
"prototype_tags",
"prototype_locks",
"prototype_parent",
)
_PROTOTYPE_ROOT_NAMES = (
"typeclass",
"key",
"aliases",
"attrs",
"tags",
"locks",
"permissions",
"location",
"home",
"destination",
)
_NON_CREATE_KWARGS = _CREATE_OBJECT_KWARGS + _PROTOTYPE_META_NAMES
[docs]class Unset:
"""
Helper class representing a non-set diff element.
"""
def __bool__(self):
return False
def __str__(self):
return "<Unset>"
# Helper
def _get_prototype(inprot, protparents=None, uninherited=None, _workprot=None):
"""
Recursively traverse a prototype dictionary, including multiple
inheritance. Use validate_prototype before this, we don't check
for infinite recursion here.
Args:
inprot (dict): Prototype dict (the individual prototype, with no inheritance included).
protparents (dict): Custom protparents, supposedly provided specifically for this `inprot`.
If given, any parents will first be looked up in this dict, and then by searching
the global prototype store given by settings/db.
uninherited (dict): Parts of prototype to not inherit.
_workprot (dict, optional): Work dict for the recursive algorithm.
Returns:
merged (dict): A prototype where parent's have been merged as needed (the
`prototype_parent` key is removed).
"""
def _inherit_tags(old_tags, new_tags):
old = {(tup[0], tup[1]): tup for tup in old_tags}
new = {(tup[0], tup[1]): tup for tup in new_tags}
old.update(new)
return list(old.values())
def _inherit_attrs(old_attrs, new_attrs):
old = {(tup[0], tup[2]): tup for tup in old_attrs}
new = {(tup[0], tup[2]): tup for tup in new_attrs}
old.update(new)
return list(old.values())
protparents = {} if protparents is None else protparents
_workprot = {} if _workprot is None else _workprot
if "prototype_parent" in inprot:
# move backwards through the inheritance
prototype_parents = inprot["prototype_parent"]
if isinstance(prototype_parents, dict):
# protparent already embedded as-is
prototype_parents = [prototype_parents]
for prototype in make_iter(prototype_parents):
if isinstance(prototype, dict):
# protparent already embedded as-is
parent_prototype = prototype
else:
# protparent given by-name, first search provided parents, then global store
parent_prototype = protparents.get(prototype.lower())
if not parent_prototype:
parent_prototype = search_prototype(key=prototype.lower()) or {}
if parent_prototype:
parent_prototype = parent_prototype[0]
# Build the prot dictionary in reverse order, overloading
new_prot = _get_prototype(parent_prototype, protparents, _workprot=_workprot)
# attrs, tags have internal structure that should be inherited separately
new_prot["attrs"] = _inherit_attrs(
_workprot.get("attrs", {}), new_prot.get("attrs", [])
)
new_prot["tags"] = _inherit_tags(_workprot.get("tags", []), new_prot.get("tags", []))
_workprot.update(new_prot)
# the inprot represents a higher level (a child prot), which should override parents
inprot["attrs"] = _inherit_attrs(_workprot.get("attrs", []), inprot.get("attrs", []))
inprot["tags"] = _inherit_tags(_workprot.get("tags", []), inprot.get("tags", []))
_workprot.update(inprot)
if uninherited:
# put back the parts that should not be inherited
_workprot.update(uninherited)
_workprot.pop("prototype_parent", None) # we don't need this for spawning
return _workprot
[docs]def flatten_prototype(prototype, validate=False, no_db=False):
"""
Produce a 'flattened' prototype, where all prototype parents in the inheritance tree have been
merged into a final prototype.
Args:
prototype (dict): Prototype to flatten. Its `prototype_parent` field will be parsed.
validate (bool, optional): Validate for valid keys etc.
no_db (bool, optional): Don't search db-based prototypes. This can speed up
searching dramatically since module-based prototypes are static.
Returns:
flattened (dict): The final, flattened prototype.
"""
if prototype:
prototype = protlib.homogenize_prototype(prototype)
protlib.validate_prototype(prototype, is_prototype_base=validate, strict=validate)
return _get_prototype(
prototype, uninherited={"prototype_key": prototype.get("prototype_key")}
)
return {}
# obj-related prototype functions
[docs]def prototype_from_object(obj):
"""
Guess a minimal prototype from an existing object.
Args:
obj (Object): An object to analyze.
Returns:
prototype (dict): A prototype estimating the current state of the object.
"""
# first, check if this object already has a prototype
prot = obj.tags.get(category=PROTOTYPE_TAG_CATEGORY, return_list=True)
if prot:
prot = protlib.search_prototype(prot[0])
if not prot or len(prot) > 1:
# no unambiguous prototype found - build new prototype
prot = {}
prot["prototype_key"] = "From-Object-{}-{}".format(
obj.key, hashlib.md5(bytes(str(time.time()), "utf-8")).hexdigest()[:7]
)
prot["prototype_desc"] = "Built from {}".format(str(obj))
prot["prototype_locks"] = "spawn:all();edit:all()"
prot["prototype_tags"] = []
else:
prot = prot[0]
prot["key"] = obj.db_key or hashlib.md5(bytes(str(time.time()), "utf-8")).hexdigest()[:6]
prot["typeclass"] = obj.db_typeclass_path
location = obj.db_location
if location:
prot["location"] = location.dbref
home = obj.db_home
if home:
prot["home"] = home.dbref
destination = obj.db_destination
if destination:
prot["destination"] = destination.dbref
locks = obj.locks.all()
if locks:
prot["locks"] = ";".join(locks)
perms = obj.permissions.get(return_list=True)
if perms:
prot["permissions"] = make_iter(perms)
aliases = obj.aliases.get(return_list=True)
if aliases:
prot["aliases"] = aliases
tags = sorted(
[(tag.db_key, tag.db_category, tag.db_data) for tag in obj.tags.all(return_objs=True)],
key=lambda tup: (str(tup[0]), tup[1] or "", tup[2] or ""),
)
if tags:
prot["tags"] = tags
attrs = sorted(
[
(attr.key, attr.value, attr.category, ";".join(attr.locks.all()))
for attr in obj.attributes.all()
],
key=lambda tup: (str(tup[0]), tup[1] or "", tup[2] or "", tup[3]),
)
if attrs:
prot["attrs"] = attrs
return prot
[docs]def prototype_diff(prototype1, prototype2, maxdepth=2, homogenize=False, implicit_keep=False):
"""
A 'detailed' diff specifies differences down to individual sub-sections
of the prototype, like individual attributes, permissions etc. It is used
by the menu to allow a user to customize what should be kept.
Args:
prototype1 (dict): Original prototype.
prototype2 (dict): Comparison prototype.
maxdepth (int, optional): The maximum depth into the diff we go before treating the elements
of iterables as individual entities to compare. This is important since a single
attr/tag (for example) are represented by a tuple.
homogenize (bool, optional): Auto-homogenize both prototypes for the best comparison.
This is most useful for displaying.
implicit_keep (bool, optional): If set, the resulting diff will assume KEEP unless the new
prototype explicitly change them. That is, if a key exists in `prototype1` and
not in `prototype2`, it will not be REMOVEd but set to KEEP instead. This is
particularly useful for auto-generated prototypes when updating objects.
Returns:
diff (dict): A structure detailing how to convert prototype1 to prototype2. All
nested structures are dicts with keys matching either the prototype's matching
key or the first element in the tuple describing the prototype value (so for
a tag tuple `(tagname, category)` the second-level key in the diff would be tagname).
The the bottom level of the diff consist of tuples `(old, new, instruction)`, where
instruction can be one of "REMOVE", "ADD", "UPDATE" or "KEEP".
"""
_unset = Unset()
def _recursive_diff(old, new, depth=0):
old_type = type(old)
new_type = type(new)
if old_type == new_type and not (old or new):
# both old and new are unset, like [] or None
return (None, None, "KEEP")
if old_type != new_type:
if old and not new:
if depth < maxdepth and old_type == dict:
return {key: (part, None, "REMOVE") for key, part in old.items()}
elif depth < maxdepth and is_iter(old):
return {
part[0] if is_iter(part) else part: (part, None, "REMOVE") for part in old
}
if isinstance(new, Unset) and implicit_keep:
# the new does not define any change, use implicit-keep
return (old, None, "KEEP")
return (old, new, "REMOVE")
elif not old and new:
if depth < maxdepth and new_type == dict:
return {key: (None, part, "ADD") for key, part in new.items()}
elif depth < maxdepth and is_iter(new):
return {part[0] if is_iter(part) else part: (None, part, "ADD") for part in new}
return (old, new, "ADD")
else:
# this condition should not occur in a standard diff
return (old, new, "UPDATE")
elif depth < maxdepth and new_type == dict:
all_keys = set(list(old.keys()) + list(new.keys()))
return {
key: _recursive_diff(old.get(key, _unset), new.get(key, _unset), depth=depth + 1)
for key in all_keys
}
elif depth < maxdepth and is_iter(new):
old_map = {part[0] if is_iter(part) else part: part for part in old}
new_map = {part[0] if is_iter(part) else part: part for part in new}
all_keys = set(list(old_map.keys()) + list(new_map.keys()))
return {
key: _recursive_diff(
old_map.get(key, _unset), new_map.get(key, _unset), depth=depth + 1
)
for key in all_keys
}
elif old != new:
return (old, new, "UPDATE")
else:
return (old, new, "KEEP")
prot1 = protlib.homogenize_prototype(prototype1) if homogenize else prototype1
prot2 = protlib.homogenize_prototype(prototype2) if homogenize else prototype2
diff = _recursive_diff(prot1, prot2)
return diff
[docs]def flatten_diff(diff):
"""
For spawning, a 'detailed' diff is not necessary, rather we just want instructions on how to
handle each root key.
Args:
diff (dict): Diff produced by `prototype_diff` and
possibly modified by the user. Note that also a pre-flattened diff will come out
unchanged by this function.
Returns:
flattened_diff (dict): A flat structure detailing how to operate on each
root component of the prototype.
Notes:
The flattened diff has the following possible instructions:
UPDATE, REPLACE, REMOVE
Many of the detailed diff's values can hold nested structures with their own
individual instructions. A detailed diff can have the following instructions:
REMOVE, ADD, UPDATE, KEEP
Here's how they are translated:
- All REMOVE -> REMOVE
- All ADD|UPDATE -> UPDATE
- All KEEP -> KEEP
- Mix KEEP, UPDATE, ADD -> UPDATE
- Mix REMOVE, KEEP, UPDATE, ADD -> REPLACE
"""
valid_instructions = ("KEEP", "REMOVE", "ADD", "UPDATE")
def _get_all_nested_diff_instructions(diffpart):
"Started for each root key, returns all instructions nested under it"
out = []
typ = type(diffpart)
if typ == tuple and len(diffpart) == 3 and diffpart[2] in valid_instructions:
out = [diffpart[2]]
elif typ == dict:
# all other are dicts
for val in diffpart.values():
out.extend(_get_all_nested_diff_instructions(val))
else:
raise RuntimeError(
_(
"Diff contains non-dicts that are not on the "
"form (old, new, action_to_take): {diffpart}"
).format(diffpart)
)
return out
flat_diff = {}
# flatten diff based on rules
for rootkey, diffpart in diff.items():
insts = _get_all_nested_diff_instructions(diffpart)
if all(inst == "KEEP" for inst in insts):
rootinst = "KEEP"
elif all(inst in ("ADD", "UPDATE") for inst in insts):
rootinst = "UPDATE"
elif all(inst == "REMOVE" for inst in insts):
rootinst = "REMOVE"
elif "REMOVE" in insts:
rootinst = "REPLACE"
else:
rootinst = "UPDATE"
flat_diff[rootkey] = rootinst
return flat_diff
[docs]def prototype_diff_from_object(prototype, obj, implicit_keep=True):
"""
Get a simple diff for a prototype compared to an object which may or may not already have a
prototype (or has one but changed locally). For more complex migratations a manual diff may be
needed.
Args:
prototype (dict): New prototype.
obj (Object): Object to compare prototype against.
Returns:
diff (dict): Mapping for every prototype key: {"keyname": "REMOVE|UPDATE|KEEP", ...}
obj_prototype (dict): The prototype calculated for the given object. The diff is how to
convert this prototype into the new prototype.
implicit_keep (bool, optional): This is usually what one wants for object updating. When
set, this means the prototype diff will assume KEEP on differences
between the object-generated prototype and that which is not explicitly set in the
new prototype. This means e.g. that even though the object has a location, and the
prototype does not specify the location, it will not be unset.
Notes:
The `diff` is on the following form:
{"key": (old, new, "KEEP|REPLACE|UPDATE|REMOVE"),
"attrs": {"attrkey": (old, new, "KEEP|REPLACE|UPDATE|REMOVE"),
"attrkey": (old, new, "KEEP|REPLACE|UPDATE|REMOVE"), ...},
"aliases": {"aliasname": (old, new, "KEEP...", ...},
... }
"""
obj_prototype = prototype_from_object(obj)
diff = prototype_diff(
obj_prototype, protlib.homogenize_prototype(prototype), implicit_keep=implicit_keep
)
return diff, obj_prototype
[docs]def batch_update_objects_with_prototype(
prototype, diff=None, objects=None, exact=False, caller=None, protfunc_raise_errors=True
):
"""
Update existing objects with the latest version of the prototype.
Args:
prototype (str or dict): Either the `prototype_key` to use or the
prototype dict itself.
diff (dict, optional): This a diff structure that describes how to update the protototype.
If not given this will be constructed from the first object found.
objects (list, optional): List of objects to update. If not given, query for these
objects using the prototype's `prototype_key`.
exact (bool, optional): By default (`False`), keys not explicitly in the prototype will
not be applied to the object, but will be retained as-is. This is usually what is
expected - for example, one usually do not want to remove the object's location even
if it's not set in the prototype. With `exact=True`, all un-specified properties of the
objects will be removed if they exist. This will lead to a more accurate 1:1 correlation
between the object and the prototype but is usually impractical.
caller (Object or Account, optional): This may be used by protfuncs to do permission checks.
protfunc_raise_errors (bool): Have protfuncs raise explicit errors if malformed/not found.
This is highly recommended.
Returns:
changed (int): The number of objects that had changes applied to them.
"""
prototype = protlib.homogenize_prototype(prototype)
if isinstance(prototype, str):
new_prototype = protlib.search_prototype(prototype)
if new_prototype:
new_prototype = new_prototype[0]
else:
new_prototype = prototype
prototype_key = new_prototype["prototype_key"]
if not objects:
objects = ObjectDB.objects.get_by_tag(prototype_key, category=PROTOTYPE_TAG_CATEGORY)
if not objects:
return 0
if not diff:
diff, _ = prototype_diff_from_object(new_prototype, objects[0])
# make sure the diff is flattened
diff = flatten_diff(diff)
changed = 0
for obj in objects:
do_save = False
old_prot_key = obj.tags.get(category=PROTOTYPE_TAG_CATEGORY, return_list=True)
old_prot_key = old_prot_key[0] if old_prot_key else None
try:
for key, directive in diff.items():
if key not in new_prototype and not exact:
# we don't update the object if the prototype does not actually
# contain the key (the diff will report REMOVE but we ignore it
# since exact=False)
continue
if directive in ("UPDATE", "REPLACE"):
if key in _PROTOTYPE_META_NAMES:
# prototype meta keys are not stored on-object
continue
val = new_prototype[key]
do_save = True
def _init(val, typ):
return init_spawn_value(
val,
typ,
caller=caller,
prototype=new_prototype,
protfunc_raise_errors=protfunc_raise_errors,
)
if key == "key":
obj.db_key = _init(val, str)
elif key == "typeclass":
obj.db_typeclass_path = _init(val, str)
elif key == "location":
obj.db_location = _init(val, value_to_obj)
elif key == "home":
obj.db_home = _init(val, value_to_obj)
elif key == "destination":
obj.db_destination = _init(val, value_to_obj)
elif key == "locks":
if directive == "REPLACE":
obj.locks.clear()
obj.locks.add(_init(val, str))
elif key == "permissions":
if directive == "REPLACE":
obj.permissions.clear()
obj.permissions.batch_add(*(_init(perm, str) for perm in val))
elif key == "aliases":
if directive == "REPLACE":
obj.aliases.clear()
obj.aliases.batch_add(*(_init(alias, str) for alias in val))
elif key == "tags":
if directive == "REPLACE":
obj.tags.clear()
obj.tags.batch_add(
*(
(_init(ttag, str), tcategory, tdata)
for ttag, tcategory, tdata in val
)
)
elif key == "attrs":
if directive == "REPLACE":
obj.attributes.clear()
obj.attributes.batch_add(
*(
(
_init(akey, str),
_init(aval, value_to_obj),
acategory,
alocks,
)
for akey, aval, acategory, alocks in val
)
)
elif key == "exec":
# we don't auto-rerun exec statements, it would be huge security risk!
pass
else:
obj.attributes.add(key, _init(val, value_to_obj))
elif directive == "REMOVE":
do_save = True
if key == "key":
obj.db_key = ""
elif key == "typeclass":
# fall back to default
obj.db_typeclass_path = settings.BASE_OBJECT_TYPECLASS
elif key == "location":
obj.db_location = None
elif key == "home":
obj.db_home = None
elif key == "destination":
obj.db_destination = None
elif key == "locks":
obj.locks.clear()
elif key == "permissions":
obj.permissions.clear()
elif key == "aliases":
obj.aliases.clear()
elif key == "tags":
obj.tags.clear()
elif key == "attrs":
obj.attributes.clear()
elif key == "exec":
# we don't auto-rerun exec statements, it would be huge security risk!
pass
else:
obj.attributes.remove(key)
except Exception:
logger.log_trace(f"Failed to apply prototype '{prototype_key}' to {obj}.")
finally:
# we must always make sure to re-add the prototype tag
obj.tags.clear(category=PROTOTYPE_TAG_CATEGORY)
obj.tags.add(prototype_key, category=PROTOTYPE_TAG_CATEGORY)
if do_save:
changed += 1
obj.save()
return changed
[docs]def batch_create_object(*objparams):
"""
This is a cut-down version of the create_object() function,
optimized for speed. It does NOT check and convert various input
so make sure the spawned Typeclass works before using this!
Args:
objsparams (tuple): Each paremter tuple will create one object instance using the parameters
within.
The parameters should be given in the following order:
- `create_kwargs` (dict): For use as new_obj = `ObjectDB(**create_kwargs)`.
- `permissions` (str): Permission string used with `new_obj.batch_add(permission)`.
- `lockstring` (str): Lockstring used with `new_obj.locks.add(lockstring)`.
- `aliases` (list): A list of alias strings for
adding with `new_object.aliases.batch_add(*aliases)`.
- `nattributes` (list): list of tuples `(key, value)` to be loop-added to
add with `new_obj.nattributes.add(*tuple)`.
- `attributes` (list): list of tuples `(key, value[,category[,lockstring]])` for
adding with `new_obj.attributes.batch_add(*attributes)`.
- `tags` (list): list of tuples `(key, category)` for adding
with `new_obj.tags.batch_add(*tags)`.
- `execs` (list): Code strings to execute together with the creation
of each object. They will be executed with `evennia` and `obj`
(the newly created object) available in the namespace. Execution
will happend after all other properties have been assigned and
is intended for calling custom handlers etc.
Returns:
objects (list): A list of created objects
Notes:
The `exec` list will execute arbitrary python code so don't allow this to be available to
unprivileged users!
"""
# bulk create all objects in one go
# unfortunately this doesn't work since bulk_create doesn't creates pks;
# the result would be duplicate objects at the next stage, so we comment
# it out for now:
# dbobjs = _ObjectDB.objects.bulk_create(dbobjs)
objs = []
for objparam in objparams:
obj = ObjectDB(**objparam[0])
# setup
obj._createdict = {
"permissions": make_iter(objparam[1]),
"locks": objparam[2],
"aliases": make_iter(objparam[3]),
"nattributes": objparam[4],
"attributes": objparam[5],
"tags": make_iter(objparam[6]),
}
# this triggers all hooks
obj.save()
# run eventual extra code
for code in objparam[7]:
if code:
exec(code, {}, {"evennia": evennia, "obj": obj})
objs.append(obj)
return objs
# Spawner mechanism
[docs]def spawn(*prototypes, caller=None, **kwargs):
"""
Spawn a number of prototyped objects.
Args:
prototypes (str or dict): Each argument should either be a
prototype_key (will be used to find the prototype) or a full prototype
dictionary. These will be batched-spawned as one object each.
Keyword Args:
caller (Object or Account, optional): This may be used by protfuncs to do access checks.
prototype_modules (str or list): A python-path to a prototype
module, or a list of such paths. These will be used to build
the global protparents dictionary accessible by the input
prototypes. If not given, it will instead look for modules
defined by settings.PROTOTYPE_MODULES.
prototype_parents (dict): A dictionary holding a custom
prototype-parent dictionary. Will overload same-named
prototypes from prototype_modules.
only_validate (bool): Only run validation of prototype/parents
(no object creation) and return the create-kwargs.
protfunc_raise_errors (bool): Raise explicit exceptions on a malformed/not-found
protfunc. Defaults to True.
Returns:
object (Object, dict or list): Spawned object(s). If `only_validate` is given, return
a list of the creation kwargs to build the object(s) without actually creating it.
"""
# search string (=prototype_key) from input
prototypes = [
protlib.search_prototype(prot, require_single=True)[0] if isinstance(prot, str) else prot
for prot in prototypes
]
if not kwargs.get("only_validate"):
# homogenization to be more lenient about prototype format when entering the prototype
# manually
prototypes = [protlib.homogenize_prototype(prot) for prot in prototypes]
# overload module's protparents with specifically given protparents
# we allow prototype_key to be the key of the protparent dict, to allow for module-level
# prototype imports. We need to insert prototype_key in this case
custom_protparents = {}
for key, protparent in kwargs.get("prototype_parents", {}).items():
key = str(key).lower()
protparent["prototype_key"] = str(protparent.get("prototype_key", key)).lower()
custom_protparents[key] = protlib.homogenize_prototype(protparent)
objsparams = []
for prototype in prototypes:
# run validation and homogenization of provided prototypes
protlib.validate_prototype(
prototype, None, protparents=custom_protparents, is_prototype_base=True
)
prot = _get_prototype(
prototype,
protparents=custom_protparents,
uninherited={"prototype_key": prototype.get("prototype_key")},
)
if not prot:
continue
# extract the keyword args we need to create the object itself. If we get a callable,
# call that to get the value (don't catch errors)
create_kwargs = {}
init_spawn_kwargs = dict(
caller=caller,
prototype=prototype,
protfunc_raise_errors=kwargs.get("protfunc_raise_errors", True),
)
# we must always add a key, so if not given we use a shortened md5 hash. There is a (small)
# chance this is not unique but it should usually not be a problem.
val = prot.pop(
"key",
"Spawned-{}".format(hashlib.md5(bytes(str(time.time()), "utf-8")).hexdigest()[:6]),
)
create_kwargs["db_key"] = init_spawn_value(val, str, **init_spawn_kwargs)
val = prot.pop("location", None)
create_kwargs["db_location"] = init_spawn_value(val, value_to_obj, **init_spawn_kwargs)
val = prot.pop("home", None)
if val:
create_kwargs["db_home"] = init_spawn_value(val, value_to_obj, **init_spawn_kwargs)
else:
try:
create_kwargs["db_home"] = init_spawn_value(
settings.DEFAULT_HOME, value_to_obj, **init_spawn_kwargs
)
except ObjectDB.DoesNotExist:
# settings.DEFAULT_HOME not existing is common for unittests
pass
val = prot.pop("destination", None)
create_kwargs["db_destination"] = init_spawn_value(val, value_to_obj, **init_spawn_kwargs)
# we need the 'true' path to the typeclass (not its alias), so we make sure to load the typeclass
# and use its path directly
val = prot.pop("typeclass", settings.BASE_OBJECT_TYPECLASS)
typeclass = class_from_module(
init_spawn_value(val, str, **init_spawn_kwargs), settings.TYPECLASS_PATHS
)
create_kwargs["db_typeclass_path"] = f"{typeclass.__module__}.{typeclass.__name__}"
# extract calls to handlers
val = prot.pop("permissions", [])
permission_string = init_spawn_value(val, make_iter, **init_spawn_kwargs)
val = prot.pop("locks", "")
lock_string = init_spawn_value(val, str, **init_spawn_kwargs)
val = prot.pop("aliases", [])
alias_string = init_spawn_value(val, make_iter, **init_spawn_kwargs)
val = prot.pop("tags", [])
tags = []
for tag, category, *data in val:
tags.append(
(
init_spawn_value(tag, str, **init_spawn_kwargs),
category,
data[0] if data else None,
)
)
prototype_key = prototype.get("prototype_key", None)
if prototype_key:
# we make sure to add a tag identifying which prototype created this object
tags.append((prototype_key, PROTOTYPE_TAG_CATEGORY))
val = prot.pop("exec", "")
execs = init_spawn_value(val, make_iter, **init_spawn_kwargs)
# extract ndb assignments
nattributes = dict(
(
key.split("_", 1)[1],
init_spawn_value(val, value_to_obj, **init_spawn_kwargs),
)
for key, val in prot.items()
if key.startswith("ndb_")
)
# the rest are attribute tuples (attrname, value, category, locks)
val = make_iter(prot.pop("attrs", []))
attributes = []
for attrname, value, *rest in val:
attributes.append(
(
attrname,
init_spawn_value(value, **init_spawn_kwargs),
rest[0] if rest else None,
rest[1] if len(rest) > 1 else None,
)
)
simple_attributes = []
for key, value in (
(key, value) for key, value in prot.items() if not (key.startswith("ndb_"))
):
# we don't support categories, nor locks for simple attributes
if key in _PROTOTYPE_META_NAMES:
continue
else:
simple_attributes.append(
(
key,
init_spawn_value(value, value_to_obj_or_any, **init_spawn_kwargs),
None,
None,
)
)
attributes = attributes + simple_attributes
attributes = [tup for tup in attributes if not tup[0] in _NON_CREATE_KWARGS]
# pack for call into _batch_create_object
objsparams.append(
(
create_kwargs,
permission_string,
lock_string,
alias_string,
nattributes,
attributes,
tags,
execs,
)
)
if kwargs.get("only_validate"):
return objsparams
return batch_create_object(*objsparams)
