Package for simplify data structures migrations
Project description
This is support package for simplify data serialization and persistance data between sessions and versions.
Basic usage
If You only need to serialize data, then you could use only JSON hooks
import json
from pydantic import BaseModel
from nme import NMEEncoder, nme_object_hook
class SampleModel(BaseModel):
field1: int
field2: str
data = SampleModel(field1=4, field2="abc")
with open("sample.json", "w") as f_p:
json.dump(data, f_p, cls=NMEEncoder)
with open("sample.json") as f_p:
data2 = json.load(f_p, object_hook=nme_object_hook)
assert data == data2
Migrations
The main idea of this package is simplify data migration between versions, and allow to define migration information next to data structure definition.
To register this information there is register_class decorator. It has 4 parameters:
version - version of data structure
migration_list - list of tuple (version. migration_function).
old_paths - list of fully qualified python paths to previous class definitions. This is to allow move class during code refactoring.
use_parent_migrations - if True, then parent class migrations will be used.
Lets imagine that we have such code
from nme import NMEEncoder, nme_object_hook
class SampleModel(BaseModel):
field1: int
field_ca_1: str
field_ca_2: float
with open("sample.json", "w") as f_p:
json.dump(data, f_p, cls=NMEEncoder)
But there is decision to mov both ca field to sub structure:
class CaModel(BaseModel)
field_1: str
field_2: float
class SampleModel(BaseModel):
field1: int
field_ca: CaModel
Then with nme code may look:
from nme import nme_object_hook, register_class
class CaModel(BaseModel)
field_1: str
field_2: float
def ca_migration_function(dkt):
dkt["field_ca"] = CaModel(field1=dkt.pop("field_ca_1"),
field2=dkt.pop("field_ca_2"))
return dkt
@register_class("0.0.1", [("0.0.1", ca_migration_function)])
class SampleModel(BaseModel):
field1: int
field_ca: CaModel
with open("sample.json") as f_p:
data = json.load(f_p, object_hook=nme_object_hook)
CBOR support
Also cbor2 encoder (nme_object_encoder) and object hook (nme_cbor_decoder) are available.
import cbor2
from pydantic import BaseModel
from nme import nme_cbor_encoder, nme_cbor_decoder
class SampleModel(BaseModel):
field1: int
field2: str
data = SampleModel(field1=4, field2="abc")
with open("sample.cbor", "wb") as f_p:
cbor2.dump(data, f_p, default=nme_cbor_encoder)
with open("sample.cbor", "rb") as f_p:
data2 = cbor2.load(f_p, object_hook=nme_cbor_decoder)
assert data == data2
Additional functions
rename_key(from_key: str, to_key: str, optional=False) -> Callable[[Dict], Dict] - helper function for rename field migrations.
update_argument(argument_name:str)(func: Callable) -> Callable - decorator to keep backward compatibility by converting dict argument to some class base on function type annotation
Additional notes
This package is extracted from PartSeg project for simplify reuse it in another projects.
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