A decorator for generating xsd, xml and parsers from dataclasses
Project description
XMLable
An easy xml/xsd generator and parser for python dataclasses!
@xmlify
@dataclass
class Config:
date: str
number_of_cores: int
codes: list[int]
show_logs: bool
write_xsd(THIS_DIR / "config.xsd", Config)
write_xml_template(THIS_DIR / "config_xml_template.xml", Config)
original = Config(
date="31/02/2023",
number_of_cores=48,
codes=[101, 345, 42, 67],
show_logs=False,
)
write_xml_value(THIS_DIR / "config_xml_example.xml", original)
read_config: Config = parse_file(Config, THIS_DIR / "config_xml_example.xml")
assert read_config == original
See more in examples
Capabilities
Types
Currently supports the types:
int, float, str, dict, tuple, set, list, None
# as well as unions!
int | float | None
And dataclasses that have been @xmlify
-ed.
These can be combined for types such as:
@xmlify
@dataclass
class Complex:
a: dict[tuple[int, str], list[tuple[dict[int, float | str], set[bool]]]]
c1 = Complex(
a={(3, "hello"): [({3: 0.4}, {True, False}), ({2: "str"}, {False})]}
)
Custom Classes
The xmlify interface can be implemented by adding methods described in xmlify
Once the class is_xmlified
it can be used just as if generated by @xmlify
from xmlable._xobject import XObject
from xmlable._user import IXmlify
from xmlable._manual import manual_xmlify
@manual_xmlify
class MyClass(IXmlify):
def get_xobject() -> XObject:
class XMyClass(XObject):
def xsd_out(self, name: str, attribs: dict[str, str] = {}, add_ns: dict[str, str] = {}) -> _Element:
pass
def xml_temp(self, name: str) -> _Element:
pass
def xml_out(self, name: str, val: Any, ctx: XErrorCtx) -> _Element:
pass
def xml_in(self, obj: ObjectifiedElement, ctx: XErrorCtx) -> Any:
pass
return XMyClass() # must be an instance of XMyClass, not the class
def xsd_forward(add_ns: dict[str, str]) -> _Element:
pass
def xsd_dependencies() -> set[type]:
return {MyClass}
See the user define example for implementation.
Limitations
Unions of Generic Types
Generating xsd works, parsing works, however generating an xml template can fail if they type is not determinable at runtime.
- Values do not have type arguments carried with them
- Many types are indistinguishable in python
For example:
@xmlify
@dataclass
class GenericUnion:
u: dict[int, float] | dict[int, str]
GenericUnion(u={}) # which variant in the xml should {} have??named_
In this case an error is raised
To Develop
git clone # this project
# Can use hatch to build, run
hatch run check:test # run tests/
hatch run check:lint # check formatting
hatch run check:typecheck # mypy for src/ and all examples
hatch run auto:examplegen # regenerate the example code
hatch run auto:lint # format code
# Alternatively can just create a normal env
python3.11 -m venv .venv
source .venv/bin/activate # activate virtual environment
pip install -e . # install this project in the venv
pip install -e .[dev] # install optional dev dependencies (mypy, black and pytest)
black . # to reformat
mypy # type check
pytest # to run tests
Hatch is used for build, test and pypi publish.
To Improve
Fuzzing
(As a fun weekend project) generate arbitrary python data types with values, and dataclasses.
Then @xmlify
all and validate as in the current tests
Etree vs Objectify
Currently using objectify for parsing and etree for construction, I want to move parsing to use etree
- previously used objectify for quick prototype.
Project details
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