Boilerplate Generator for Classes
Project description
PrefabClasses - Python Class Boilerplate Generator
Writes the class boilerplate code so you don't have to. Yet another variation on attrs/dataclasses.
Unlike dataclasses
or attrs
, prefab_classes
has a
focus on performance and startup time in particular.
This includes trying to minimise the impact of importing
the module itself.
Classes are written lazily when you first access the methods or eagerly when the module is compiled into a .pyc or rewritten out to a new .py source file.
The dynamic method of evaluating lazily is more flexible, while the compiled method is faster (once the .pyc file has been generated).
For more detail look at the documentation.
Usage
Define the class using plain assignment and attribute
function calls:
from prefab_classes import prefab, attribute
@prefab
class Settings:
hostname = attribute(default="localhost")
template_folder = attribute(default='base/path')
template_name = attribute(default='index')
Or with type hinting:
from prefab_classes import prefab
@prefab
class Settings:
hostname: str = "localhost"
template_folder: str = 'base/path'
template_name: str = 'index'
In either case the result behaves the same.
>>> from prefab_classes.funcs import to_json
>>> s = Settings()
>>> print(s)
Settings(hostname='localhost', template_folder='base/path', template_name='index')
>>> to_json(s)
'{"hostname": "localhost", "template_folder": "base/path", "template_name": "index"}'
For further details see the usage
pages in the documentation.
Why not just use attrs/dataclasses?
If attrs or dataclasses solves your problem then you should use them. They are thoroughly tested, well supported packages. This is a new project and has not had the rigorous real world testing of either of those.
Dataclasses/attrs/pydantic all impose some overhead on startup time. Prefab classes aims to minimise startup time and performance impact of class generation and in doing so sacrifices some features or nice internals of these other implementations.
Import time example:
Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
---|---|---|---|---|
python -c "pass" |
26.6 ± 1.2 | 25.0 | 30.6 | 1.00 |
python -c "import prefab_classes" |
28.4 ± 0.4 | 27.6 | 29.5 | 1.07 ± 0.05 |
python -c "import dataclasses" |
48.4 ± 1.0 | 46.5 | 51.5 | 1.82 ± 0.09 |
python -c "import attrs" |
67.3 ± 0.7 | 65.9 | 71.1 | 2.53 ± 0.11 |
python -c "import pydantic" |
105.4 ± 3.4 | 100.3 | 115.7 | 3.96 ± 0.22 |
For more detailed tests you can look at the performance section of the docs.
How does it work
The @prefab
decorator either rewrites the class dynamically, putting methods
in place that will be generated as they are first accessed OR it acts
as a marker to indicate the class should be transformed for the compiled
classes.
Compiled classes can both be imported directly or converted back to new .py files. Direct import will perform the conversion before creating the .pyc file.
example.py
# COMPILE_PREFABS
from prefab_classes import prefab, attribute
from pathlib import Path
@prefab(compile_prefab=True)
class SettingsPath:
hostname = attribute(default="localhost")
template_folder = attribute(default='base/path')
template_name = attribute(default='index')
file_types = attribute(default_factory=list)
def __prefab_post_init__(self, template_folder, file_types):
self.template_folder = Path(template_folder)
file_types.extend(['.md', '.html'])
self.file_types = file_types
Direct import using prefab_compiler
from prefab_classes import prefab_compiler
with prefab_compiler():
from example import SettingsPath
# Use normally from here
Compile to a new .py file using rewrite_to_py:
>>> from prefab_classes.compiled import rewrite_to_py
>>> rewrite_to_py('example.py', 'example_compiled.py', use_black=True)
Using black to format for ease of reading.
example_compiled.py
# DO NOT MANUALLY EDIT THIS FILE
# MODULE: example_compiled.py
# GENERATED FROM: example.py
# USING prefab_classes VERSION: v0.9.1
from pathlib import Path
class SettingsPath:
COMPILED = True
PREFAB_FIELDS = ["hostname", "template_folder", "template_name", "file_types"]
__match_args__ = ("hostname", "template_folder", "template_name", "file_types")
def __init__(
self,
hostname="localhost",
template_folder="base/path",
template_name="index",
file_types=None,
):
self.hostname = hostname
self.template_name = template_name
file_types = file_types if file_types is not None else list()
self.__prefab_post_init__(
template_folder=template_folder, file_types=file_types
)
def __repr__(self):
return f"{type(self).__qualname__}(hostname={self.hostname!r}, template_folder={self.template_folder!r}, template_name={self.template_name!r}, file_types={self.file_types!r})"
def __eq__(self, other):
return (
(self.hostname, self.template_folder, self.template_name, self.file_types)
== (
other.hostname,
other.template_folder,
other.template_name,
other.file_types,
)
if self.__class__ == other.__class__
else NotImplemented
)
def __prefab_post_init__(self, template_folder, file_types):
self.template_folder = Path(template_folder)
file_types.extend([".md", ".html"])
self.file_types = file_types
If compile_plain=True
is provided as an argument to @prefab
the COMPILED
and PREFAB_FIELD
variables will not be set on the class.
Credit
autogen
function and some magic method definitions taken from
David Beazley's Cluegen
General design based on previous experience using dataclasses and attrs and trying to match the requirements for PEP 681.
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