| Name | dek JSON |
| Version |
1.4.2
JSON |
| download |
| home_page | https://github.com/rec/dek |
| Summary | 🎴 The decorator-decorator 🎴 |
| upload_time | 2024-01-25 11:37:10 |
| maintainer | |
| docs_url | None |
| author | Tom Ritchford |
| requires_python | >=3.8 |
| license | MIT |
| keywords |
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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🗃 `dek` - the decorator-decorator 🗃
`dek` decorates your decorators to diminish defects and drudgery.
Writing a Python decorator which takes no parameters isn't hard.
But writing a decorator with parameters is less easy - and more work
if you want to decorate classes, like `unittest.mock.patch` does.
`dek` is a decorator for decorators that does this deftly with a
single tiny function.
## Example 1: a simple decorator with dek
TASK: write a decorator `before` that prints a function's name and its
arguments before it executes.
With `dek`, it's a few lines:
import dek
@dek
def before(pfunc):
print(pfunc)
return pfunc()
Done! To use your new decorator:
@before
def phone(two, four=4):
print('Calling', two + two, four * four)
one(32, four=3)
# That prints something like:
#
# functools.partial(<function phone at 0x7fafa8072b00>, 32, four=3)
# Calling 64 9
`pfunc` is a [`functools.partial`](
https://docs.python.org/3/library/functools.html#functools.partial),
which represents the function call that `dek` intercepted. Your code
can call `pfunc` as often as you like, or add or change parameters.
## Example 2: same, without `dek`
import functools
def before(func):
@functools.wraps(func)
def wrapped(*args, **kwargs):
print(func, args, kwargs)
return func(*args, **kwargs)
return wrapped
With `dek` it's a bit less work, but the real advantage comes when you have
a decorator with a parameter.
## Example 3: a decorator with a single optional parameter
Write a decorator `before` that prints a function's name, arguments
_and a label_ before it executes.
With `dek`, it's a trivial change from the previous solution.
import dek
@dek
def before(pfunc, label='dull'):
print(label, pfunc.func, *pfunc.args)
return pfunc()
@before
def add(x, y):
return x + y
@before(label='Exciting!')
def times(x, y):
return x * y
print('Result', add(2, times(2, 3)))
# Prints:
# Exciting! times 2 3
# dull add 2 6
# Result 8
## Example 4: same, without `dek`
Without `dek` it's actual work that's easy to get wrong.
import functools
def before(func=None, label='dull'):
if func is not None:
@functools.wraps(func)
def wrapped(*args, **kwargs):
print(label, func.__name, *args)
return func(*args, **kwargs)
return wrapped
return functools.partial(before, label=label)
## Example 5: Deferred mode
For finer control over function signatures there is deferred mode, which
lets you select what sort of signature you want to expose with a `wrapped`
function that you create.
@dek(defer=True)
def before(func, label='debug'):
def wrapped(foo, bar):
print(label, foo, bar)
return func(foo, bar)
return wrapped
## Example 6: Decorating a class
If you need to decorate methods on a class, there's a `methods` parameter to
select which methods get decorated.
import dek
@dek(methods='test')
def before(pfunc):
print('HERE', *pfunc.args)
return pfunc()
@before
class Class:
def test_one(self):
return 1
def test_two(self):
return 2
def three(self): # This won't get decorated
return 1
# Test at the command line:
>>> cl = Class()
>>> cl.test_one(), cl.test_two(), cl.three()
HERE 1
HERE 2
(1, 2, 3)
NOTES:
[This article](https://medium.com/p/1277a9ed34dc/) talks more about
decorators that take parameters and about `dek` in general.
For your advanced decorator desires, the PyPi module
[`decorator`](https://github.com/micheles/decorator/blob/master/docs/documentation.md) does not duplicate duties that `dek` does, but does
pretty anything else you could conceive of in a decorator library.
### [API Documentation](https://rec.github.io/dek#dek--api-documentation)
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