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Python dependency injection you can taste.
A lightweight dependency injection and result processing framework for Python using type hints. Emphasis is on simplicity, ease of use, and minimal impact on source code.
import in_n_out as ino
class Thing:
def __init__(self, name: str):
self.name = name
# use ino.inject to create a version of the function
# that will retrieve the required dependencies at call time
@ino.inject
def func(thing: Thing):
return thing.name
def give_me_a_thing() -> Thing:
return Thing("Thing")
# register a provider of Thing
ino.register_provider(give_me_a_thing)
print(func()) # prints "Thing"
def give_me_another_thing() -> Thing:
return Thing("Another Thing")
with ino.register_provider(give_me_another_thing, weight=10):
print(func()) # prints "Another Thing"
This also supports processing return values as well (injection of intentional side effects):
@ino.inject_processors
def func2(thing: Thing) -> str:
return thing.name
def greet_name(name: str):
print(f"Hello, {name}!")
ino.register_processor(greet_name)
func2(Thing('Bob')) # prints "Hello, Bob!"
Lots of other python DI frameworks exist, here are a few alternatives to consider:
FAQs
plugable dependency injection and result processing
We found that in-n-out demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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