GitLocker: The Coding Marketplace

Description:

innout 0.2.1

in-n-out

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!"

Alternatives
Lots of other python DI frameworks exist, here are a few alternatives to consider:

https://github.com/ets-labs/python-dependency-injector
https://github.com/google/pinject
https://github.com/ivankorobkov/python-inject
https://github.com/alecthomas/injector
https://github.com/Finistere/antidote
https://github.com/dry-python/returns
https://github.com/adriangb/di