Dependency injection the python way, the good way. Not a port of Guice or Spring.
Key features
- Fast.
- Thread-safe.
- Simple to use.
- Does not steal class constructors.
- Does not try to manage your application object graph.
- Transparently integrates into tests.
- Supports Python 2.7 and Python 3.3+.
- Supports type hinting in Python 3.5+.
- Autoparams leveraging type annotations.
Installation
Use pip to install the lastest version:
Autoparams example
@inject.autoparams returns a decorator which automatically injects arguments into a function
that uses type annotations. This is supported only in Python >= 3.5.
@inject.autoparams() def refresh_cache(cache: RedisCache, db: DbInterface): pass
There is an option to specify which arguments we want to inject without attempts of injecting everything:
@inject.autoparams('cache', 'db') def sign_up(name, email, cache, db): pass
Step-by-step example
# Import the inject module. import inject # `inject.instance` requests dependencies from the injector. def foo(bar): cache = inject.instance(Cache) cache.save('bar', bar) # `inject.params` injects dependencies as keyword arguments or positional argument. # Also you can use @inject.autoparams in Python 3.5, see the example above. @inject.params(cache=Cache, user=CurrentUser) def baz(foo, cache=None, user=None): cache.save('foo', foo, user) # this can be called in different ways: # with injected arguments baz('foo') # with positional arguments baz('foo', my_cache) # with keyword arguments baz('foo', my_cache, user=current_user) # `inject.param` is deprecated, use `inject.params` instead. @inject.param('cache', Cache) def bar(foo, cache=None): cache.save('foo', foo) # `inject.attr` creates properties (descriptors) which request dependencies on access. class User(object): cache = inject.attr(Cache) def __init__(self, id): self.id = id def save(self): self.cache.save('users', self) @classmethod def load(cls, id): return cls.cache.load('users', id) # Create an optional configuration. def my_config(binder): binder.install(my_config2) # Add bindings from another config. binder.bind(Cache, RedisCache('localhost:1234')) # Configure a shared injector. inject.configure(my_config) # Instantiate User as a normal class. Its `cache` dependency is injected when accessed. user = User(10) user.save() # Call the functions, the dependencies are automatically injected. foo('Hello') bar('world')
Usage with Django
Django can load some modules multiple times which can lead to
InjectorException: Injector is already configured. You can use configure_once which
is guaranteed to run only once when the injector is absent:
import inject inject.configure_once(my_config)
Testing
In tests use inject.clear_and_configure(callable) to create a new injector on setup,
and optionally inject.clear() to clean up on tear down:
class MyTest(unittest.TestCase): def setUp(self): inject.clear_and_configure(lambda binder: binder .bind(Cache, Mock() \ .bind(Validator, TestValidator()) def tearDown(self): inject.clear()
Thread-safety
After configuration the injector is thread-safe and can be safely reused by multiple threads.
Binding types
Instance bindings always return the same instance:
redis = RedisCache(address='localhost:1234') def config(binder): binder.bind(Cache, redis)
Constructor bindings create a singleton on injection:
def config(binder): # Creates a redis cache singleton on first injection. binder.bind_to_constructor(Cache, lambda: RedisCache(address='localhost:1234'))
Provider bindings call the provider on injection:
def get_my_thread_local_cache(): pass def config(binder): # Executes the provider on each injection. binder.bind_to_provider(Cache, get_my_thread_local_cache)
Runtime bindings automatically create singletons on injection, require no configuration.
For example, only the Config class binding is present, other bindings are runtime:
class Config(object): pass class Cache(object): config = inject.attr(Config) class Db(object): config = inject.attr(Config) class User(object): cache = inject.attr(Cache) db = inject.attr(Db) @classmethod def load(cls, user_id): return cls.cache.load('users', user_id) or cls.db.load('users', user_id) inject.configure(lambda binder: binder.bind(Config, load_config_file())) user = User.load(10)
Disabling runtime binding
Sometimes runtime binding leads to unexpected behaviour. Say if you forget
to bind an instance to a class, inject will try to implicitly instantiate it.
If an instance is unintentionally created with default arguments it may lead to
hard-to-debug bugs. To disable runtime binding and make sure that only
explicitly bound instances are injected, pass bind_in_runtime=False
to inject.configure, inject.configure_once or inject.clear_and_configure.
In this case inject immediately raises InjectorException when the code
tries to get an unbound instance.
Keys
It is possible to use any hashable object as a binding key. For example:
import inject inject.configure(lambda binder: \ binder.bind('host', 'localhost') \ binder.bind('port', 1234))
Why no scopes?
I've used Guice and Spring in Java for a lot of years, and I don't like their scopes.
python-inject by default creates objects as singletons. It does not need a prototype scope
as in Spring or NO_SCOPE as in Guice because python-inject does not steal your class
constructors. Create instances the way you like and then inject dependencies into them.
Other scopes such as a request scope or a session scope are fragile, introduce high coupling,
and are difficult to test. In python-inject write custom providers which can be thread-local,
request-local, etc.
For example, a thread-local current user provider:
import inject import threading # Given a user class. class User(object): pass # Create a thread-local current user storage. _LOCAL = threading.local() def get_current_user(): return getattr(_LOCAL, 'user', None) def set_current_user(user): _LOCAL.user = user # Bind User to a custom provider. inject.configure(lambda binder: binder.bind_to_provider(User, get_current_user)) # Inject the current user. @inject.params(user=User) def foo(user): pass
Links
License
Apache License 2.0
Contributers
- Ivan Korobkov @ivankorobkov
- Jaime Wyant @jaimewyant
- Sebastian BuczyĆski @Enforcer
- Oleksandr Fedorov @Fedorof