jeni lets developers build applications and not e.g. web applications.

1. Configure each dependency in the project (requirements.txt, config, ...).
2. Write code with natural call signatures taking those dependencies as input.
3. Implement a Provider for each dependency, register with an Injector.

jeni runs on Python 2.7, Python 3.3 through 3.5, and pypy.

Write code as its meant to be written, without pegging function call signatures to some monolithic object that only applies to a specific runtime. This is about more than just testing. This is about composition.

jeni's design principle is to have all annotated callables usable in a context that knows nothing about jeni. Any callable is as relevant to a fresh Python REPL as it is to an injector.

Annotations are implemented as decorators for Python2. In Python 3, either decorators or function annotations can be used for injection.

Annotate a callable with a decorator to provide data for Injectors.

Intended use:

from jeni import annotate

@annotate('foo', 'bar')
def function(foo, bar):
    return

An Injector would then need to register providers for 'foo' and 'bar' in order to apply this function; an injector with such providers can apply the annotated function without any further information:

injector.apply(function)

To get a partially applied function, to call later:

fn = injector.partial(function)
fn()

Annotation does not alter the callable's default behavior. Call it normally:

foo, bar = 'foo', 'bar'
function(foo, bar)

On Python 2, use decorators to annotate. On Python 3, use either decorators or function annotations:

from jeni import annotate

@annotate
def function(foo: 'foo', bar: 'bar'):
    return

Note that when using Python function annotations, all injected values are provided as keyword arguments.

Since function annotations could be interpreted differently by different packages, injectors do not use function.__annotations__ directly. Functions opt in by a simple @annotate decoration. Functions with Python annotations which have not been decorated are assumed to not be decorated for injection.

(For this reason, annotating a callable with a single note where the note is a callable is not supported.)

Notes which are provided to annotate (above 'foo' and 'bar') can be any hashable object (i.e. object able to be used as a key in a dict) and is not limited to strings. If tuples are used as notes, they must be of length 2, and ('maybe', ...) and ('partial', ...) are reserved.

Provide a single prepared dependency.

Implement in subclass.

Annotations in the form of 'object:name' will pass the name value to the get method of the registered Provider (in this case, the provider registered with the Injector to provide object). This get-by-name pattern is useful for providers which have a dependency which supports lookups by key (e.g. HTTP headers or records in a key-value store).

By default, does nothing. Close objects as needed in subclass.

Provider close methods should not intentionally raise errors. Specifically, if a dependency has transactions, the transaction should be committed or rolled back before close is called, and not left as an operation to be called during the close phase.

Provider close methods must not take an argument; an injector cannot apply provided values on a close method since some providers may have already been closed. If an injected value is needed for the close method, annotate __init__ and access the value via self.

Collects dependencies and reads annotations to inject them.

A subclass could take arguments, but should pass keywords to super.

An Injector subclass inherits the provider registry of its base classes, but can override any provider by re-registering notes. When organizing a project, create an Injector subclass to serve as the object to register all providers. This allows for the project to have its own namespace of registered dependencies. This registry can be customized by further subclasses, either for injecting mocks in testing or providing alternative dependencies in a different runtime:

from jeni import Injector as BaseInjector

class Injector(BaseInjector):
    "Subclass provides namespace when registering providers."

Injector instances may be used as a context manager:

with Injector() as injector:
    injector.apply(annotated_fn)

The injector lifecycle can also be managed asynchronously using the enter() and exit() methods:

injector = Injector().enter()
injector.apply(annotated_fn)
...
injector.exit()

The injector provides itself as the 'injector' service:

with Injector() as injector:
    injector.get('injector')

Create and instantiate a sub-injector.

Mixins and local value dicts can be passed in as arguments. Local values can also be passed in as keyword arguments.

Register a provider, either a Provider class or a generator.

Provider class:

from jeni import Injector as BaseInjector
from jeni import Provider

class Injector(BaseInjector):
    pass

@Injector.provider('hello')
class HelloProvider(Provider):
    def get(self, name=None):
        if name is None:
            name = 'world'
        return 'Hello, {}!'.format(name)

Simple generator:

@Injector.provider('answer')
def answer():
    yield 42

If a generator supports get with a name argument:

@Injector.provider('spam', name=True)
def spam():
    count_str = yield 'spam'
    while True:
        count_str = yield 'spam' * int(count_str)

Registration can be a decorator or a direct method call:

Injector.provider('hello', HelloProvider)

Register a function as a provider.

Function (name support is optional):

from jeni import Injector as BaseInjector
from jeni import Provider

class Injector(BaseInjector):
    pass

@Injector.factory('echo')
def echo(name=None):
    return name

Registration can be a decorator or a direct method call:

Injector.factory('echo', echo)

Register a single value to be provided.

Supports base notes only, does not support get-by-name notes.

Fully apply annotated callable, returning callable's result.

Return function with closure to lazily inject annotated callable.

Repeat calls to the resulting function will reuse injections from the first call.

Positional arguments are provided in this order:

1. positional arguments provided by injector
2. positional arguments provided in partial_fn = partial(fn, *args)
3. positional arguments provided in partial_fn(*args)

Keyword arguments are resolved in this order (later override earlier):

1. keyword arguments provided by injector
2. keyword arguments provided in partial_fn = partial(fn, **kwargs)
3. keyword arguments provided in partial_fn(**kargs)

Note that Python function annotations (in Python 3) are injected as keyword arguments, as documented in annotate, which affects the argument order here.

annotate.partial accepts arguments in same manner as this partial.

Partially apply annotated callable, returning a partial function.

By default, partial is lazy so that injections only happen when they are needed. Use eager_partial in place of partial when a guarantee of injection is needed at the time the partially applied function is created.

eager_partial resolves arguments similarly to partial but relies on functools.partial for argument resolution when calling the final partial function.

Like apply, but applies if callable is not annotated.

Like partial, but applies if callable is not annotated.

Like eager_partial, but applies if callable is not annotated.

Resolve a single note into an object.

Close injector & injected Provider instances, including generators.

Providers are closed in the reverse order in which they were opened, and each provider is only closed once. Providers are closed if accessed by the injector, even if a dependency is not successfully provided. As such, providers should determine whether or not anything needs to be done in the close method.

Enter context-manager without with-block. See also: exit.

Useful for before- and after-hooks which cannot use a with-block.

Exit context-manager without with-block. See also: enter.

Like functools.wraps, with support for annotations.

Wrap a keyword note to record that its resolution is optional.

Normally all annotations require fulfilled dependencies, but if a keyword argument is annotated as maybe, then on apply, an injector does not attempt to pass dependencies which are unset or not provided:

from jeni import annotate

@annotate('foo', bar=annotate.maybe('bar'))
def foobar(foo, bar=None):
    return

Wrap a note for injection of a partially applied function.

This allows for annotated functions to be injected for composition:

from jeni import annotate

@annotate('foo', bar=annotate.maybe('bar'))
def foobar(foo, bar=None):
    return

@annotate('foo', annotate.partial(foobar))
def bazquux(foo, fn):
    # fn: injector.partial(foobar)
    return

Keyword arguments are treated as maybe when using partial, in order to allow partial application of only the notes which can be provided, where the caller could then apply arguments known to be unavailable in the injector. Note that with Python 3 function annotations, all annotations are injected as keyword arguments.

Injections on the partial function are lazy and not applied until the injected partial function is called. See eager_partial to inject eagerly.

Wrap a note for injection of an eagerly partially applied function.

Use this instead of partial when eager injection is needed in place of lazy injection.

Forwards getattr & getitem to enclosed injector.

If an injector has 'hello' registered:

from jeni import InjectorProxy
deps = InjectorProxy(injector)
deps.hello

Get by name can use dict-style access:

deps['hello:name']

Copyright 2013-2015 Ron DuPlain <[email protected]> (see AUTHORS file).

Released under the BSD License (see LICENSE file).