python-simple-di is a simple dependency injection container implementation. With its help you can create instances and its dependencies on runtime.
Contents
- Added LazyResolverMixin and created ReferenceResolverLazy, RelationResolverLazy, ModuleResolverLazy, AttributeResolverLazy and FactoryResolverLazy with it. The shortcuts for string configurations are *_lazy.
- Default resolver are no longer registered hardcoded. The become added with add_value_resolver classmethod.
- kwargs was added as additional configuration option now. Args and KWargs can be splitted in this options now. Using an empty string key for mixing arguments and keyword arguments is deprecated now and will be removed in 2.0.
- Loosely coupled inject and inject_many decorator. (WARNING: inject_many uses resolve_many that makes use of the unsorted items dict-method. So there is no guarantee that the first instance will be the first registered instance.)
- resolve also accepts a type as parameter name and will return the first instance subclassing that type (first result of resolve_many). (WARNING: resolve_many makes use of the unsorted items dict-method. So there is no guarantee that the first instance will be the first registered instance.)
- resolve many: the new methods resolve_many and resolve_many_lazy gives you the possibility to resolve multiple objects depending on their class.
- alias names: you can provide a list of alias names within the object configuration.
- constructor/factory (kw)argument overridies: resolve methods accepts args and kwargs that will be used instead of args configurations.
- register decorator:
register
can be used as decorator now. - use as contextmanager: the container can be used as a context manager to temporarily override settings in
with
block. - mixin support: new option
mixins
can contain a list or a type of types that will be used to create the new type.
- copy settings in DIContainer.__init__.
You can install it via pip:
pip install python-simple-di
or via easy_install:
easy_install -U python-simple-di
To configure the di.DIContainer
you need to pass a dict with the needed configuration in it. Alternatively you can use an instance of di.DIConfig
which is used internal anyway.
Define the object's name as key to access it at runtime. The value needs to be the configuration to create the instance.
- type (required): This option defines the type with its complete python dotted path or the python type instance. You can prepend a filesystem path that will dynamically be added to the
sys.path
if the instance is requested. Examples:
'type': 'path.to.my.Type'
'type': path.to.my.Type
# or
'type': '/add/to/sys/path:add.to.sys.path.Type'
- args (optional): The args can either be a
list
of values to pass as arguments or adict
to pass as keyword arguments. To mix both, you can define a dictionary with an empty string or None as key and a list as value. Examples:
'args': ['first', 3, 'third']
# or
'args': {'one': '1', 'two':'two'}
# or
'args': {'': [1, 'two'], 'three': 3}
- lazy (optional): This option defines whether the instance will be created on runtime or on container initialization. Example:
'lazy': False # default: True
- singleton (optional, default: True): If this option is set to
True
, the created instance will be saved inside the container. Next time the same instance will be returned. If this value is set toFalse
a new instance will be created every time. - properties (optional): This option is similar to the
args
option. After an instance was created a buildup is called. This buildup fills the given properties with the given values in this dictionary. Examples:
{
'type': 'some.Person',
'propeties': {
'first_name': 'John',
'last_name': 'Doe'
}
}
- assert_type (optional): Checks whether the created type has the given base_type.
'type': 'path.to.implemented.Type',
'assert_type': 'path.to.parent.Type'
- factory_method (optional): This option can be used to create an instance by a classmethod which creates the wanted instance. For example this can be used to create class based views in django at runtime. Example:
'type': 'myapp.views.ClassBasedView',
'factory_method': 'as_view'
- mixins (optional): This option allows you to mix the given types into the configured type to create new type.
With the help of the resolver the magic comes into play. Thanks to this small classes it is possible to trigger the dependencies of a type at runtime.
The following resolvers are included in the default package. Individual resolvers can be implemented by extending the base class di.Resolver
.
The ReferenceResolver offers the possibility to resolve an attribute within the python path to refer. This must be the path of the object as a python dotted path.
Example:
{
'args': {
'output_stream': ReferenceResolver('sys.stdout')
}
}
di also provides some shortcuts for this name:
di.ref('sys.stdout')
as shortcut for type.di.reference('sys.stdout')
as shortcut for the type.'ref:sys.stdout'
as prefix of the configured type to use the resolver lazily.
The RelationResolver allows the resolution of an object of this container at runtime.
Example:
{
'object_a': {
'type': 'some.ClassName'
},
'object_b': {
'type': 'some.other.ClassName',
'args': [
RelationResolver('object_a')
]
},
}
di also provides some shortcuts for this name:
di.rel('object_a')
as shortcut for type.di.relation('object_a')
as shortcut for the type.'rel:object_a'
as prefix of the configured type to use the resolver lazily.
Sometimes it may be necessary to pass an entire module as a parameter. For this purpose the ModuleResolver is available.
Example:
{
'type': 'some.ClassName',
'args': {
'serializer': ModuleResolver('json')
}
}
Di also provides some shortcuts for this name.
di.mod('json')
as shortcut for type.di.module('json')
as shortcut for the type.'mod:json'
as prefix of the configured type to lazy use the resolver.
With the help of FactoryResolver the return value of a function as an argument can be passed to the specified type.
Example.
{
'type': 'some.ClassName',
'args': [
FactoryResolver('path.to.the.factory_method')
]
}
Di also provides some shortcuts for this name.
di.fac('path.to.the.factory_method')
as shortcut for type.di.factory('path.to.the.factory_method')
as shortcut for the type.'factory:path.to.the.factory_method'
as prefix of the configured type to lazy use the resolver.
With the Resolver an attribute of an instance can be passed as an argument. This can be very useful if you are using the django web framework and want to pass a settings value as an argument fo an instance.
Example:
{
'type': 'some.ClassName':
'args': {
'debug': AttributeResolver('django.conf.settings.DEBUG')
}
}
Di also provides some shortcuts for this name.
di.attr('django.conf.settings.DEBUG')
as shortcut for type.di.attribute('django.conf.settings.DEBUG')
as shortcut for the type.'attr:django.conf.settings.DEBUG'
as prefix of the configured type to lazy use the resolver.
You can pass an EventDispatcher into the DiContainer. This Dispatcher will be called if anything interesting happens inside the Container. BaseType is di.DIEventDispatcher
.
Simply create a dictionary with your type configuration and pass it as settings argument to the DIContainer
. The Dictionarys key is the type key to resolve the instance.
# create the container
container = DIContainer(config)
# resolve the instance
instance = container.resolve('instance_key')
# resolve the instance type only
type_of_instance_key = container.resolve_type('instance_key')
Sometimes it may be necessary to create an instance at its first useage. So there are the following two messages, that returns a di.Proxy
instance at first.
To use this Feature you need to provide a proxy_type_name
and install the specific package for this. I recommend lazy-object-proxy
with its type Proxy
. Which is the default value for this argument. It is not shipped with this package because of the many different other implementations and thier different licence.
If you use this in combination with django you can use django.utils.functional.SimpleLazyObject
. But at this moment the ``resolve_type_lazy`` is not working properly with ``SimpleLazyObject``.
# create the container
container = DIContainer(config, proxy_type_name='lazy_object_proxy.Proxy')
# lazy resolves the instance
instance = container.resolve_lazy('instance_key')
# lazy resolves the instance type only
type_of_instance_key = container.resolve_type_lazy('instance_key')
If you need the same container but override some settings you can create a child container and pass the deviant settings into it.
This is the unittest that explains this function at its best.
container = DIContainer({
'one': {
'type': 'mock.Mock',
'properties': {
'source': 'parent'
}
},
'two': {
'type': 'mock.Mock',
'properties': {
'source': 'parent'
}
}
})
self.assertEqual(container.one.source, 'parent')
self.assertEqual(container.two.source, 'parent')
child_container = container.create_child_container({
'two': {
'type': 'mock.Mock',
'properties': {
'source': 'child'
}
}
})
self.assertEqual(child_container.one.source, 'parent')
self.assertEqual(child_container.two.source, 'child')
self.assertEqual(container.one.source, 'parent')
self.assertEqual(container.two.source, 'parent')
Some method of the di.DIContainer
can be used as decorator zu register or inject instances within your code.
The method register can be used as decorator for classes or factory methods. With this you do not need to provide the instances configuration at container creation.
Passing the settings is optional.
@container.register("my_service", dict(args={'init_arg': 'test'}))
class MyService(object):
def __init__(self, init_arg):
self.init_arg = init_arg
def get_data(self, args):
pass
The method inject
gives you the possibility to inject instances into a
method if a keyword argument was not provided. that makes the loosely coupeling
and testing very easy:
@container.inject(service='some_service')
def some_method(value, service):
service.do_work(value)
some_method("hello world")
some_method("hello world", ExplicitService())
The method inject_many
gives you the possibility to inject multiple instances depending on
their type.
@container.inject_many(hooks=SomeHookClass)
def method(data, hook_instances):
for hook in hook_instance:
hook.hook(data)
# ...