معرفی شرکت ها
andi-0.4.1
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
Library for annotation-based dependency injection
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | andi-0.4.1 |
| نام | andi |
| نسخه کتابخانه | 0.4.1 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Mikhail Korobov |
| ایمیل نویسنده | kmike84@gmail.com |
| آدرس صفحه اصلی | https://github.com/scrapinghub/andi |
| آدرس اینترنتی | https://pypi.org/project/andi/ |
| مجوز | - |
====
andi
====
.. image:: https://img.shields.io/pypi/v/andi.svg
:target: https://pypi.python.org/pypi/andi
:alt: PyPI Version
.. image:: https://img.shields.io/pypi/pyversions/andi.svg
:target: https://pypi.python.org/pypi/andi
:alt: Supported Python Versions
.. image:: https://travis-ci.com/scrapinghub/andi.svg?branch=master
:target: https://travis-ci.com/scrapinghub/andi
:alt: Build Status
.. image:: https://codecov.io/github/scrapinghub/andi/coverage.svg?branch=master
:target: https://codecov.io/gh/scrapinghub/andi
:alt: Coverage report
``andi`` makes easy implementing custom dependency injection mechanisms
where dependencies are expressed using type annotations.
``andi`` is useful as a building block for frameworks, or as a library
which helps to implement dependency injection (thus the name -
ANnotation-based Dependency Injection).
License is BSD 3-clause.
Installation
============
::
pip install andi
andi requires Python >= 3.5.3.
Goal
====
See the following classes that represents parts of a car
(and the car itself):
.. code-block:: python
class Valves:
pass
class Engine:
def __init__(self, valves):
self.valves = valves
class Wheels:
pass
class Car:
def __init__(self, engine, wheels):
self.engine = engine
self.wheels = wheels
The following would be the usual way of build a ``Car`` instance:
.. code-block:: python
valves = Valves()
engine = Engine(valves)
wheels = Wheels()
car = Car(engine, wheels)
There are some dependencies between the classes: A car requires
and engine and wheels to be built, as well as the engine requires
valves. These are the car dependencies and sub-dependencies.
The question is, could we have an automatic way of building instances?
For example, could we have a ``build`` function that
given the ``Car`` class or any other class would return an instance
even if the class itself has some other dependencies?
.. code-block:: python
car = build(Car) # Andi helps creating this generic build function
``andi`` inspect the dependency tree and creates a plan making easy creating
such a ``build`` function.
This is how this plan for the ``Car`` class would looks like:
1. Invoke ``Valves`` with empty arguments
2. Invoke ``Engine`` using the instance created in 1 as the argument ``valves``
3. Invoke ``Wheels`` with empty arguments
4. Invoke ``Cars`` with the instance created in 2 as the ``engine`` argument and with
the instance created in 3 as the ``wheels`` argument
Type annotations
----------------
But there is a missing piece in the Car example before. How can
``andi`` know that the class ``Valves`` is required to build the
argument ``valves``? A first idea would be to use the argument
name as a hint for the class name
(as `pinject <https://pypi.org/project/pinject/>`_ does),
but ``andi`` opts to rely on arguments' type annotations instead.
The classes for ``Car`` should then be rewritten as:
.. code-block:: python
class Valves:
pass
class Engine:
def __init__(self, valves: Valves):
self.valves = valves
class Wheels:
pass
class Car:
def __init__(self, engine: Engine, wheels: Wheels):
self.engine = engine
self.wheels = wheels
Note how now there is a explicit annotation stating that the
``valves`` argument is of type ``Valves``
(same for ``engine`` and ``wheels``).
The ``andi.plan`` function can now create a plan to build the
``Car`` class (ignore the ``is_injectable`` parameter by now):
.. code-block:: python
plan = andi.plan(Car, is_injectable={Engine, Wheels, Valves})
This is what the ``plan`` variable contains:
.. code-block:: python
[(Valves, {}),
(Engine, {'valves': Valves}),
(Wheels, {}),
(Car, {'engine': Engine,
'wheels': Wheels})]
Note how this plan correspond exactly to the 4-steps plan described
in the previous section.
Building from the plan
----------------------
Creating a generic function to build the instances from
a plan generated by ``andi`` is then very easy:
.. code-block:: python
def build(plan):
instances = {}
for fn_or_cls, kwargs_spec in plan:
instances[fn_or_cls] = fn_or_cls(**kwargs_spec.kwargs(instances))
return instances
So let's see putting all the pieces together. The following code
creates an instance of ``Car`` using ``andi``:
.. code-block:: python
plan = andi.plan(Car, is_injectable={Engine, Wheels, Valves})
instances = build(plan)
car = instances[Car]
is_injectable
-------------
It is not always desired for ``andi`` to manage every single annotation found.
Instead is usually better to explicitly declare which types
can be handled by ``andi``. The argument ``is_injectable``
allows to customize this feature.
``andi`` will raise an error on the presence of a dependency that cannot be resolved
because it is not injectable.
Usually is desirable to declare injectabilty by
creating a base class to inherit from. For example,
we could create a base class ``Injectable`` as base
class for the car components:
.. code-block:: python
class Injectable(ABC):
pass
class Valves(Injectable):
pass
class Engine(Injectable):
def __init__(self, valves: Valves):
self.valves = valves
class Wheels(Injectable):
pass
The call to ``andi.plan`` would then be:
.. code-block:: python
is_injectable = lambda cls: issubclass(cls, Injectable)
plan = andi.plan(Car, is_injectable=is_injectable)
Functions and methods
---------------------
Dependency injection is also very useful when applied to functions.
Imagine that you have a function ``drive`` that drives the ``Car``
through the ``Road``:
.. code-block:: python
class Road(Injectable):
...
def drive(car: Car, road: Road, speed):
... # Drive the car through the road
The dependencies has to be resolved before invoking
the ``drive`` function:
.. code-block:: python
plan = andi.plan(drive, is_injectable=is_injectable)
instances = build(plan.dependencies)
Now the ``drive`` function can be invoked:
.. code-block:: python
drive(instances[Car], instances[Road], 100)
Note that ``speed`` argument was not annotated. The resultant plan just won't include it
because the ``andi.plan`` ``full_final_kwargs`` parameter is ``False``
by default. Otherwise, an exception would have been raised (see ``full_final_kwargs`` argument
documentation for more information).
An alternative and more generic way to invoke the drive function
would be:
.. code-block:: python
drive(speed=100, **plan.final_kwargs(instances))
dataclasses and attrs
---------------------
``andi`` supports classes defined using `attrs <https://www.attrs.org/>`_
and also `dataclasses <https://docs.python.org/3/library/dataclasses.html>`_.
For example the ``Car`` class could have been defined as:
.. code-block:: python
# attrs class example
@attr.s(auto_attribs=True)
class Car:
engine: Engine
wheels: Wheels
# dataclass example
@dataclass
class Car(Injectable):
engine: Engine
wheels: Wheels
Using ``attrs`` or ``dataclass`` is handy because they avoid
some boilerplate.
Externally provided dependencies
--------------------------------
Retaining the control over object instantiation
could be desired in some cases. For example creating
a database connection could require accessing some
credentials registry or getting the connection from a pool
so you might want to control building
such instances outside of the regular
dependency injection mechanism.
``andi.plan`` allows to specify which types would be
externally provided. Let's see an example:
.. code-block:: python
class DBConnection(ABC):
@abstractmethod
def getConn():
pass
@dataclass
class UsersDAO:
conn: DBConnection
def getUsers():
return self.conn.query("SELECT * FROM USERS")
``UsersDAO`` requires a database connection to run queries.
But the connection will be provided externally from a pool, so we
call then ``andi.plan`` using also the ``externally_provided``
parameter:
.. code-block:: python
plan = andi.plan(UsersDAO, is_injectable=is_injectable,
externally_provided={DBConnection})
The build method should then be modified slightly to be able
to inject externally provided instances:
.. code-block:: python
def build(plan, instances_stock=None):
instances_stock = instances_stock or {}
instances = {}
for fn_or_cls, kwargs_spec in plan:
if fn_or_cls in instances_stock:
instances[fn_or_cls] = instances_stock[fn_or_cls]
else:
instances[fn_or_cls] = fn_or_cls(**kwargs_spec.kwargs(instances))
return instances
Now we are ready to create ``UserDAO`` instances with ``andi``:
.. code-block:: python
plan = andi.plan(UsersDAO, is_injectable=is_injectable,
externally_provided={DBConnection})
dbconnection = DBPool.get_connection()
instances = build(plan.dependencies, {DBConnection: dbconnection})
users_dao = instances[UsersDAO]
users = user_dao.getUsers()
Note that being injectable is not required for externally provided
dependencies.
Optional
--------
``Optional`` type annotations can be used in case of
dependencies that can be optional. For example:
.. code-block:: python
@dataclass
class Dashboard:
conn: Optional[DBConnection]
def showPage():
if self.conn:
self.conn.query("INSERT INTO VISITS ...")
... # renders a HTML page
In this example, the ``Dashboard`` class generates a HTML page to be served, and
also stores the number of visits into a database. Database
could be absent in some environments, but you might want
the dashboard to work even if it cannot log the visits.
When a database connection is possible the plan call would be:
.. code-block:: python
plan = andi.plan(UsersDAO, is_injectable=is_injectable,
externally_provided={DBConnection})
And the following when the connection is absent:
.. code-block:: python
plan = andi.plan(UsersDAO, is_injectable=is_injectable,
externally_provided={})
It is also required to register the type of ``None``
as injectable. Otherwise ``andi.plan`` with raise an exception
saying that "NoneType is not injectable".
.. code-block:: python
Injectable.register(type(None))
Union
-----
``Union`` can also be used to express alternatives. For example:
.. code-block:: python
@dataclass
class UsersDAO:
conn: Union[ProductionDBConnection, DevelopmentDBConnection]
``DevelopmentDBConnection`` will be injected in the absence of
``ProductionDBConnection``.
Full final kwargs mode
-------------------------
By default ``andi.plan`` won't fail if it is not able to provide
some of the direct dependencies for the given input (see the
``speed`` argument in one of the examples above).
This behaviour is desired when inspecting functions
for which is already known that some arguments won't be
injectable but they will be provided by other means
(like the ``drive`` function above).
But in other cases is better to be sure that all dependencies
are fulfilled and otherwise fail. Such is the case for classes.
So it is recommended to set ``full_final_kwargs=True`` when invoking
``andi.plan`` for classes.
Why type annotations?
---------------------
``andi`` uses type annotations to declare dependencies (inputs).
It has several advantages, and some limitations as well.
Advantages:
1. Built-in language feature.
2. You're not lying when specifying a type - these
annotations still work as usual type annotations.
3. In many projects you'd annotate arguments anyways, so ``andi`` support
is "for free".
Limitations:
1. Callable can't have two arguments of the same type.
2. This feature could possibly conflict with regular type annotation usages.
If your callable has two arguments of the same type, consider making them
different types. For example, a callable may receive url and html of
a web page:
.. code-block:: python
def parse(html: str, url: str):
# ...
To make it play well with ``andi``, you may define separate types for url
and for html:
.. code-block:: python
class HTML(str):
pass
class URL(str):
pass
def parse(html: HTML, url: URL):
# ...
This is more boilerplate though.
Why doesn't andi handle creation of objects?
--------------------------------------------
Currently ``andi`` just inspects callable and chooses best concrete types
a framework needs to create and pass to a callable, without prescribing how
to create them. This makes ``andi`` useful in various contexts - e.g.
* creation of some objects may require asynchronous functions, and it
may depend on libraries used (asyncio, twisted, etc.)
* in streaming architectures (e.g. based on Kafka) inspection may happen
on one machine, while creation of objects may happen on different nodes
in a distributed system, and then actually running a callable may happen on
yet another machine.
It is hard to design API with enough flexibility for all such use cases.
That said, ``andi`` may provide more helpers in future,
once patterns emerge, even if they're useful only in certain contexts.
Examples: callback based frameworks
-----------------------------------
Spider example
**************
Nothing better than a example to understand how ``andi`` can be useful.
Let's imagine you want to implemented a callback based framework
for writing spiders to crawl web pages.
The basic idea is that there is framework in which the user
can write spiders. Each spider is a collection of callbacks
that can process data from a page, emit extracted data or request new
pages. Then, there is an engine that takes care of downloading
the web pages
and invoking the user defined callbacks, chaining requests
with its corresponding callback.
Let's see an example of an spider to download recipes
from a cooking page:
.. code-block:: python
class MySpider(Spider):
start_url = "htttp://a_page_with_a_list_of_recipes"
def parse(self, response):
for url in recipes_urls_from_page(response)
yield Request(url, callback=parse_recipe)
def parse_recipe(self, response):
yield extract_recipe(response)
It would be handy if the user can define some requirements
just by annotating parameters in the callbacks. And ``andi`` make it
possible.
For example, a particular callback could require access to the cookies:
.. code-block:: python
def parse(self, response: Response, cookies: CookieJar):
# ... Do something with the response and the cookies
In this case, the engine can use ``andi`` to inspect the ``parse`` method, and
detect that ``Response`` and ``CookieJar`` are required.
Then the framework will build them and will invoke the callback.
This functionality would serve to inject into the users callbacks
some components only when they are required.
It could also serve to encapsulate better the user code. For
example, we could just decouple the recipe extraction into
it's own class:
.. code-block:: python
@dataclass
class RecipeExtractor:
response: Response
def to_item():
return extract_recipe(self.response)
The callback could then be defined as:
.. code-block:: python
def parse_recipe(extractor: RecipeExtractor):
yield extractor.to_item()
Note how handy is that with ``andi`` the engine can create
an instance of ``RecipesExtractor`` feeding it with the
declared ``Response`` dependency.
In definitive, using ``andi`` in such a framework
can provide great flexibility to the user
and reduce boilerplate.
Web server example
******************
``andi`` can be useful also for implementing a new
web framework.
Let's imagine a framework where you can declare your sever in a
class like the following:
.. code-block:: python
class MyWeb(Server):
@route("/products")
def productspage(self, request: Request):
... # return the composed page
@route("/sales")
def salespage(self, request: Request):
... # return the composed page
The former case is composed of two endpoints, one for serving
a page with a summary of sales, and a second one to serve
the products list.
Connection to the database can be required
to sever these pages. This logic could be encapsulated
in some classes:
.. code-block:: python
@dataclass
class Products:
conn: DBConnection
def get_products()
return self.conn.query("SELECT ...")
@dataclass
class Sales:
conn: DBConnection
def get_sales()
return self.conn.query("SELECT ...")
Now ``productspage`` and ``salespage`` methods can just declare
that they require these objects:
.. code-block:: python
class MyWeb(Server):
@route("/products")
def productspage(self, request: Request, products: Products):
... # return the composed page
@route("/sales")
def salespage(self, request: Request, sales: Sales):
... # return the composed page
And the framework can then be responsible to fulfill these
dependencies. The flexibility offered would be a great advantage.
As an example, if would be very easy to create a page that requires
both sales and products:
.. code-block:: python
@route("/overview")
def productspage(self, request: Request,
products: Products, sales: Sales):
... # return the composed overview page
Contributing
============
* Source code: https://github.com/scrapinghub/andi
* Issue tracker: https://github.com/scrapinghub/andi/issues
Use tox_ to run tests with different Python versions::
tox
The command above also runs type checks; we use mypy.
.. _tox: https://tox.readthedocs.io
Changes
=======
0.4.1 (2021-02-11)
------------------
* Overrides support in ``andi.plan``
0.4.0 (2020-04-23)
------------------
* ``andi.inspect`` can handle classes now (their ``__init__`` method
is inspected)
* ``andi.plan`` and ``andi.inspect`` can handle objects which are
callable via ``__call__`` method.
0.3.0 (2020-04-03)
------------------
* ``andi.plan`` function replacing ``andi.to_provide``.
* Rewrite README explaining the new approach based in ``plan`` method.
* ``andi.inspect`` return non annotated arguments also.
0.2.0 (2020-02-14)
------------------
* Better attrs support (workaround issue with string type annotations).
* Declare Python 3.8 support.
* More tests; ensure dataclasses support.
0.1 (2019-08-28)
----------------
Initial release.
نحوه نصب
نصب پکیج whl andi-0.4.1:
pip install andi-0.4.1.whl
نصب پکیج tar.gz andi-0.4.1:
pip install andi-0.4.1.tar.gz