Responses¶
Lilya, by design, furnishes specific response classes that serve a dual purpose. They offer
utility and are tasked with sending the appropriate ASGI messages through the send
channel.
Lilya automatically includes the Content-Length
and Content-Type
headers.
How does it work¶
There are a few ways of using the responses within a Lylia application.
- You can import the appropriate
response
class and use it directly. - You can build the response.
- You can delegate to Lilya.
- Build a custom encoder that will allow Lilya to automatically parse the response.
Available responses¶
All the responses from Lilya inherit from the parent object Response
and that same class can
also be used directly.
All the responses are considered ASGI applications, which means you can treat them as such in your application if necessary.
Example
from lilya.responses import PlaiText
from lilya.types import Scope, Receive, Send
async def asgi_app(scope: Scope, receive: Receive, send: Send):
assert scope['type'] == 'http'
response = PlaiText('Welcome')
await response(scope, receive, send)
Response¶
from lilya.responses import Response
Example
from lilya.apps import Lilya
from lilya.responses import Response
from lilya.routing import Path
def home():
return Response("Welcome home")
app = Lilya(routes=[Path("/", home)])
Set cookie¶
Lilya provides the set_cookie
that allows settings a cookie on a given response. All the responses
available in Lilya have access to this functionality.
from lilya.responses import Response
from lilya.types import Scope, Receive, Send
async def asgi_app(scope: Scope, receive: Receive, send: Send):
assert scope['type'] == 'http'
response = Response('Welcome', media_type='text/plain')
response.set_cookie(key=..., value=..., max_age=..., expires=...,)
await response(scope, receive, send)
Parameters¶
The available parameters of the set_cookie
are as follow:
key
- A string representing the cookie's key.value
- A string representing the cookie's value.max_age
- An integer defining the cookie's lifetime in seconds. A negative value or 0 discards the cookie immediately. (Optional)expires
- Either an integer indicating the seconds until the cookie expires or a datetime. (Optional)path
- A string specifying the subset of routes to which the cookie applies. (Optional)domain
- A string specifying the valid domain for the cookie. (Optional)secure
- A boolean indicating that the cookie is sent to the server only if the request uses SSL and the HTTPS protocol. (Optional)httponly
- A boolean indicating that the cookie is inaccessible via JavaScript through Document.cookie, the XMLHttpRequest, or Request APIs. (Optional)samesite
- A string specifying the samesite strategy for the cookie, with valid values of'lax'
,'strict'
, and'none'
. Defaults to 'lax'. (Optional)
Delete cookie¶
In the same fashion as the set cookie, this function is available on every response provided by Lilya.
from lilya.responses import Response
from lilya.types import Scope, Receive, Send
async def asgi_app(scope: Scope, receive: Receive, send: Send):
assert scope['type'] == 'http'
response = Response('Welcome', media_type='text/plain')
response.delete_cookie(key=..., path=..., domain=...)
await response(scope, receive, send)
Parameters¶
The available parameters of the set_cookie
are as follow:
key
- A string representing the cookie's key.path
- A string specifying the subset of routes to which the cookie applies. (Optional)domain
- A string specifying the valid domain for the cookie. (Optional)
HTMLResponse¶
Returning an html
response.
from lilya.responses import HTMLResponse
Example
from lilya.apps import Lilya
from lilya.responses import HTMLResponse
from lilya.routing import Path
def home():
return HTMLResponse("<html><body><p>Welcome!</p></body></html>")
app = Lilya(routes=[Path("/", home)])
Error¶
Response that can be used when throwing a 500
error. Defaults to return an html
response.
from lilya.responses import Error
Example
from lilya.apps import Lilya
from lilya.responses import Error
from lilya.routing import Path
def home():
return Error("<html><body><p>Error!</p></body></html>")
app = Lilya(routes=[Path("/", home)])
PlainText¶
Response that can be used to return text/plain
.
from lilya.responses import PlainText
Example
from lilya.apps import Lilya
from lilya.responses import PlainText
from lilya.routing import Path
def home():
return PlainText("Welcome home")
app = Lilya(routes=[Path("/", home)])
JSONResponse¶
Response that can be used to return application/json
.
from lilya.responses import JSONResponse
Example
from lilya.apps import Lilya
from lilya.responses import JSONResponse
from lilya.routing import Path
def home():
return JSONResponse({"message": "Welcome home"})
app = Lilya(routes=[Path("/", home)])
Ok¶
Response that can be used to return application/json
as well. You can see this as an
alternative to JSONResponse
.
from lilya.responses import Ok
Example
from lilya.apps import Lilya
from lilya.responses import Ok
from lilya.routing import Path
def home():
return Ok({"message": "Welcome home"})
app = Lilya(routes=[Path("/", home)])
RedirectResponse¶
Used for redirecting the responses.
from lilya.responses import RedirectResponse
Example
from lilya.apps import Lilya
from lilya.responses import RedirectResponse
from lilya.routing import Path
def home():
return RedirectResponse(url="/another-url")
app = Lilya(routes=[Path("/", home)])
StreamingResponse¶
from lilya.responses import StreamingResponse
Example
from collections.abc import Generator
from lilya.apps import Lilya
from lilya.responses import StreamingResponse
from lilya.routing import Path
def my_generator() -> Generator[str, None, None]:
count = 0
while True:
count += 1
yield str(count)
def home():
return StreamingResponse(my_generator(), media_type="text/html")
app = Lilya(routes=[Path("/", home)])
FileResponse¶
from lilya.responses import FileResponse
Streams a file asynchronously as the response, employing a distinct set of arguments for instantiation compared to other response types:
path
- The filepath to the file to stream.status_code
- The Status code to return.headers
- Custom headers to include, provided as a dictionary.media_type
- A string specifying the media type. If unspecified, the filename or path is used to deduce the media type.filename
- If specified, included in the response Content-Disposition.content_disposition_type
- Included in the response Content-Disposition. Can be set toattachment
(default) orinline
.background
- A task instance.
Example
from lilya.apps import Lilya
from lilya.responses import FileResponse
from lilya.routing import Path
def home():
return FileResponse(
"files/something.csv",
filename="something",
)
app = Lilya(routes=[Path("/", home)])
Importing the appropriate class¶
This is the classic most used way of using the responses. The available responses contains a list of available responses of Lilya but you are also free to design your own and apply them.
Example
from lilya.apps import Lilya
from lilya.responses import JSONResponse
from lilya.routing import Path
def home():
return JSONResponse({"message": "Welcome home"})
app = Lilya(routes=[Path("/", home)])
Build the Response¶
This is where the things get great. Lilya provides a make_response
function that automatically
will build the response for you.
from lilya.responses import make_response
Example
from lilya.apps import Lilya
from lilya.responses import make_response
from lilya.routing import Path
def home():
return make_response({{"message": "Hello"}}, status_code=201)
app = Lilya(routes=[Path("/", home)])
By default, the make_response
returns a JSONResponse but that can be also
changed if the response_class
parameter is set to something else.
So, why is this make_response
different from the other responses? Well, here its where Lilya shines.
Lilya is pure Python, which means that it does not rely or depend on external libraries like Pydantic,
msgspec, attrs or any other but allows you to build a custom encoder that
can later be used to serialise your response automatically and then passed to the make_response
.
Check the build a custom encoder and custom encoders with make_response for more details and how to leverage the power of Lilya.
Delegate to Lilya¶
Delegating to Lilya means that if no response is specified, Lilya will go through the internal
encoders
and will try to jsonify
the response for you.
Let us see an example.
from lilya.apps import Lilya
from lilya.routing import Path
def home():
return {"message": "Welcome home"}
app = Lilya(routes=[Path("/", home)])
As you can see, no response
was specified but instead a python dict
was returned. What Lilya
internally does is to guess and understand the type of response parse the result into json
and returning a JSONResponse
automatically,
If the type of response is not json serialisable, then a ValueError
is raised.
Let us see some more examples.
from lilya.apps import Lilya
from lilya.routing import Path
def home_dict():
return {"message": "Welcome home"}
def home_frozen_set():
return frozenset({"message": "Welcome home"})
def home_set():
return set({"message": "Welcome home"})
def home_list():
return ["Welcome", "home"]
def home_str():
return "Welcome home"
def home_int():
return 1
def home_float():
return 2.0
app = Lilya(
routes=[
Path("/dict", home_dict),
Path("/fronzenset", home_frozen_set),
Path("/set", home_set),
Path("/list", home_list),
Path("/str", home_str),
Path("/int", home_int),
Path("/float", home_float),
]
)
And the list goes on and on. Lilya by design understands almost every single datastructure of Python
by default, including Enum
, deque
, dataclasses
, PurePath
, generators
and tuple
.
Default Encoders¶
In order to understand how to serialise a specific object into json
, Lilya has some default
encoders that evaluates when tries to guess the response type.
DataclassEncoder
- Serialisesdataclass
objects.EnumEncoder
- SerialisesEnum
objects.PurePathEncoder
- SerializesPurePath
objects.PrimitiveEncoder
- Serializes python primitive types.str, int, float and None
.DictEncoder
- Serializesdict
types.StructureEncoder
- Serializes more complex data types.list, set, frozenset, GeneratorType, tuple, deque
.
What a brand new encoder is needed and it is not natively supported by Lilya? Well, building a custom encoder is extremly easy and possible.
Build a custom encoder¶
As mentioned before, Lilya has default encoders that are used to transform a response
into a json
serialisable response.
To build a custom encoder you must use the Encoder
class from Lilya and override the serialize()
function
where it applies the serialisation process of the encoder type.
Then you must register the encoder for Lilya to use it.
When defining an encoder the __type__
or def is_type(self, value: Any) -> bool:
must be declared or overridden.
When the __type__
is properly declared, the default is_type
will evaluate the object against the
type and return True
or False
.
This is used internally to understand the type of encoder that will be applied to a given object.
Warning
If you are not able to provide the __type__
for any reason and you just want to override the
default evaluation process, simple override the is_type()
and apply your custom logic there.
E.g.: In Python 3.8, for a Pydantic BaseModel
if passed in the __type__
, it will throw an
error due to Pydantic internals, so to workaround this issue, you can simply override the is_type()
and apply the logic that validates the type of the object and returns a boolean.
from lilya.encoders import Encoder, register_encoder
Example
Create and register an encoder that handles msgspec.Struct
types.
from typing import Any
import msgspec
from msgspec import Struct
from lilya.encoders import Encoder, register_encoder
class MsgSpecEncoder(Encoder):
__type__ = Struct
def serialize(self, obj: Any) -> Any:
"""
When a `msgspec.Struct` is serialised,
it will call this function.
"""
return msgspec.json.decode(msgspec.json.encode(obj))
# A normal way
register_encoder(MsgSpecEncoder())
# As alternative
register_encoder(MsgSpecEncoder)
Simple right? Because now the MsgSpecEncoder
is registered, you can simply do this in your handlers
and return directly the msgspec.Struct
object type.
from msgspec import Struct
from lilya.routing import Path
class User(Struct):
name: str
email: str
def msgspec_struct():
return User(name="lilya", url="example@lilya.dev")
Design specific custom encoders¶
Lilya being 100% pure python and not tight to any particular validation library allows you to design custom encoders that are later used by Lilya responses.
Ok, this sounds a bit confusing right? I bet it does so let us go slowly.
Imagine you want to use a particular validation library such as Pydantic, msgspec or even attrs or something else at your choice.
You want to make sure that if you return a pydantic model or a msgspec Struct or even a define
attr class.
Let us see how it would look like for all of them.
For Pydantic BaseModel
from __future__ import annotations
from typing import Any
from pydantic import BaseModel
from lilya.encoders import Encoder, register_encoder
class PydanticEncoder(Encoder):
__type__ = BaseModel
def serialize(self, obj: BaseModel) -> dict[str, Any]:
return obj.model_dump()
# A normal way
register_encoder(PydanticEncoder())
# As alternative
register_encoder(PydanticEncoder)
For msgspec Struct
from typing import Any
import msgspec
from msgspec import Struct
from lilya.encoders import Encoder, register_encoder
class MsgSpecEncoder(Encoder):
__type__ = Struct
def serialize(self, obj: Any) -> Any:
"""
When a `msgspec.Struct` is serialised,
it will call this function.
"""
return msgspec.json.decode(msgspec.json.encode(obj))
# A normal way
register_encoder(MsgSpecEncoder())
# As alternative
register_encoder(MsgSpecEncoder)
For attrs
from typing import Any
from attrs import asdict, has
from lilya.encoders import Encoder, register_encoder
class AttrsEncoder(Encoder):
def is_type(self, value: Any) -> bool:
"""
You can use this function instead of declaring
the `__type__`.
"""
return has(value)
def serialize(self, obj: Any) -> Any:
return asdict(obj)
# A normal way
register_encoder(AttrsEncoder())
# As alternative
register_encoder(AttrsEncoder)
Easy and poweful, right? Yes.
Do you understand what does this mean? Means you can design any encoder at your choice using also any library of your choice as well.
The flexibility of Lilya allows you to be free and for Lilya not to be tight to any particular library.
Custom encoders and responses¶
After the custom encoders in the examples are created, this allows to do something like this directly.
from attrs import define
from msgspec import Struct
from pydantic import BaseModel
from lilya.apps import Lilya
from lilya.routing import Path
class User(BaseModel):
name: str
age: int
class Item(Struct):
name: str
age: int
@define
class AttrItem:
name: str
age: int
def pydantic_response():
return User(name="lilya", age=24)
def pydantic_response_list():
return [User(name="lilya", age=24)]
def msgspec_struct():
return Item(name="lilya", age=24)
def msgspec_struct_list():
return [Item(name="lilya", age=24)]
def attrs_response():
return AttrItem(name="lilya", age=24)
def attrs_response_list():
return [AttrItem(name="lilya", age=24)]
app = Lilya(
routes=[
Path("/pydantic", pydantic_response),
Path("/pydantic-list", pydantic_response_list),
Path("/msgspec", msgspec_struct),
Path("/msgspec-list", pydantic_response_list),
Path("/attrs", attrs_response),
Path("/attrs-list", attrs_response_list),
]
)
Custom encoders and the make_response
¶
Well, here its where the make_response
helps you. The make_response
will generate a JSONResponse
by default and when you return a custom encoder type, there are some limitations to it.
For example, what if you want to return with a different status_code
? Or even attach a task
to it?
The custom encoder does not handle that for you but the make_response
does!
Let us see how it would look like now using the make_response
.
from attrs import define
from msgspec import Struct
from pydantic import BaseModel
from lilya import status
from lilya.apps import Lilya
from lilya.responses import make_response
from lilya.routing import Path
class User(BaseModel):
name: str
age: int
class Item(Struct):
name: str
age: int
@define
class AttrItem:
name: str
age: int
def pydantic_response():
data = User(name="lilya", age=24)
return make_response(
data,
status_code=status.HTTP_200_OK,
)
def pydantic_response_list():
data = [User(name="lilya", age=24)]
return make_response(
data,
status_code=status.HTTP_201_CREATED,
background=...,
headers=...,
)
def msgspec_struct():
return make_response(Item(name="lilya", age=24))
def msgspec_struct_list():
return make_response(
[Item(name="lilya", age=24)],
status_code=...,
)
def attrs_response():
return make_response(
AttrItem(name="lilya", age=24),
status_code=...,
)
def attrs_response_list():
return make_response(
[AttrItem(name="lilya", age=24)],
status_code=...,
)
app = Lilya(
routes=[
Path("/pydantic", pydantic_response),
Path("/pydantic-list", pydantic_response_list),
Path("/msgspec", msgspec_struct),
Path("/msgspec-list", pydantic_response_list),
Path("/attrs", attrs_response),
Path("/attrs-list", attrs_response_list),
]
)