:fire:toastedmarshmallow:fire:: Makes Marshmallow Toasty Fast
Toasted Marshmallow implements a JIT for marshmallow that speeds up dumping
objects 10-25X (depending on your schema). Toasted Marshmallow allows you to
have the great API that
Marshmallow <https://github.com/marshmallow-code/marshmallow>
_ provides
without having to sacrifice performance!
::
Benchmark Result:
Original Time: 2682.61 usec/dump
Optimized Time: 176.38 usec/dump
Speed up: 15.21x
Even PyPy
benefits from toastedmarshmallow
!
::
Benchmark Result:
Original Time: 189.78 usec/dump
Optimized Time: 20.03 usec/dump
Speed up: 9.48x
Installing toastedmarshmallow
.. code-block:: bash
pip install toastedmarshmallow
This will also install a slightly-forked marshmallow
that includes some
hooks Toastedmarshmallow needs enable the JIT to run before falling back
to the original marshmallow code. These changes are minimal making it easier
to track upstream. You can find the changes
Here <https://github.com/marshmallow-code/marshmallow/pull/629/files>
_.
This means you should remove marshmallow
from your requirements and
replace it with toastedmarshmallow
. By default there is no
difference unless you explicitly enable Toasted Marshmallow.
Enabling Toasted Marshmallow
Enabling Toasted Marshmallow on an existing Schema is just one line of code,
set the jit
property on any Schema
instance to
toastedmarshmallow.Jit
. For example:
.. code-block:: python
from datetime import date
import toastedmarshmallow
from marshmallow import Schema, fields, pprint
class ArtistSchema(Schema):
name = fields.Str()
class AlbumSchema(Schema):
title = fields.Str()
release_date = fields.Date()
artist = fields.Nested(ArtistSchema())
schema = AlbumSchema()
# Specify the jit method as toastedmarshmallow's jit
schema.jit = toastedmarshmallow.Jit
# And that's it! Your dump methods are 15x faster!
It's also possible to use the Meta
class on the Marshmallow
schema
to specify all instances of a given Schema
should be optimized:
.. code-block:: python
import toastedmarshmallow
from marshmallow import Schema, fields, pprint
class ArtistSchema(Schema):
class Meta:
jit = toastedMarshmallow.Jit
name = fields.Str()
You can also enable Toasted Marshmallow globally by setting the environment
variable MARSHMALLOW_SCHEMA_DEFAULT_JIT
to toastedmarshmallow.Jit
.
Future versions of Toasted Marshmallow may make this the default.
How it works
Toasted Marshmallow works by generating code at runtime to optimize dumping
objects without going through layers and layers of reflection. The generated
code optimistically assumes the objects being passed in are schematically valid,
falling back to the original marshmallow code on failure.
For example, taking AlbumSchema
from above, Toastedmarshmallow will
generate the following 3 methods:
.. code-block:: python
def InstanceSerializer(obj):
res = {}
value = obj.release_date; value = value() if callable(value) else value; res["release_date"] = _field_release_date__serialize(value, "release_date", obj)
value = obj.artist; value = value() if callable(value) else value; res["artist"] = _field_artist__serialize(value, "artist", obj)
value = obj.title; value = value() if callable(value) else value; value = str(value) if value is not None else None; res["title"] = value
return res
def DictSerializer(obj):
res = {}
if "release_date" in obj:
value = obj["release_date"]; value = value() if callable(value) else value; res["release_date"] = _field_release_date__serialize(value, "release_date", obj)
if "artist" in obj:
value = obj["artist"]; value = value() if callable(value) else value; res["artist"] = _field_artist__serialize(value, "artist", obj)
if "title" in obj:
value = obj["title"]; value = value() if callable(value) else value; value = str(value) if value is not None else None; res["title"] = value
return res
def HybridSerializer(obj):
res = {}
try:
value = obj["release_date"]
except (KeyError, AttributeError, IndexError, TypeError):
value = obj.release_date
value = value; value = value() if callable(value) else value; res["release_date"] = _field_release_date__serialize(value, "release_date", obj)
try:
value = obj["artist"]
except (KeyError, AttributeError, IndexError, TypeError):
value = obj.artist
value = value; value = value() if callable(value) else value; res["artist"] = _field_artist__serialize(value, "artist", obj)
try:
value = obj["title"]
except (KeyError, AttributeError, IndexError, TypeError):
value = obj.title
value = value; value = value() if callable(value) else value; value = str(value) if value is not None else None; res["title"] = value
return res
Toastedmarshmallow will invoke the proper serializer based upon the input.
Since Toastedmarshmallow is generating code at runtime, it's critical you
re-use Schema objects. If you're creating a new Schema object every time you
serialize/deserialize an object you'll likely have much worse performance.