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Python library for simplified YAML object serialization

Project description

yaml-serde - Simplified YAML serialization framework

yaml-serde provides a framework for implementing custom conversions of Python objects to and from the YAML serialization format.

These transformations allow applications to use YAML as a simple way to persist and share objects.

Python to YAML

After the appropriate serializers have been defined (see Custom YAML serialization), objects can be transformed to a YAML string using function yml():

from yaml_serde import YamlSerializer, yml, repr_yml

class Foo(list):
  def __init__(self):
    super().__init__(Bar(1), Bar(2), Bar(3))

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"foo": [repr_yml(b, **kwargs) for b in py_repr]}

class Bar:
  def __init__(self, n):
    self.n = n

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"bar": py_repr.n}

foo = Foo()
yml_str = yml(foo)
assert yml_str == """---
foo:
  - bar: 1
  - bar: 2
  - bar: 3

...
"""

The result can also be saved directly into a file by specifying a path with to_file:

yml(foo, to_file="foo.yml")

If you prefer, you can also convert objects to JSON using function json():

from yaml_serde import yml

foo = Foo()
json_str = json(foo)
assert json_str == '{"foo": [{"bar": 1}, {"bar": 2}, {"bar": 3}]}'

YAML to Python

Given a YAML (or JSON) string, you can build a Python object out of it using function yml_obj(). This function takes a class object and the input string, and will return an instance of the class built by its serializer:

import pathlib
from yaml_serde import YamlSerializer, yml, repr_yml, yml_obj, repr_py

class Foo(list):
  def __init__(self, *args):
    if not args:
      args = (Bar(1), Bar(2), Bar(3))
    super().__init__(*args)

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"foo": [repr_yml(b, **kwargs) for b in py_repr]}
    def repr_py(self, yml_repr, **kwargs):
      return Foo(*[repr_py(Bar, b, **kwargs) for b in yml_repr["foo"]])

class Bar:
  def __init__(self, n):
    self.n = n

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"bar": py_repr.n}
    def repr_py(self, yml_repr, **kwargs):
      return Bar(yml_repr["bar"])

with pathlib.Path("foo.yml").open("r") as input:
  foo = yml_obj(Foo, input.read())

Since loading YAML from a file is common enough, yml_obj() offers argument from_file to indicate that the input is the path of a file from which to read the input string:

foo = yml_obj(Foo, "foo.yml", from_file=True)

Custom YAML serialization

The yaml-serde framework is built on top of PyYAML, as way to easily call functions yaml.safe_dump() and yaml.safe_load() on objects of any user-defined class.

The PyYAML functions only accept basic Python objects such as numbers, strings, arrays, and dictionaries, and they are designed to reject any generic "object" (which must be handled using their "unsafe" counterparts).

For this reason, yaml_serde allows users to implement the logic required to convert instances of their classes into "YAML-safe" representations compatible with the PyYAML functions.

The conversion is implemented by a nested "serializer" class, called _YamlSerializer and derived from yaml_serde.YamlSerializer, which must be manually defined for every class to convert, and provide two methods:

  • YamlSerializer::repr_yml(self, py_repr, **kwargs):

    • Take an object in its "Python representation" and return the equivalent "YAML representation".
    • The value returned by this function must be safe to pass to yaml.safe_dump().
  • YamlSerializer::repr_py(self, yml_repr, **kwargs):

    • Take an object's "YAML representation" and return its "Python representation".
    • The value returned by this function should be an instance of the associated class.

Implementations are free to map an objects state to YAML however they prefer.

For example, in the case of a trivial class, a simple string might be used:

from yaml_serde import YamlSerializer, repr_yml

class MyClass:
  def __init__(self, foo : str):
    self.foo = foo

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return py_repr.foo
    def repr_py(self, yml_repr, **kwargs):
      return MyClass(yml_repr)

In most cases, a class will likely map to a dictionary, with entries for each of its state attributes.

Two convenience functions (repr_yml() and repr_py()) can be used to automatically invoke an object's serializer, and convert it between the two formats. These functions can be useful to build a "recursive" serializer:

from yaml_serde import YamlSerializer, repr_yml, repr_py

class Foo(list):
  def __init__(self, *args):
    if not args:
      args = (Bar(1), Bar(2), Bar(3))
    super().__init__(*args)

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"foo": [repr_yml(b, **kwargs) for b in py_repr]}
    def repr_py(self, yml_repr, **kwargs):
      return Foo(*[repr_py(Bar, b, **kwargs) for b in yml_repr["foo"]])

class Bar:
  def __init__(self, n):
    self.n = n

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"bar": py_repr.n}
    def repr_py(self, yml_repr, **kwargs):
      return Bar(yml_repr["bar"])

The serializer class will be passed through all the extra keyword arguments passed to the yml() and yml_obj() functions.

This can be used to implement optional behavior in the serializer, for example to exclude certain fields from serialization:

from yaml_serde import YamlSerializer, repr_yml

class MyClassWithPrivateFields:
  def __init__(self, user : str, passwd : str):
    self.user = user
    self.passwd = passwd

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      yml_repr = {"user": py_repr.user}
      if not kwargs.get("public_only"):
        yml_repr["passwd"] = py_repr.passwd
      return yml_repr
    def repr_py(self, yml_repr, **kwargs):
      return MyClass(yml_repr["user"], yml_repr.get("passwd",""))

def test_my_class_with_private_fields():
  from yaml_serde import yml, yml_obj

  obj = MyClassWithPrivateFields("foo", "bar")

  yml_str = yml(obj)
  assert "passwd: bar" in yml_str

  obj = yml_obj(MyClassWithPrivateFields, yml_str)
  assert obj.passwd == "bar"

  yml_str = yml(obj, public_only=True)
  assert "passwd: bar" not in yml_str

  obj = yml_obj(MyClassWithPrivateFields, yml_str)
  assert obj.passwd == ""

Class YamlSerializer offers two methods which subclasses can override to customize the serialization of data in files:

  • YamlSerializer::file_format_out() is called when a YAML string is about to be written to a file. It takes the YAML string (along with any extra keyword arguments passed to yml()), and it must return the actual string that will be written to the file system.

  • YamlSerializer::file_format_in() is called whenever a YAML string is loaded from a file. It take the file's contents (along with any extra keywork arguments passed to yml_obj()) and it must return the string to parse into an object.

These function can be used to pre/post-process the contents of a file, for example to encode it on serialization, and decoding it when the value is read back from the file:

from yaml_serde import YamlSerializer, repr_yml

class MyEncodedClass:
  def __init__(self, user : str, passwd : str):
    self.user = user
    self.passwd = passwd

  class _YamlSerializer(YamlSerializer):
    def repr_yml(self, py_repr, **kwargs):
      return {"user": py_repr.user, "passwd": py_repr.passwd}
    def repr_py(self, yml_repr, **kwargs):
      return MyClass(yml_repr["user"], yml_repr["passwd"])
    def file_format_in(self, yml_str, **kwargs):
      encoder = kwargs["encoder"]
      return encoder.encode(yml_str)
    def file_format_out(self, yml_str, **kwargs):
      encoder = kwargs["encoder"]
      return encoder.decode(yml_str)

class MyEncoder:
  def __init__(self, prefix):
    self.prefix = prefix
  def encode(self, contents):
    return f"{self.prefix}{contents}{self.prefix}"
  def decode(self, contents):
    return contents[len(self.prefix):-len(self.prefix)]
  def verify(self, encoded):
    assert encoded.startswith(self.prefix)
    assert encoded.endswith(self.prefix)

def test_my_encoded_class():
  from yaml_serde import yml, yml_obj

  from my_encoder_package import MyEncoder

  obj = MyEncodedClass("foo", "bar")

  encoder = MyEncoder("****\n")

  yml(obj, to_file="encoded.yml", encoder=encoder)

  import pathlib
  with pathlib.Path("encoded.yml").open("r") as input:
    assert encoder.verify(input.read())

  obj = yml_obj(MyEncodedClass, "encoded.yml", from_file=True, encoder=encoder)

  assert obj.user == "foo"
  assert obj.passwd == "bar"

A similar result may also be achieved by having the serializer use a custom FileSystem implementation. By default, any YamlSerializer will rely on a LocalFileSytem instance, which provides access to writing and storing files in the local file system, and does not apply any transformation to file contents.

Overriding the FileSystem class allows the same processing logic to be reused by multiple YamlSerializer classes:

from yaml_serde import LocalFileSystem

class MyEncoder:
  def __init__(self, prefix):
    self.prefix = prefix
  def encode(self, contents):
    return f"{self.prefix}{contents}{self.prefix}"
  def decode(self, contents):
    return contents[len(self.prefix):-len(self.prefix)]
  def verify(self, encoded):
    assert encoded.startswith(self.prefix)
    assert encoded.endswith(self.prefix)

class MyEncodedFileSystem(LocalFileSystem):
  def format_output(self, output, append=False, **kwargs):
    pfx = kwargs.get("pfx")
    if pfx is not None:
      encoded = MyEncoder(pfx)
      return self.encoder.encode(output)
    else:
      return output

  def format_input(self, input, **kwargs):
    pfx = kwargs.get("pfx")
    if pfx is not None:
      encoded = MyEncoder(pfx)
      return self.encoder.decode(input)
    else:
      return input

encoded_fs = MyEncodedFileSystem()

class MyEncodedClass:
  def __init__(self, user : str, passwd : str):
    self.user = user
    self.passwd = passwd

  class _YamlSerializer(YamlSerializer):
    fs = encoded_fs
    def repr_yml(self, py_repr, **kwargs):
      return {"user": py_repr.user, "passwd": py_repr.passwd}
    def repr_py(self, yml_repr, **kwargs):
      return MyClass(yml_repr["user"], yml_repr["passwd"])

class MyOtherEncodedClass:
  def __init__(self, foo : str):
    self.foo = foo

  class _YamlSerializer(YamlSerializer):
    fs = encoded_fs
    def repr_yml(self, py_repr, **kwargs):
      return py_repr.foo
    def repr_py(self, yml_repr, **kwargs):
      return MyClass(yml_repr)

def test_my_encoded_classes():
  from yaml_serde import yml, yml_obj

  from my_encoder_package import MyEncoder

  obj = MyEncodedClass("foo", "bar")
  other_obj = MyOtherEncodedClass("foo")

  pfx = "****\n"

  yml(obj, to_file="encoded_obj.yml", pfx=pfx)
  yml(obj, to_file="encoded_other_obj.yml", pfx=pfx)

  encoder = MyEncoder(pfx)
  def check_encoded(f):
    import pathlib
    with pathlib.Path(f).open("r") as input:
      assert encoder.verify(input.read())

  check_encoded("encoded_obj.yml")
  check_encoded("encoded_other_obj.yml")

  obj = yml_obj(MyEncodedClass, "encoded_obj.yml", from_file=True, pfx=pfx)
  assert obj.user == "foo"
  assert obj.passwd == "bar"

  other_obj = yml_obj(MyOtherEncodedClass, "encoded_other_obj.yml", from_file=True, pfx=pfx)
  assert other_obj.foo == "foo"

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