Merge a series of JSON documents

This Python module allows you to merge a series of JSON documents into a
single one.

This problem often occurs for example when different authors fill in
different parts of a common document and you need to construct a document
that includes contributions from all the authors. It also helps when
dealing with consecutive versions of a document where different fields get
updated over time.

Consider a trivial example with two documents::

>>> base = {
...         "foo": 1,
...         "bar": [ "one" ],
...      }

>>> head = {
...         "bar": [ "two" ],
...         "baz": "Hello, world!"
...     }

We call the document we are merging changes into base and the changed
document head. To merge these two documents using jsonmerge::

>>> from pprint import pprint

>>> from jsonmerge import merge
>>> result = merge(base, head)

>>> pprint(result, width=40)
{'bar': ['two'],
 'baz': 'Hello, world!',
 'foo': 1}

As you can see, when encountering an JSON object, jsonmerge by default
returns fields that appear in either base or head document. For other
JSON types, it simply replaces the older value. These principles are also
applied in case of multiple nested JSON objects.

In a more realistic use case however, you might want to apply different
merge strategies to different parts of the document. You can tell
jsonmerge how to do that using a syntax based on JSON schema_.

If you already have schemas for your document, you can simply expand them
with some additional keywords. Apart from the custom keywords described
below, jsonmerge by default uses the schema syntax defined in the Draft 4_ of the JSON schema specification.

You use the mergeStrategy schema keyword to specify the strategy. The
default two strategies mentioned above are called objectMerge for objects
and overwrite for all other types.

Let's say you want to specify that the merged bar field in the example
document above should contain elements from all documents, not just the
latest one. You can do this with a schema like this::

>>> schema = {
...             "properties": {
...                 "bar": {
...                     "mergeStrategy": "append"
...                 }
...             }
...         }

>>> from jsonmerge import Merger
>>> merger = Merger(schema)
>>> result = merger.merge(base, head)

>>> pprint(result, width=40)
{'bar': ['one', 'two'],
 'baz': 'Hello, world!',
 'foo': 1}

Another common example is when you need to keep a versioned list of values
that appeared in the series of documents::

>>> schema = {
...             "properties": {
...                 "foo": {
...                     "type": "object",
...                     "mergeStrategy": "version",
...                     "mergeOptions": { "limit": 5 }
...                 }
...             },
...             "additionalProperties": False
...         }
>>> from jsonmerge import Merger
>>> merger = Merger(schema)

>>> rev1 = {
...     'foo': {
...         'greeting': 'Hello, World!'
...     }
... }

>>> rev2 = {
...     'foo': {
...         'greeting': 'Howdy, World!'
...     }
... }

>>> base = None
>>> base = merger.merge(base, rev1, merge_options={
...                     'version': {
...                         'metadata': {
...                             'revision': 1
...                         }
...                     }
...                 })
>>> base = merger.merge(base, rev2, merge_options={
...                     'version': {
...                         'metadata': {
...                             'revision': 2
...                         }
...                     }
...                 })
>>> pprint(base, width=55)
{'foo': [{'revision': 1,
          'value': {'greeting': 'Hello, World!'}},
         {'revision': 2,
          'value': {'greeting': 'Howdy, World!'}}]}

Note that we use the mergeOptions keyword in the schema to supply
additional options to the merge strategy. In this case, we tell the
version strategy to retain only 5 most recent versions of this field.

We also used the merge_options argument to supply some options that are
specific to each call of the merge method. Options specified this
way are applied to all invocations of a specific strategy in a schema (in
contrast to mergeOptions, which applies only to the strategy invocation
in that specific location in the schema). Options specified in
mergeOptions schema keyword override the options specified in the
merge_options argument.

The metadata option for the version strategy can contain some document
meta-data that is included for each version of the field. metadata can
contain an arbitrary JSON object.

Example above also demonstrates how jsonmerge is typically used when
merging more than two documents. Typically you start with an empty base
and then consecutively merge different heads into it.

A common source of problems are documents that do not match the schema used
for merging. jsonmerge by itself does not validate input documents. It
only uses the schema to obtain necessary information to apply appropriate merge
strategies. Since the default strategies are used for parts of the
document that are not covered by the schema it's easy to get unexpected
output without any obvious errors raised by jsonmerge.

In the following example, the property Foo (uppercase F) does not match
foo (lowercase f) in the schema and hence the version strategy is not
applied as with previous two revisions::

>>> rev3 = {
...     'Foo': {
...         'greeting': 'Howdy, World!'
...     }
... }

>>> base = merger.merge(base, rev3, merge_options={
...                     'version': {
...                         'metadata': {
...                             'revision': 3
...                         }
...                     }
...                 })

>>> pprint(base, width=55)
{'Foo': {'greeting': 'Howdy, World!'},
 'foo': [{'revision': 1,
          'value': {'greeting': 'Hello, World!'}},
         {'revision': 2,
          'value': {'greeting': 'Howdy, World!'}}]}

Hence it is recommended to validate the input documents against the schema
before passing them to jsonmerge. This practice is even more effective if
the schema is filled in with more information than strictly necessary for
jsonmerge (e.g. adding information about types, restrict valid object
properties with additionalProperties, etc.)::

>>> from jsonschema import validate
>>> validate(rev1, schema)
>>> validate(rev2, schema)
>>> validate(rev3, schema)
Traceback (most recent call last):
    ...
jsonschema.exceptions.ValidationError: Additional properties are not allowed ('Foo' was unexpected)

If you care about well-formedness of your documents, you might also want to
obtain a schema for the documents that the merge method creates.
jsonmerge provides a way to automatically generate it from a schema for
the input document::

>>> result_schema = merger.get_schema()

>>> pprint(result_schema, width=80)
{'additionalProperties': False,
 'properties': {'foo': {'items': {'properties': {'value': {'type': 'object'}}},
                        'maxItems': 5,
                        'type': 'array'}}}

Note that because of the version strategy, the type of the foo field
changed from object to array.

Merge strategies

These are the currently implemented merge strategies.

overwrite
Overwrite with the value in base with value in head. Works with any
type.

discard
Keep the value in base, even if head contains a different value.
Works with any type.

By default, if base does not contain any value (i.e. that part of the
document is undefined), the value after merge is kept undefined. This can
be changed with the keepIfUndef option. If this option is true, then
the value from head will be retained in this case. This is useful if
you are merging a series of documents and want to keep the value that
first appears in the series, but want to discard further modifications.

append
Append arrays. Works only with arrays.

You can specify a sortByRef merge option to indicate the key that will
be used to sort the items in the array. This option can be an arbitrary
JSON pointer. When resolving the pointer the root is placed at the
root of the array item. Sort order can be reversed by setting the
sortReverse option.

arrayMergeById
Merge arrays, identifying items to be merged by an ID field. Resulting
arrays have items from both base and head arrays. Any items that
have identical an ID are merged based on the strategy specified further
down in the hierarchy.

By default, array items are expected to be objects and ID of the item is
obtained from the id property of the object.

You can specify an arbitrary JSON pointer to point to the ID of the
item using the idRef merge option. When resolving the pointer, document
root is placed at the root of the array item (e.g. by default, idRef is
'/id'). You can also set idRef to '/' to treat an array of integers or
strings as a set of unique values.

Array items in head for which the ID cannot be identified (e.g. idRef
pointer is invalid) are ignored.

You can specify an additional item ID to be ignored using the ignoreId
merge option.

A compound ID can be specified by setting idRef to an array of
pointers. In that case, if any pointer in the array is invalid for an
object in head, the object is ignored. If using an array for idRef
and if ignoreId option is also defined, ignoreId must be an array as
well.

You can specify a sortByRef merge option to indicate the key that will
be used to sort the items in the array. This option can be an arbitrary
JSON pointer. The pointer is resolved in the same way as idRef. Sort
order can be reversed by setting the sortReverse option.

arrayMergeByIndex
Merge array items by their index in the array. Similarly to
arrayMergeById strategy, the resulting arrays have items from both
base and head arrays. Items that occur at identical positions in both
arrays will be merged based on the strategy specified further down in the
hierarchy.

objectMerge
Merge objects. Resulting objects have properties from both base and
head. Any properties that are present both in base and head are
merged based on the strategy specified further down in the hierarchy
(e.g. in properties, patternProperties or additionalProperties
schema keywords).

The objClass option allows one to request a different dictionary class
to be used to hold the JSON object. The possible values are names that
correspond to specific Python classes. Built-in names include
OrderedDict, to use the collections.OrderedDict class, or dict,
which uses the Python's dict built-in. If not specified, dict is
used by default.

Note that additional classes or a different default can be configured via
the Merger() constructor (see below).

version
Changes the type of the value to an array. New values are appended to the
array in the form of an object with a value property. This way all
values seen during the merge are preserved.

You can add additional properties to the appended object using the
metadata option. Additionally, you can use metadataSchema option to
specify the schema for the object in the metadata option.

You can limit the length of the list using the limit option in the
mergeOptions keyword.

By default, if a head document contains the same value as the base,
document, no new version will be appended. You can change this by setting
ignoreDups option to false.

If a merge strategy is not specified in the schema, objectMerge is used
for objects and overwrite for all other values (but see also the section
below regarding keywords that apply subschemas).

You can implement your own strategies by making subclasses of
jsonmerge.strategies.Strategy and passing them to Merger() constructor
(see below).

The Merger Class

The Merger class allows you to further customize the merging of JSON
data by allowing you to:

set the schema containing the merge strategy configuration,
provide additional strategy implementations,
set a default class to use for holding JSON object data and
configure additional JSON object classes selectable via the objClass
merge option.

The Merger constructor takes the following arguments (all optional, except
schema):

schema
The JSON Schema that contains the merge strategy directives
provided as a JSON object. An empty dictionary should be provided
if no strategy configuration is needed.

strategies
A dictionary mapping strategy names to instances of Strategy
classes. These will be combined with the built-in strategies
(overriding them with the instances having the same name).

objclass_def
The name of a supported dictionary-like class to hold JSON data by
default in the merged result. The name must match a built-in name or one
provided in the objclass_menu parameter.

objclass_menu
A dictionary providing additional classes to use as JSON object
containers. The keys are names that can be used as values for the
objectMerge strategy's objClass option or the objclass_def
argument. Each value is a function or class that produces an instance of
the JSON object container. It must support an optional dictionary-like
object as a parameter which initializes its contents.

validatorclass
A jsonschema.Validator subclass. This can be used to specify which
JSON Schema draft version will be used during merge. Some details such
as reference resolution are different between versions. By default, the
Draft 4 validator is used.

Support for keywords that apply subschemas

Complex merging of documents with schemas that use keywords allOf,
anyOf and oneOf can be problematic. Such documents do not have a
well-defined type and might require merging of two values of different
types, which will fail for some strategies. In such cases get_schema()
might also return schemas that never validate.

The overwrite strategy is usually the safest choice for such schemas.

If you explicitly define a merge strategy at the same level as allOf,
anyOf or oneOf keyword, then jsonmerge will use the defined strategy
and not further process any subschemas under those keywords. The
strategy however will descend as usual (e.g. objectMerge will take into
account subschemas under the properties keyword at the same level as
allOf).

If a merge strategy is not explicitly defined and an allOf or anyOf
keyword is present, jsonmerge will raise an error.

If a merge strategy is not explicitly defined and an oneOf keyword is
present, jsonmerge will continue on the branch of oneOf that validates
both base and head. If no branch validates, it will raise an error.

You can define more complex behaviors by defining for your own strategy
that defines what to do in such cases. See docstring documentation for the
Strategy class on how to do that.

Security considerations

A JSON schema document can contain $ref references to external schemas.
jsonmerge resolves URIs in these references using the mechanisms provided
by the jsonschema module. External references can cause HTTP or similar
network requests to be performed.

If jsonmerge is used on untrusted input, this may lead to vulnerabilities
similar to the XML External Entity (XXE) attack.

Requirements

jsonmerge supports Python 2 (2.7) and Python 3 (3.5 and newer).

You need jsonschema (https://pypi.python.org/pypi/jsonschema) module
installed.

Installation

To install the latest jsonmerge release from the Python package index::

pip install jsonmerge

Source

The latest development version is available on GitHub:
https://github.com/avian2/jsonmerge

To install from source, run the following from the top of the source
distribution::

pip install .

jsonmerge uses Tox_ for testing. To run the test suite run::

tox

Troubleshooting

The most common problem with jsonmerge is getting unexpected results from
a merge. Finding the exact reason why jsonmerge produced a particular
result can be complicated, especially when head and base structures are
very large. Most often the cause is a problem with either the schema or
head and base that is passed to jsonmerge, not a bug in jsonmerge
itself.

Here are some tips for debugging issues with jsonmerge:

Try to minimize the problem. Prune branches of head and base structures
that are not relevant to your issue and re-run the merge. Often just
getting a clearer view of the relevant parts exposes the problem.
jsonmerge uses the standard logging_ Python module to print out what
it is doing during the merge. You need to increase verbosity to DEBUG
level to see the messages.
A very common mistake is misunderstanding which part of the schema
applies to which part of the head and base structures. Debug logs
mentioned in the previous point can be very helpful with that, since they
show how merge descends into hierarchies of all involved structures and
when a default strategy is used.
With large head and base it's common that parts of them are not what you
think they are. Validate your inputs against your schema using the
jsonschema library before passing them onto jsonmerge. Make sure your
schema is restrictive enough.
Pay special attention to parts of the schema that use oneOf, anyOf,
allOf keywords. These can sometimes validate in unexpected ways.
Another problem point can be $ref pointers if they can cause recursion.
Using recursive schemas with jsonmerge is fine, but they can often
product unexpected results.

Reporting bugs and contributing code

Thank you for contributing to jsonmerge! Free software wouldn't be
possible without contributions from users like you. However, please consider
that I maintain this project in my free time. Hence I ask you to follow
this simple etiquette to minimize the amount of effort needed to include
your contribution.

Please use GitHub issues_ to report bugs.

Before reporting the bug, please make sure that:

You've read this entire README file.
You've read the Troubleshooting section of the README file.
You've looked at existing issues if the bug has already been reported.

Make sure that your report includes:

A minimal, but complete, code example that reproduces the problem,
including any JSON data required to run it. It should be something I can
copy-paste into a .py file and run.
Relevant versions of jsonmerge and jsonschema - either release number
on PyPi or the git commit hash.
Copy of the traceback, in case you are reporting an unhandled exception.
Example of what you think should be the correct output, in case you are
reporting wrong result of a merge or schema generation.

Please use GitHub pull requests_ to contribute code. Make sure that your
pull request:

Passes all existing tests and includes new tests that cover added code.
Updates README.rst to document added functionality.

License

Copyright 2023, Tomaz Solc tomaz.solc@tablix.org

The MIT License (MIT)

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.

.. _JSON schema: http://json-schema.org
.. _Draft 4: http://json-schema.org/specification-links.html#draft-4
.. _Tox: https://tox.readthedocs.io/en/latest/
.. _GitHub issues: https://github.com/avian2/jsonmerge/issues
.. _GitHub pull requests: https://github.com/avian2/jsonmerge/pulls
.. _logging: https://docs.python.org/3/library/logging.html

..
vim: tw=75 ts=4 sw=4 expandtab softtabstop=4

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