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Merge a series of JSON documents.

Project description

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


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 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.


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.


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.


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).


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):


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.


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).


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.


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.


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.


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

You need jsonschema ( module installed.


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

pip install jsonmerge


The latest development version is available on GitHub:

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:



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.


Copyright 2023, Tomaz Solc <>

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.


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