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 currently supports 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 }
... }
... }
... }
>>> from jsonmerge import Merger
>>> merger = Merger(schema)
>>> v1 = {
... 'foo': {
... 'greeting': 'Hello, World!'
... }
... }
>>> v2 = {
... 'foo': {
... 'greeting': 'Howdy, World!'
... }
... }
>>> base = None
>>> base = merger.merge(base, v1, meta={'version': 1})
>>> base = merger.merge(base, v2, meta={'version': 2})
>>> pprint(base, width=55)
{'foo': [{'value': {'greeting': 'Hello, World!'},
'version': 1},
{'value': {'greeting': 'Howdy, World!'},
'version': 2}]}
Note that we use the mergeOptions keyword 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 meta argument to supply some document meta-data that is included for each version of the field. meta 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.
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)
{'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.
- 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.
- 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 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 stategy 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:
- 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.
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 stragegy 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 (3.2 and newer).
You need jsonschema (https://pypi-hypernode.com/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 and run the test suite:
python setup.py install python setup.py test
License
Copyright 2018, 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.
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