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More human readable JSON serializer/de-serializer for MongoEngine

Project description

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What This?

This script has MongoEngine Document json serialization more-natural.

Why this invented?

Using MongoEngine to create something (e.g. RESTful API), sometimes you might want to serialize the data from the db into JSON, but some fields are weird and not suitable for frontend/api:

{
  "_id": {
    "$oid": "5700c32a1cbd5856815051ce"
  },
  "name": "Hiroaki Yamamoto",
  "registered_date": {
      "$date": 1459667811724
  }
}

The points are 2 points:

  • _id might not be wanted because jslint disagrees _ character unless declaring jslint nomen:true
  • There are sub-fields such $oid and $date. These fields are known as MongoDB Extended JSON. However, considering MongoEngine is ODM and therefore it has schema-definition methods, the fields shouldn’t have the special fields. In particular problems, you might get No such property $oid of undefined error when you handle above generated data on frontend.

To solve the problems, the generated data should be like this:

{
  "id": "5700c32a1cbd5856815051ce",
  "name": "Hiroaki Yamamoto",
  "registered_date": 1459667811724
}

Making above structure can be possible by doing re-mapping, but if we do it on API’s controller object, the code might get super-dirty:

"""Dirty code."""
import mongoengine as db


class User(db.Document):
  """User class."""
  name = db.StringField(required=True, unique=True)
  registered_date = db.DateTimeField()


def get_user(self):
  """Get user."""
  models = [
    {
      ("id" if key == "_id" else key): (
        value.pop("$oid") if "$oid" in value and isinstance(value, dict)
        else value.pop("$date") if "$date" in value and isinstance(value, dict)
        else value  #What if there are the special fields in child dict?
      )
      for (key, value) in doc.items()
    } for doc in User.objects(pk=ObjectId("5700c32a1cbd5856815051ce"))
  ]
  return json.dumps(models, indent=2)

To give the solution of this problem, I developed this scirpt. By using this script, you will not need to make the transform like above. i.e.

"""A little-bit clean code."""

import mongoengine as db
import mongoengine_goodjson as gj


class User(gj.Document):
  """User class."""
  name = db.StringField(required=True, unique=True)
  registered_date = db.DateTimeField()


def get_user(self):
  """Get user."""
  return model_cls.objects(
    pk=ObjectId("5700c32a1cbd5856815051ce")
  ).to_json(indent=2)

How to use it

Generally you can define the document as usual, but you might want to inherits mongoengnie_goodjson.Document or mongoengnie_goodjson.EmbeddedDocument.

Here is the example:

"""Example schema."""

import mongoengine_goodjson as gj
import mongoengine as db


class Address(gj.EmbeddedDocument):
    """Address schema."""

    street = db.StringField()
    city = db.StringField()
    state = db.StringField()


class User(gj.Document):
    """User data schema."""

    name = db.StringField()
    email = db.EmailField()
    address = db.EmbeddedDocumentListField(Address)

Feature: Follow Reference

Adding documents with ReferenceField, the fields are serialized as ObjectId by default:

model.py

import mongoengine as db
import mongoengine_goodjson as gj


class Book(gj.Document):
  """Book information model."""

  name = db.StringField(required=True)
  isbn = db.StringField(required=True)
  author = db.StringField(required=True)
  publisher = db.StringField(required=True)
  publish_date = db.DateTimeField(required=True)


class User(gj.Document):
  firstname = db.StringField(required=True)
  lastname = db.StringField(required=True)
  books_bought = db.ListField(db.ReferenceField(Book))
  favorite_one = db.ReferenceField(Book)

The example of generated output

{
  "id": "570ee9d1fec55e755db82129",
  "firstname": "James",
  "lastname": "Smith",
  "books_bought": [
    "570eea0afec55e755db8212a",
    "570eea0bfec55e755db8212b",
    "570eea0bfec55e755db8212c"
  ],
  "favorite_one": "570eea0bfec55e755db8212b"
}

This seems to be good deal for Reference Field, but sometimes you might want to generate the Document with Referenced Document like Embedded Document:

{
  "id": "570ee9d1fec55e755db82129",
  "firstname": "James",
  "lastname": "Smith",
  "books_bought": [
    {
      "id": "570eea0afec55e755db8212a",
      "name": "ドグラ・マグラ (上)",
      "author": "夢野 久作",
      "publisher": "角川文庫",
      "publish_date": "1976-10-01",
      "isbn": "978-4041366035"
    },
    {
      "id": "570eea0bfec55e755db8212b",
      "name": "ドグラ・マグラ (下)",
      "author": "夢野 久作",
      "publisher": "角川文庫",
      "publish_date": "1976-10-01",
      "isbn": "978-4041366042"
    },
    {
      "id": "570eea0bfec55e755db8212c",
      "name": "The Voynich Manuscript: Full Color Photographic Edition",
      "author": "Unknown",
      "publisher": "FQ Publishing",
      "publish_date": "2015-01-17",
      "isbn": "978-1599865553"
    }
  ],
  "favorite_one": {
    "id": "570eea0bfec55e755db8212b",
    "name": "ドグラ・マグラ (下)",
    "author": "夢野 久作",
    "publisher": "角川文庫",
    "publish_date": "1976-10-01",
    "isbn": "978-4041366042"
  }
}

Making this format can be done by making Document.objects query for each reference. However, doing it, the code would be also dirty:

def output_references():
  user = User.objects(pk=ObjectId("570ee9d1fec55e755db82129")).get()
  user_dct = json.loads(user.to_json())
  user_dct["books"] = [
    json.loads(book.to_json()) for book in user.books_bought
  ]
  user_dct["favorite_one"] = json.loads(user.favorite_one.to_json())
  return jsonify(user_dct)
  # ...And what if there are references in the referenced document??

To avoid this annoying problem, this script has new function called Follow Reference since 0.9. To use it, you can just set follow_reference=True on serialization:

def output_references():
  user = User.objects(pk=ObjectId("570ee9d1fec55e755db82129")).get()
  return jsonify(json.loads(user.to_json(follow_reference=True)))

Note that setting follow_reference=True, Document.to_json checks the reference recursively until the depth is reached 3rd depth. To change the maximum recursion depth, you can set the value you want to max_depth:

def output_references():
  user = User.objects(pk=ObjectId("570ee9d1fec55e755db82129")).get()
  return jsonify(json.loads(user.to_json(follow_reference=True, max_depth=5)))

Feature: FollowReferenceField

This script also provides a field that supports serialization of the reference with follow_reference=True. Unlike ReferenceField, this field supports deserialization and automatic-save.

To use this field, you can just simply declare the field as usual. For example, like this:

import mongoengine as db
import mongoengine_goodjson as gj


class User(gj.Document):
  """User info."""
  name = db.StringField()
  email = db.EmailField()

class DetailedProfile(gj.Document):
  """Detail profile of the user."""
  # FollowReferenceField without auto-save
  user = gj.FollowReferenceField(User)
  yob = db.DateTimeField()
  # FollowReferenceField with auto-save
  partner = gj.FollowReferenceField(User, autosave=True)

Important Note when use FollowReferenceField

Currently, FollowReferenceField doesn’t support the limit of recursion. Therefore, don’t implement self-reference document and/or loop-reference document.

Feature 2: Exclude fields from JSON serialization/deserialization

Sometimes you might want to exclude fields from JSON serialization, but to do so, you might need to decode JSON-serialized string, pop the key, then, serialize the dict object again. Since 0.11, metadata exclude_to_json, exclude_from_json, and exclude_json are available and they behave like the following:

  • Setting Truthy value to exclude_to_json, the corresponding field is omitted from JSON encoding. Note that this excludes fields JSON encoding only.
  • Setting Truthy value to exclude_from_json, the corresponding field is omitted from JSON decoding. Note that this excludes fields JSON decoding only.
  • Setting Truhy value to exclude_json, the corresponding field is omitted from JSON encoding and decoding.

Example

To use the exclusion, you can just put exclude metadata like this:

import mongoengine_goodjson as gj
import mongoengine as db


class ExclusionModel(gj.Document):
    """Example Model."""
    to_json_exclude = db.StringField(exclude_to_json=True)
    from_json_exclude = db.IntField(exclude_from_json=True)
    json_exclude = db.StringField(exclude_json=True)
    required = db.StringField(required=True)


def get_json_obj(*q, **query):
    model = Exclude.objects(*q, **query).get()
    # Just simply call to_json :)
    return model.to_json()


def get_json_list(*q, **query):
    # You can also get JSON serialized text from QuerySet.
    return Exclude.objects(*q, **query).to_json()


# Decoding is also simple.
def get_obj_from_json(json_text):
  return Exclude.from_json(json_text)


def get_list_from_json(json_text):
  return Exclude.objects.from_json(json_text)

Not implemented list

The following types are partially implemented because there aren’t any corresponding fields on MongoEngine:

Type Encoder Decoder
Regex
white_check_mark:
 
x:
MinKey
white_check_mark:
 
x:
MaxKey
white_check_mark:
 
x:
TimeStamp
white_check_mark:
 
x:
Code
white_check_mark:
 
x:

The following document types are not implemented yet:

  • DynamicDocument
  • DynamicEmbeddedDocument
  • MapReduceDocument

Btw I don’t think above documents implementations are needed because they can be handled by using multiple-inheritance. If you couldn’t do it, post issue or PR.

FollowReference Decoder

[STRIKEOUT:Since 0.9, this script supports Follow Reference, but it doesn’t support decoder. Passing “followed reference” dict to ReferenceField, it recognized id field only. This behavior will be fixed at 0.10.] Use FollowReferenceField.

Contribute

This scirpt is coded on TDD. i.e. Writing a test that fails, and then write the actual code to pass the test. Therefore, virtualenv, nose and tox will be needed to code this script. In addtion, you will need to have MongoDB installed and it must be running on the computer to run the tests.

In addition, you can use gulp to watch the file changes.

License (MIT License)

Copyright (c) 2016 Hiroaki Yamamoto

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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