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MongoNow is the equivalent of sqlite for MongoDB. It's a local in-memory mongo-like database.

Project description

Are you unsatisfied of working with mock data in dev environment ?

MongoNow is here to help.

Do you wonder if there is a quick way of setting up a dummy MongoDB instance in less that seconds?

With MongoNow, all your problems have finally found a solution. Install MongoNow with pip or git and your Mongo-like database is ready to be used in seconds.


Install the MongoNow package with python-pip or clone it from github.

Install using pip:

$ pip install mongonow

Install using git:

$ git clone


  • Create a MongoNowClient instance and start exploring its content:
from mongonow import MongoNowClient

# Create a MongoNowClient specifying the path of your databases.
client = MongoNowClient(path='/dbs')
# Select one of your database
db = client['test_db']
# Select a collection
cheese_collection = db['cheese']
  • Perform a query on your collection with the same syntax you would use for MongoDB:
# SELECT all FROM cheese documents WHERE price is less than 4.99 AND country is France
>>> cheese_collection.find({
....    '$and': [
....        {'$lt': {'price': '4.99'}},
....        {'$eq': {'country': 'France'}} # or {'country: 'France'} without $eq
....    ]
.... })

        "_id": 5590198231212309,
        "name": "Camembert",
        "price": 2.99,
        "country": "France"
        "_id": 5512398091283234,
        "name": "Maroilles",
        "price": 4.49,
        "country": "France"
  • Mutate several documents
# Set field discounted to True for all french cheese
    {"country": "France"},
    {"discounted": True}

File Structure

The structure of the local database should be conform to the MongoNow's file structure Specification.

  • The Database Container (e.g. dbs/) containing all databases. The path of this folder has to be specified during MongoNowClient instanciation: client = MongoNowClient(path='/dbs')
  • Database folders (e.g. test_db/) containing all its collection. Navigate to this database with db = client['test_db'].
  • Collection files (e.g. cheese.json): Navigate to this collection with coll = db['cheese'].
└── dbs/
    ├── dev_db/
    │   └── ...
    └── test_db/
        ├── users.json
        │   └── ...
        └── cheese.json
            └── {
                  "cheese": [
                      "_id": 5590198231212309,
                      "name": "Camembert",
                      "price": 2.99,
                      "country": "France"
                      "_id": 5512398091283234,
                      "name": "Maroilles",
                      "price": 4.49,
                      "country": "France"

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