essentialdb 0.3.10

EssentialDB - NOSQL document database.

Welcome to EssentialDB

=======================



A Fast Embedded Database in Python.



Use case: You want to prototype an idea wihtout a heavyweight database install. If the idea works out though, you don't want

to rewrite all of your data access code.



EssentialDB helps solve that problem by being (nearly) api compatible with MongoDB. That way when your idea starts to grow,

you can switch to MongoDB to scale.



* Syntax and semantics are very similar to MongoDB, lowering the barrier of entry.

* Fairly complex query support.

* Its in pure python.

* Its very fast.



`Project On GitHub <https://github.com/shane-mason/essentialdb>`_ |

`Full Docs @ ReadTheDocs <http://essentialdb.readthedocs.io/en/latest/>`_ |

`Distribution On Pypi <https://pypi.python.org/pypi/essentialdb>`_



Current Status

---------------

Just getting started!



Quickstart

-----------



Install with pip::



pip install essentialdb





Basic usage is straightforward::



from essentialdb import EssentialDB



author_db = EssentialDB(filepath="authors.db")



author_db.insert_one({'first': 'Langston', 'last': 'Hughes', 'born': 1902});



results = author_db.find({'last':'Hughes'})



author_db.sync()



Or using the 'with' semantics to assure that write happen without having to explicitly call sync::



with EssentialDB(filepath="authors.db") as author_db:

author_db.insert_one({'first': 'Langston', 'last': 'Hughes', 'born': 1902});





Insert a document::



author = {'first': 'Langston', 'last': 'Hughes', 'born': 1902}

author_db.insert_one(author)



Insert many documents::



authors = [{'first': 'Langston', 'last': 'Hughes', 'born': 1902},

{'first': 'Ezra', 'last': 'Pound', 'born': 1885}]

author_db.insert_many(authors)



Find one document::



document = author_db.find_one({'first': 'Ezra', 'last': 'Pound'})



Find many::



documents = author_db.find({'born': {'$gt': 1900}})



Update one::



updated = author_db.update({'_id': {'$eq': "A345i"}}, {'born': 1902})



Update many::



updated = author_db.update({'born': {'$gt': 1900}}, {'period': 'Modern'})



Remove Items::



removed = author_db.remove({'period':'Modern'))



Nested Queries::



customer_db.insert_one({'first': 'John', 'last': 'Smith', 'address': { 'street': '10 Maple St', 'city': 'Missoula', 'state': 'MT'}})

results = customer_db.find({'address.state':'MT'})



Note that nested query support means that key names can not include a period.



Write updates to disk::



author_db.sync()



Queries

--------



Queries in EssentialDB follow the same basic form as MongoDB::



{ <field1>: { <operator1>: <value1> }, ... }





Comparison Query Selectors

^^^^^^^^^^^^^^^^^^^^^^^^^^^



The $eq operator matches documents where the value of a field equals the specified value::



author_db.find({"born" : {"$eq": 1972}})



The $ne operator matches documents where the value of a field is not equal to the specified value::



author_db.find({"born" : {"$ne": 1972}})



The $gt operator matches documents where the value of a field is greater than the specified value::



author_db.find({"born" : {"$gt": 1900}})



The $gte operator matches documents where the value of a field is great than or equal to the specified value::



author_db.find({"born" : {"$gte": 1900}})



The $lt operator matches documents where the value of a field is less than the specified value::



author_db.find({"born" : {"$lt": 1900}})





The $lte operator matches documents where the value of a field is less than or equal to the specified value::



author_db.find({"born" : {"$lte": 1900}})



The $in operator matches documents where the value of a field is equal any item in the specified array::



author_db.find({"genre" : {"$in": ["tragedy", "drama"]}})



The $nin operator matches documents where the value of a field is not equal to any item in the specified array::



author_db.find({"genre" : {"$nin": ["tragedy", "drama"]}})





Boolean Operators

^^^^^^^^^^^^^^^^^

The $and operator matches documents where all the fields match::



author_db.find({'$and':[{'born': {'$gte': 1900}},{'born': {'$lt': 2000}}]})



The $or operator matches documents where any of the fields match::



author_db.find({'$or':[{'first': {'$eg': 'John'}},{'last': {'$eq': 'John'}}]})



The $nor operator matches document where none of the conditions match::



author_db.find({"$nor":[{'first': {"$eq": 'John'}},{'last': {'$eq': 'John'}}]})






Keywords: database nosql
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6