A simple wrapper to make a flat file drop in raplacement for mongodb out of TinyDB

Overview

Gitpod Ready-to-Code

logo

Build Status

Purpose

A simple wrapper to make a drop in replacement for mongodb out of tinydb. This module is an attempt to add an interface familiar to those currently using pymongo.

Status

Unit testing is currently being worked on and functionality is being added to the library. Current coverage is 93%. Current builds tested on Python versions 2.7 and 3.3+.

Installation

The latest stable release can be installed via pip install tinymongo.

The library is currently under rapid development and a more recent version may be desired.

In this case, simply clone this repository, navigate to the root project directory, and pip install -e .

or use pip install -e git+https://github.com/schapman1974/tinymongo.git#egg=tinymongo

This is a pure python distribution and - thus - should require no external compilers or tools besides those contained within Python itself.

Examples

The quick start is shown below. For a more detailed look at tinymongo, take a look at demo.py within the repository.

    from tinymongo import TinyMongoClient

    # you can include a folder name or absolute path
    # as a parameter if not it will default to "tinydb"
    connection = TinyMongoClient()

    # either creates a new database file or accesses an existing one named `my_tiny_database`
    db = connection.my_tiny_database

    # either creates a new collection or accesses an existing one named `users`
    collection = db.users

    # insert data adds a new record returns _id
    record_id = collection.insert_one({"username": "admin", "password": "admin", "module":"somemodule"}).inserted_id
    user_info = collection.find_one({"_id": record_id})  # returns the record inserted

    # you can also use it directly
    db.users.insert_one({"username": "admin"})

    # returns a list of all users of 'module'
    users = db.users.find({'module': 'module'})

    #update data returns True if successful and False if unsuccessful
    upd = db.users.update_one({"username": "admin"}, {"$set": {"module":"someothermodule"}})

    # Sorting users by its username DESC
    # omitting `filter` returns all records
    db.users.find(sort=[('username', -1)])

    # Pagination of the results
    # Getting the first 20 records
    db.users.find(sort=[('username', -1)], skip=0, limit=20)
    # Getting next 20 records
    db.users.find(sort=[('username', -1)], skip=20, limit=20)

    # Getting the total of records
    db.users.count()

Custom Storages and Serializers

HINT: Learn more about TinyDB storages and Serializers in documentation

Custom Storages

You have to subclass TinyMongoClient and provide custom storages like CachingMiddleware or other available TinyDB Extension.

Caching Middleware

    from tinymongo import TinyMongoClient
    from tinydb.storages import JSONStorage
    from tinydb.middlewares import CachingMiddleware

    class CachedClient(TinyMongoClient):
        """This client has cache"""
        @property
        def _storage(self):
            return CachingMiddleware(JSONStorage)

    connection = CachedClient('/path/to/folder')

HINT: You can nest middlewares: FirstMiddleware(SecondMiddleware(JSONStorage))

Serializers

To convert your data to a format that is writable to disk TinyDB uses the Python JSON module by default. It's great when only simple data types are involved but it cannot handle more complex data types like custom classes.

To support serialization of complex types you can write your own serializers using the tinydb-serialization extension.

First you need to install it pip install tinydb-serialization

Handling datetime objects

You can create a serializer for the python datetime using the following snippet:

    from datetime import datetime
    from tinydb_serialization import Serializer

    class DatetimeSerializer(Serializer):
        OBJ_CLASS = datetime

        def __init__(self, format='%Y-%m-%dT%H:%M:%S', *args, **kwargs):
            super(DatetimeSerializer, self).__init__(*args, **kwargs)
            self._format = format

        def encode(self, obj):
            return obj.strftime(self._format)

        def decode(self, s):
            return datetime.strptime(s, self._format)

NOTE: this serializer is available in tinymongo.serializers.DateTimeSerializer

Now you have to subclass TinyMongoClient and provide customs storage.

    from tinymongo import TinyMongoClient
    from tinymongo.serializers import DateTimeSerializer
    from tinydb_serialization import SerializationMiddleware


    class CustomClient(TinyMongoClient):
        @property
        def _storage(self):
            serialization = SerializationMiddleware()
            serialization.register_serializer(DateTimeSerializer(), 'TinyDate')
            # register other custom serializers
            return serialization


    connection = CustomClient('/path/to/folder')

Flask-Admin

This extension can work with Flask-Admin which gives a web based administrative panel to your TinyDB. Flask-Admin has features like filtering, search, web forms to perform CRUD (Create, Read, Update, Delete) of the TinyDB records.

You can find the example of Flask-Admin with TinyMongo in Flask-Admin Examples Repository

NOTE: To use Flask-Admin you need to register a DateTimeSerialization as showed in the previous topic.

Contributions

Contributions are welcome! Currently, the most valuable contributions would be:

  • adding test cases
  • adding functionality consistent with pymongo
  • documentation
  • identifying bugs and issues

Future Development

I will also be adding support for gridFS by storing the files somehow and indexing them in a db like mongo currently does

More to come......

License

MIT License

This repository is for active development of the Azure SDK for Python.

Azure SDK for Python This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public

Microsoft Azure 3.4k Jan 02, 2023
Neo4j Bolt driver for Python

Neo4j Bolt Driver for Python This repository contains the official Neo4j driver for Python. Each driver release (from 4.0 upwards) is built specifical

Neo4j 762 Dec 30, 2022
The Database Toolkit for Python

SQLAlchemy The Python SQL Toolkit and Object Relational Mapper Introduction SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that giv

SQLAlchemy 6.5k Jan 01, 2023
Python DBAPI simplified

Facata A Python library that provides a simplified alternative to DBAPI 2. It provides a facade in front of DBAPI 2 drivers. Table of Contents Install

Tony Locke 44 Nov 17, 2021
SQL queries to collections

SQC SQL Queries to Collections Examples from sqc import sqc data = [ {"a": 1, "b": 1}, {"a": 2, "b": 1}, {"a": 3, "b": 2}, ] Simple filte

Alexander Volkovsky 0 Jul 06, 2022
Toolkit for storing files and attachments in web applications

DEPOT - File Storage Made Easy DEPOT is a framework for easily storing and serving files in web applications on Python2.6+ and Python3.2+. DEPOT suppo

Alessandro Molina 139 Dec 25, 2022
A simple wrapper to make a flat file drop in raplacement for mongodb out of TinyDB

Purpose A simple wrapper to make a drop in replacement for mongodb out of tinydb. This module is an attempt to add an interface familiar to those curr

180 Jan 01, 2023
Asynchronous Python client for InfluxDB

aioinflux Asynchronous Python client for InfluxDB. Built on top of aiohttp and asyncio. Aioinflux is an alternative to the official InfluxDB Python cl

Gustavo Bezerra 159 Dec 27, 2022
Generate database table diagram from SQL data definition.

sql2diagram Generate database table diagram from SQL data definition. e.g. "CREATE TABLE ..." See Example below How does it works? Analyze the SQL to

django-cas-ng 1 Feb 08, 2022
Monty, Mongo tinified. MongoDB implemented in Python !

Monty, Mongo tinified. MongoDB implemented in Python ! Inspired by TinyDB and it's extension TinyMongo. MontyDB is: A tiny version of MongoDB, against

David Lai 522 Jan 01, 2023
Redis Python Client

redis-py The Python interface to the Redis key-value store. Python 2 Compatibility Note redis-py 3.5.x will be the last version of redis-py that suppo

Andy McCurdy 11k Dec 29, 2022
A database migrations tool for SQLAlchemy.

Alembic is a database migrations tool written by the author of SQLAlchemy. A migrations tool offers the following functionality: Can emit ALTER statem

SQLAlchemy 1.7k Jan 01, 2023
High level Python client for Elasticsearch

Elasticsearch DSL Elasticsearch DSL is a high-level library whose aim is to help with writing and running queries against Elasticsearch. It is built o

elastic 3.6k Jan 03, 2023
A HugSQL-inspired database library for Python

PugSQL PugSQL is a simple Python interface for using parameterized SQL, in files. See pugsql.org for the documentation. To install: pip install pugsql

Dan McKinley 558 Dec 24, 2022
Async ORM based on PyPika

PyPika-ORM - ORM for PyPika SQL Query Builder The package gives you ORM for PyPika with asycio support for a range of databases (SQLite, PostgreSQL, M

Kirill Klenov 7 Jun 04, 2022
Sample scripts to show extracting details directly from the AIQUM database

Sample scripts to show extracting details directly from the AIQUM database

1 Nov 19, 2021
A library for python made by me,to make the use of MySQL easier and more pythonic

my_ezql A library for python made by me,to make the use of MySQL easier and more pythonic This library was made by Tony Hasson , a 25 year old student

3 Nov 19, 2021
Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

AWS Data Wrangler Pandas on AWS Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretMana

Amazon Web Services - Labs 3.3k Dec 31, 2022
A Python Object-Document-Mapper for working with MongoDB

MongoEngine Info: MongoEngine is an ORM-like layer on top of PyMongo. Repository: https://github.com/MongoEngine/mongoengine Author: Harry Marr (http:

MongoEngine 3.9k Jan 08, 2023
Databank is an easy-to-use Python library for making raw SQL queries in a multi-threaded environment.

Databank Databank is an easy-to-use Python library for making raw SQL queries in a multi-threaded environment. No ORM, no frills. Thread-safe. Only ra

snapADDY GmbH 4 Apr 04, 2022