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Awesome PyMongo Awesome

Welcome to the comprehensive PyMongo tutorial repository! This guide is designed to help you master the art of working with MongoDB, using the official Python driver, PyMongo.

Inspired by awesome-python.

Introduction to MongoDB and PyMongo

What is MongoDB?

MongoDB is a popular open-source NoSQL database management system. It is designed to be flexible, scalable, and high-performance, making it well-suited for modern web applications and data-intensive workloads. Unlike traditional relational databases, MongoDB stores data in flexible, JSON-like documents, allowing for dynamic and unstructured data models. This makes it a popular choice for developers working with rapidly changing application requirements.

What is PyMongo?

PyMongo is the official Python driver for MongoDB, the popular NoSQL database. It provides a high-level API for interacting with MongoDB databases from within a Python application. PyMongo allows developers to perform various database operations such as inserting, querying, updating, and deleting data, as well as managing database connections and configurations.

Key Features of PyMongo

  1. Easy Integration: PyMongo seamlessly integrates with the Python programming language, allowing developers to leverage the full power of MongoDB within their Python applications.

  2. Comprehensive API: The PyMongo API provides a wide range of methods and functions for performing common database operations, making it easy to interact with MongoDB databases.

  3. Connection Management: PyMongo handles the complexities of managing database connections, including connection pooling and automatic reconnection, allowing developers to focus on their application logic.

  4. Query Optimization: PyMongo optimizes database queries by automatically converting Python data structures into the appropriate MongoDB query formats, ensuring efficient data retrieval.

  5. Data Mapping: PyMongo provides a flexible data mapping system that allows developers to map Python objects to MongoDB documents, simplifying the process of working with complex data structures.

  6. GridFS Support: PyMongo includes support for GridFS, a specification for storing and retrieving large files (such as images, videos, or other binary data) in MongoDB.

  7. Asynchronous Support: PyMongo supports asynchronous programming using the asyncio and motor libraries, enabling developers to build high-performance, scalable applications.

Installation

Installing MongoDB

  1. Download and install MongoDB from the official website: MongoDB Installation Guide
  2. Ensure that Mon is running on your system.

Installing PyMongo

You can install it simply by using pip:

pip install pymongo

Working in virtual environment is recommended

$ cd <path to your file>
$ python -m venv .env

Now your virtual environment is ready with the name .env. Let's activate the virtual-env & then start coding:

source .env/bin/activate

Connecting to MongoDB

First import pymongo,

from pymongo import MongoClient

Connecting client:

client = MongoClient('localhost', 27017)
print(client)

# OR you can use URL format like,

client = MongoClient('mongodb://localhost:27017/')
print(client)

Now if you run the code, the output will be like this,

>>> MongoClient(host=['localhost:27017'], document_class=dict, tz_aware=False, connect=True)

Congrats 🎉, you have passed the first chapter.

Accessing Database and Collection

The way to Creating and Opening existing Database and Collection are the same. If the given database or collection name matches with an existing one then it will open it. Otherwise, it will create a new database with the same name.

But still, there are slight differences.

If you are creating a new database or collection then you have to insert a document into them. Otherwise, a database or collection will not be created.

Database

# for opening or creating a database
db = client['test-database']

Collection

# for opening or creating collection
collection = db['test-collection']

NOTE: You have to give collection name in the defined database; here 'db'

Inserting

Now you have to insert a document into the collection if you are creating a new one as mentioned before,

# First arrange the values in a dictionary
my_dict = {"name": "HONEY", "language": "Python", "Platform": "GitHub"}

Here I am using insert_one function to insert the values. Another function to insert the value I will explain in next step.

# insert the value containing dictionary
collection.insert_one(my_dict)  # Using "insert_one" function

Inserting Document

Now we will learn how to insert a document into a collection of any database. PyMongo has two methods to insert documents:

  • insert_one (for inserting only one document)
  • insert_many (for inserting multiple documents at once)

  1. Insert One

    First, we need to arrange the values into a dictionary; for example:

    # our sample dictionary
my_dict = {"name": "HONEY", "language": "Python", "Platform": "GitHub"}

# Using "insert_one" function
collection.insert_one(my_dict)  # inserting a file in collection ( here our "my_dict" dictionary )

  2. Insert Many

    For this, put multiple dictionaries into a list, like this:

    files = [
    {'name':'A', "language": "Java", "Platform": "Git"},
    {'name':'B', "language": "Java", "Platform": "GitHub"},
    {"name":"C", "language": "Python", "Platform": "GitHub"}
]
# using insert_many function
collection.insert_many(files) # inserting the data

Document ID

MongoDB sets a document id for every document by itself in the database to manage them. But you can also give your custom document id (But it should be unique). To do so just add '_id' key and its value in the dictionary: { '_id':'CustomID' }

my_dict = {
    "_id":"customID",
    "name":"D", 
    "language": "Javascript", 
    "Platform": "Git"
    }

# NOTE: "_id":"customID"

Now we can just insert it into the collection as mentioned earlier.

Find Document In Database

PyMongo has a function called find_one() to find any document in the database. find_one() returns only one document. It doesn't have any function to find multiple documents at the same time. You have to use for loop for it.

  1. Finding random document

    doc = collection.find_one()
print(doc)

  2. Finding Specific document

    _filter = {'name':'A'}  # filter
doc = collection.find_one(_filter)
print(doc)

  3. Counting the no. of documents matching the filter

    _filter = {"language": "Python"}
# counting the number of document/s of matching the filter
count = collection.count_documents(_filter)
print(count)

Getting Specific Data

When we import data from a database then we may want to get only the required data, not all data from documents. For that, we have to show only the required data and have to hide other things. We can do this by using PyMongo.

If we want to hide some Key's value, then we can do this just by adding a second argument containing keys in a dictionary.

There, the key's value will be 0 or 1
0 👉 it not will print
1 👉 it will print

_If we make the specific key or keys 1, then others key automatically become 0, but not _id key

Example:

import pymongo

# Connecting client
client = pymongo.MongoClient("mongodb://localhost:27017")
db = client['test-database']  # Database
collection = db['test-collection']  # Collection


# Finding Specific document using filter
_filter = {'name':'A'}

# Showing only specific keys
one = collection.find_one(_filter, {'name':1})
# NOTE: here only '_id' & 'name' key will show

two = collection.find_one(_filter, {'name':1, '_id':0})
# Here only 'name' will show

print(one)
print(two)

From the above example, we can see that we have to make _id key 0. Because it doesn't become 0 by default.

Showing Databases and Collections

Anytime we may need to check the list of created databases and collections. Luckily, PyMongo has the functionality to do it.

  1. Databases

    # For listing all Databases
AllDatabases = client.list_database_names()
print(AllDatabases)

  2. Collections

    First select the database and then,

    db = client['test-database']  # selected database

# For listing all collections
AllCollections = db.list_collection_names()
print(AllCollections)

Updating Document

When we are working with a database then, we have to update documents with time. Here we can do that using PyMongo.

Pymongo have functions that update documents,

  • update_one(),
  • update_many()

Here also we have to arrange updated values into a dictionary. But here you have to put this dictionary into another dictionary of key "$set". Like: {"$set": {"key": "updated value"}}

  1. Update One

    Example:

    # Changing A's language to Python (Previously it was Java)
filter = {"name": "A"}  # creating a filter
updated_values = {"$set":{"language": "Python"}}

collection.update_one(filter, updated_values)  # Updating

  2. Update Many

    It changes every document's value which matches the filter

    Example:

    # Changing everyone's language to Python, whose Platform is GitHub

_filter = {"Platform": "GitHub"}  # filter
updated_values = {"$set":{"age":18}}

up = collection.update_many(_filter, updated_values)  # Updating

    For counting the number of documents updated

    print(up.modified_count)

Deleting Document

For deleting documents also there are two functions:

  • delete_one() 👉 for deleting one document
  • delete_many() 👉 for deleting multiple documents

  1. Delete One

    _filter = {"name":"A"}  # filter
collection.delete_one(_filter)  # deleting

  2. Delete Many

    It deletes all documents that match the filter.

    filter_2 = {"Platform": "Git"}  # filter
dle = collection.delete_many(filter_2)  # deleting

    For counting the number of documents deleted

    print(dle.deleted_count)