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MongoDB with Pymongo Tutorial
https://github.com/ruanbekker/mongodb-with-python-tutorial
mongodb mongodb-tutorial nosql nosql-database pymongo python
Last synced: 4 days ago
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MongoDB with Pymongo Tutorial
Host: GitHub
URL: https://github.com/ruanbekker/mongodb-with-python-tutorial
Owner: ruanbekker
Created: 2019-04-09T21:46:02.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2024-04-19T08:21:02.000Z (7 months ago)
Last Synced: 2024-04-19T09:32:09.843Z (7 months ago)
Topics: mongodb, mongodb-tutorial, nosql, nosql-database, pymongo, python
Size: 43.9 KB
Stars: 10
Watchers: 3
Forks: 5
Open Issues: 0
Metadata Files:
- Readme: README.md
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README

        # mongodb-with-python-tutorial

MongoDB with Pymongo Tutorial

### MongoDB Server

Run a mongodb server with docker:

```

$ docker run --rm -itd --name mongodb -e MONGO_INITDB_ROOT_USERNAME=root -e MONGO_INITDB_ROOT_PASSWORD=password -p 27017:27017 mongo:4.4

```

### Python Package

Install the python package to interact with mongodb using python:

```

$ pip install pymongo

```

### Making a Connection

Making a connection without authentication:

```

>>> from pymongo import MongoClient

>>> uri = 'mongodb://localhost:27017/'

>>> client = MongoClient(uri)

>>> client.list_database_names()

['admin', 'config', 'local']

```

Making a connection with authentication:

```

>>> from pymongo import MongoClient

>>> uri = 'mongodb://root:password@localhost:27017/admin?authSource=admin&authMechanism=SCRAM-SHA-1'

>>> client = MongoClient(uri)

>>> client.list_database_names()

['admin', 'config', 'local']

```

### Listing Databases

```

>>> client.list_database_names()

['admin', 'config', 'local']

```

### Listing Collections

```

>>> db = client.config

>>> db.list_collection_names()

['system.sessions']

```

### Write One Document 

Create a database `store_db`, use the `transactions` collection and write a document to it.

```

>>> db = client.store_db

>>> transactions = db.transactions

>>> doc_data = {

    'store_name': 'sportsmans', 

    'branch_name': 'tygervalley', 

    'account_id': 'sns_03821023', 

    'total_costs': 109.20, 

    'products_purchased': ['cricket bat', 'cricket ball', 'sports hat'], 

    'purchase_method': 

    'credit card'

}

>>> response = transactions.insert_one(doc_data)

>>> response.inserted_id

ObjectId('5cad16a5a5f3826f6f046d74')

```

We can verify that the collection is present:

```

>>> db.list_collection_names()

['transactions']

```

### Write Many Documents

We can batch up our writes:

```

>>> transaction_1 = {

    'store_name': 'sportsmans', 'branch_name': 'tygervalley', 

    'account_id': 'sns_09121024', 'total_costs': 129.84, 

    'products_purchased': ['sportsdrink', 'sunglasses', 'sports illustrated'], 

    'purchase_method': 'credit card'

}

>>> transaction_2 = {

    'store_name': 'burger king', 'branch_name': 

    'somerset west', 'account_id': 'bk_29151823', 

    'total_costs': 89.99, 'products_purchased': ['cheese burger', 'pepsi'], 

    'purchase_method': 'cash'

}

>>> transaction_3 = {

    'store_name': 'game', 'branch_name': 'bellvile', 'account_id': 'gm_49121229', 

    'total_costs': 499.99, 'products_purchased': ['ps4 remote'], 

    'purchase_method': 'cash'

}

>>> response = transactions.insert_many([transaction_1, transaction_2, transaction_3])

>>> response.inserted_ids

[ObjectId('5cad18d4a5f3826f6f046d75'), ObjectId('5cad18d4a5f3826f6f046d76'), ObjectId('5cad18d4a5f3826f6f046d77')]

```

### Find One Document:

```

>>> transactions.find_one({'account_id': 'gm_49121229'})

{u'account_id': u'gm_49121229', u'store_name': u'game', u'purchase_method': u'cash', u'branch_name': u'bellvile', u'products_purchased': [u'ps4 remote'], u'_id': ObjectId('5cad18d4a5f3826f6f046d77'), u'total_costs': 499.99}

```

### Find Many Documents:

```

>>> response = transactions.find({'purchase_method': 'cash'})

>>> [doc for doc in response]

[{u'account_id': u'bk_29151823', u'store_name': u'burger king', u'purchase_method': u'cash', u'branch_name': u'somerset west', u'products_purchased': [u'cheese burger', u'pepsi'], u'_id': ObjectId('5cad18d4a5f3826f6f046d76'), u'total_costs': 89.99}, {u'account_id': u'gm_49121229', u'store_name': u'game', u'purchase_method': u'cash', u'branch_name': u'bellvile', u'products_purchased': [u'ps4 remote'], u'_id': ObjectId('5cad18d4a5f3826f6f046d77'), u'total_costs': 499.99}]

```

Or filtering down the results to only the account id:

```

>>> response = transactions.find({'purchase_method': 'cash'})

>>> [doc['account_id'] for doc in response]

[u'bk_29151823', u'gm_49121229']

```

MongoDB also has a count method:

```

>>> transactions.count_documents({'purchase_method': 'cash'})

2

```

Query with the AND condition. SQL equivalent: `where branch_name = 'tygervalley' AND account_id = 'sns_03821023'`

```

>>> response = transactions.find({ '$and': [{'branch_name': 'tygervalley'},{'account_id': 'sns_03821023'}]})

>>> [v for v in response]

[{u'account_id': u'sns_03821023', u'store_name': u'sportsmans', u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'products_purchased': [u'cricket bat', u'cricket ball', u'sports hat'], u'_id': ObjectId('5cb18881df585e003c976d5d'), u'total_costs': 109.2}]

```

Query with the OR condition. SQL equivalent: `where branch_name = 'tygervalley' OR account_id = 'sns_03821023'`:

```

>>> response = transactions.find({ '$or': [{'branch_name': 'tygervalley'},{'account_id': 'sns_03821023'}]})

>>> [v for v in response]

[{u'account_id': u'sns_03821023', u'store_name': u'sportsmans', u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'products_purchased': [u'cricket bat', u'cricket ball', u'sports hat'], u'_id': ObjectId('5cb18881df585e003c976d5d'), u'total_costs': 109.2}, {u'account_id': u'sns_09121024', u'store_name': u'sportsmans', u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'products_purchased': [u'sportsdrink', u'sunglasses', u'sports illustrated'], u'_id': ObjectId('5cb188a3df585e003c976d5e'), u'total_costs': 129.84}]

```

Combining it:

```

>>> response = transactions.find({ 'total_costs': {'$gt': 120}, '$or': [{'branch_name': 'tygervalley'},{'account_id': 'sns_03821023'}]})

>>> [v for v in response]

[{u'account_id': u'sns_09121024', u'store_name': u'sportsmans', u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'products_purchased': [u'sportsdrink', u'sunglasses', u'sports illustrated'], u'_id': ObjectId('5cb188a3df585e003c976d5e'), u'total_costs': 129.84}]

```

Other condition operations include:

```

lt  - Less Than

lte - Less Than Equals

gt  - Greater Than

gte - Greater Than Equals

ne  - Not Equals

```

## Range Queries:

```

>>> import datetime

>>> new_posts = [{"author": "Mike","text": "Another post!","tags": ["bulk", "insert"],"date": datetime.datetime(2009, 11, 12, 11, 14)},{"author": "Eliot","title": "MongoDB is fun","text": "and pretty easy too!","date": datetime.datetime(2009, 11, 10, 10, 45)}]

>>> db.posts.insert(new_posts)

[ObjectId('5cb439c0f90e2e002a164d15'), ObjectId('5cb439c0f90e2e002a164d16')]

>>> for post in db.posts.find():

...     post

...

{u'date': datetime.datetime(2009, 11, 12, 11, 14), u'text': u'Another post!', u'_id': ObjectId('5cb439c0f90e2e002a164d15'), u'author': u'Mike', u'tags': [u'bulk', u'insert']}

{u'date': datetime.datetime(2009, 11, 10, 10, 45), u'text': u'and pretty easy too!', u'_id': ObjectId('5cb439c0f90e2e002a164d16'), u'author': u'Eliot', u'title': u'MongoDB is fun'}

>>> d = datetime.datetime(2009, 11, 11, 12)

>>> for post in db.posts.find({"date": {"$lt": d}}).sort("author"):

...     post

...

{u'date': datetime.datetime(2009, 11, 10, 10, 45), u'text': u'and pretty easy too!', u'_id': ObjectId('5cb439c0f90e2e002a164d16'), u'author': u'Eliot', u'title': u'MongoDB is fun'}

```

## Updates

Let's say we want to change a transactions payment method from credit card to account:

```

>>> transactions.find_one({'account_id':'sns_03821023'})

{u'account_id': u'sns_03821023', u'store_name': u'sportsmans', u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'products_purchased': [u'cricket bat', u'cricket ball', u'sports hat'], u'_id': ObjectId('5cb18881df585e003c976d5d'), u'total_costs': 109.2}```

```

Update the purchase_method to account:

```

>>> transactions.update( {'account_id': 'sns_03821023'}, {'$set': {'purchase_method': 'account'}})

{'updatedExisting': True, u'nModified': 1, u'ok': 1.0, u'n': 1}

```

Verify:

```

>>> transactions.find_one({'account_id':'sns_03821023'})

{u'account_id': u'sns_03821023', u'store_name': u'sportsmans', u'purchase_method': u'account', u'branch_name': u'tygervalley', u'products_purchased': [u'cricket bat', u'cricket ball', u'sports hat'], u'_id': ObjectId('5cb18881df585e003c976d5d'), u'total_costs': 109.2}

```

This examples is only intended for a single document and mongodb only updates one document at a time. To update more than one at a time:

```

transactions.update( {'k': 'v'}, {'$set': {'k': 'new_v'}},{multi:true})

```

### Filters

Find all the documents with purchase price > 120:

```

>>> response = transactions.find({'total_costs': {'$gt': 120}})

>>> [doc for doc in response]

[{u'account_id': u'sns_09121024', u'store_name': u'sportsmans', u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'products_purchased': [u'sportsdrink', u'sunglasses', u'sports illustrated'], u'_id': ObjectId('5cad18d4a5f3826f6f046d75'), u'total_costs': 129.84}, {u'account_id': u'gm_49121229', u'store_name': u'game', u'purchase_method': u'cash', u'branch_name': u'bellvile', u'products_purchased': [u'ps4 remote'], u'_id': ObjectId('5cad18d4a5f3826f6f046d77'), u'total_costs': 499.99}]

```

### Projections

Select specific fields from the returned response:

```

>>> response = transactions.find({}, {'branch_name': 'tygervalley', 'purchase_method': 'credit card'})

>>> [doc for doc in response]

[{u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'_id': ObjectId('5cad16a5a5f3826f6f046d74')}, {u'purchase_method': u'credit card', u'branch_name': u'tygervalley', u'_id': ObjectId('5cad18d4a5f3826f6f046d75')}, {u'purchase_method': u'cash', u'branch_name': u'somerset west', u'_id': ObjectId('5cad18d4a5f3826f6f046d76')}, {u'purchase_method': u'cash', u'branch_name': u'bellvile', u'_id': ObjectId('5cad18d4a5f3826f6f046d77')}]

```

### Sorting Documents

Sorting Documents in Descending Order:

```

>>> from pymongo import MongoClient, DESCENDING

>>> response = transactions.find().sort('total_costs', DESCENDING)

>>> ['Products: {}, Price: {}'.format(doc['products_purchased'], doc['total_costs']) for doc in response]

["Products: [u'ps4 remote'], Price: 499.99", "Products: [u'sportsdrink', u'sunglasses', u'sports illustrated'], Price: 129.84", "Products: [u'cricket bat', u'cricket ball', u'sports hat'], Price: 109.2", "Products: [u'cheese burger', u'pepsi'], Price: 89.99"]

```

### Aggregations

```

>>> agr = [{'$group': {'_id': 1, 'all': { '$sum': '$total_costs' }}}]

>> [a for a in transactions.aggregate(agr)]

[{u'all': 829.02, u'_id': 1}]

```

or:

```

>>> agr = [{'$group': {'_id': 1, 'all': { '$sum': '$total_costs' }}}]

>>> val = list(transactions.aggregate(agr))

>>> val

[{u'all': 829.02, u'_id': 1}]

```

Select fields to aggregate, eg. aggregate the costs for selected stores:

```

>>> agr = [{ '$match': {'$or': [ { 'store_name': 'sportsmans' }, { 'store_name': 'game' }] }}, { '$group': {'_id': 1, 'sum2stores': { '$sum': '$total_costs' } }}]

>>> [a for a in transactions.aggregate(agr)]

[{u'_id': 1, u'sum2stores': 739.03}]

```

### Limit Data Output

```

>>> response = transactions.find()

>>> [a['account_id'] for a in response]

[u'sns_03821023', u'sns_09121024', u'bk_29151823', u'gm_49121229']

>>> response = transactions.find().limit(2)

>>> [a['account_id'] for a in response]

[u'sns_03821023', u'sns_09121024']

>>> response = transactions.find().skip(1).limit(3)

>>> [a['account_id'] for a in response]

[u'sns_09121024', u'bk_29151823', u'gm_49121229']

>>> response = transactions.find().skip(1).limit(2)

>>> [a['account_id'] for a in response]

[u'sns_09121024', u'bk_29151823']

>>> response = transactions.find().skip(3).limit(1)

>>> [a['account_id'] for a in response]

[u'gm_49121229']

```

## Indexes

Create index:

```

>>> from pymongo import TEXT

>>> transactions.create_index([("store_name", TEXT)], name='store_index', default_language='english')

'store_index'

```

## Delete Documents:

Delete selected documents:

```

>>> transactions.remove({'account_id':'sns_03821029'})

{u'ok': 1.0, u'n': 2}

```

Delete all documents:

```

>>> transactions.remove()

```

### Drop Collections

```

>>> transactions.drop()

>>> db.collection_names()

[]

```

### Drop Databases

```

>>> c.drop_database('store_db')

```

### MongoEngine - ORM

```

>>> from mongoengine import *

>>> connect('project1', host="mongodb://user:[email protected]:27017/random_api?authSource=admin&authMechanism=SCRAM-SHA-1")

MongoClient(host=['mongodb.domain.com:27017'], document_class=dict, tz_aware=False, connect=True, read_preference=Primary(), authsource='admin', authmechanism='SCRAM-SHA-1')

```

```

>>> class Student(Document):

    name = StringField(required=True, max_length=200)

    city = StringField(required=True, max_length=200)

    can_code = BooleanField(required=True)

```

Create a student:

```

>>> doc_1 = Student(name='Josh', city='Cape Town', can_code=True)

>>> doc_1.save()

>>> doc_1.id

ObjectId('5cad27dea5f38276a40f43db')

>>> doc_1.name

u'Josh'

>>> doc_1.city

u'Cape Town'

>>> doc_1.can_code

True

```

Test out validation:

```

>>> doc_2 = Student(name='Max', city='Cape Town')

>>> doc_2.save()

Traceback (most recent call last):

  File "", line 1, in 

  File "/usr/local/lib/python2.7/site-packages/mongoengine/document.py", line 369, in save

    self.validate(clean=clean)

  File "/usr/local/lib/python2.7/site-packages/mongoengine/base/document.py", line 392, in validate

    raise ValidationError(message, errors=errors)

mongoengine.errors.ValidationError: ValidationError (Student:None) (Field is required: ['can_code'])

```

Update a user's city:

```

>>> doc_2 = Student(name='Max', city='Cape Town', can_code=False)

>>> doc_2.save()

>>> doc_2.id

ObjectId('5cad2835a5f38276a40f43dc')

>>> doc_2.city

u'Cape Town'

>>> doc_2.city = 'Johannesburg'

>>> doc_2.save()

>>> doc_2.city

'Johannesburg'

```

## Datasets:

- https://raw.githubusercontent.com/steveren/docs-assets/charts-tutorial/movieDetails.json

## Resources

- https://itnext.io/indexing-and-mongodb-query-performance-a8a6a64c4308

- https://realpython.com/introduction-to-mongodb-and-python/

- https://docs.mongodb.com/charts/master/tutorial/movie-details/prereqs-and-import-data/

- https://www.tutorialspoint.com/mongodb/mongodb_relationships.htm

- http://zetcode.com/python/pymongo/