Tutorial pymongo

tutorial-pymongo.py

import pymongo

# Connect
# Through a MongoDB URI. The database should contain permissions for the user, if provided
client = pymongo.MongoClient('mongodb://user:password@host/database')

# Create database
db = client["database"]
# Create collection
coll = db["collection"]
# Reference database/collection
coll = client.database.collection

# Insert
import datetime
post1 = {"author": "Mike", "text": "My first blog post!", "date": datetime.datetime.utcnow()}
post2 = {"author": "Mike", "text": "My second blog post!", "date": datetime.datetime.utcnow()}
# one
inserted_id = coll.insert_one(post1).inserted_id
# many
inserted_ids = coll.insert_many([post1, post2]).inserted_ids

# Query
# one
post = coll.find_one({"author": "Mike"}) # returns the object
# many
cursor = coll.find({"author": "Mike"}) # returns Cursor
for post in cursor:
    print post
    
# Delete
# one
deleted_count = coll.delete_one({"author": "Mike"}).deleted_count
# many
deleted_count = coll.delete_many({"author": "Mike"}).deleted_count

# Update
# one
modified_count = coll.update_one({"author": "Mike"}, {"title": ""}).modified_count
# many
modified_count = coll.update_many({"author": "Mike"}, {"title": ""}).modified_count

# Indexing
# create
coll.create_index([('user_id', pymongo.ASCENDING)], unique=True) # can be multiindex
# list
list(coll.index_information())


# Data transformations through "Aggregations"
pipeline = [
    {'$match': {'author': 'Mike'}}, #like find() syntax
    {'$project': {
        'name': '$author'  #rename field
        'text': True  #include field
        'comments': {'$literal': []}, #create field
    },
    {'$out': 'superposts'} #write to new collection
]
coll.aggregate(pipeline)


# Delete collection
coll.drop()
# Delete database
client.database.drop()