MongoDB

JSON Objects = Python Dictionaries

JSON <> Python <> MongoDB

# Connect to the "nobel" database
db = client.nobel

# Retrieve sample prize and laureate documents
prize = db.prizes.find_one()
laureate = db.laureates.find_one()

# Print the sample prize and laureate documents
print(prize)
print(laureate)
print(type(laureate))

# Get the fields present in each type of document
prize_fields = list(prize.keys())
laureate_fields = list(laureate.keys())

print(prize_fields)
print(laureate_fields)

Finding Documents

db.laureates.count_documents({"born": {"$lt": "1900"}})

# Create a filter for Germany-born laureates who died in the USA and with the first name "Albert"
criteria = {'diedCountry': 'USA', 
						'bornCountry': 'Germany', 
						'firstname': 'Albert'}

# Save the count
count = db.laureates.count_documents(criteria)
print(count)

Dot Notation

Operators

$lt = less than $gte = greater than or equal $exists $ne = “Not Exists” $in $nin = “Not In” $elemMatch = Multiple Conditions

count_documents() method

# Filter for laureates born in Austria with non-Austria prize affiliation
criteria = {"bornCountry": "Austria", 
						"prizes.affiliations.country": {"$ne": "Austria"}}

# Count the number of such laureates
count = db.laureates.count_documents(criteria)
print(count)

# Filter for documents without a "born" field
criteria = {"born": {"$exists": False}}

# Save count
count = db.laureates.count_documents(criteria)
print(count)

find_one() method

# Filter for laureates with at least three prizes
criteria = {"prizes.2": {"$exists": True}}

# Find one laureate with at least three prizes
doc = db.laureates.find_one(criteria)

# Print the document
print(doc)

distinct() method

# Countries recorded as countries of death but not as countries of birth
countries = set(db.laureates.distinct("diedCountry")) - set(db.laureates.distinct("bornCountry"))
print(countries)

# The number of distinct countries of laureate affiliation for prizes
count = len(db.laureates.distinct("prizes.affiliations.country"))
print(count)

# In which countries have USA-born laureates had affiliations for their prizes?
db.laureates.distinct("prizes.affiliations.country",{"bornCountry":"USA"})

# Save a filter for prize documents with three or more laureates
criteria = {"laureates.2": {"$exists": True}}

# Save the set of distinct prize categories in documents satisfying the criteria
triple_play_categories = set(db.prizes.distinct("category", criteria))
assert set(db.prizes.distinct("category")) - triple_play_categories == {"literature"}

Complex Queries

# Save a filter for laureates with unshared prizes
unshared = {
		"prizes": {"$elemMatch": {
				"category": {"$nin": ["physics", "chemistry", "medicine"]},
				"share": "1",
				"year": {"$gte": "1945"},
		}}}

# Save a filter for laureates with shared prizes
shared = {
		"prizes": {"$elemMatch": {
				"category": {"$nin": ["physics", "chemistry", "medicine"]},
				"share": {"$ne": "1"},
				"year": {"$gte": "1945"},
		}}}

ratio = db.laureates.count_documents(unshared) / db.laureates.count_documents(shared)
print(ratio)

Regular Expressions

Projection