Pymongo Assistant

pymongo_assistant_01.py

"""
Written by Arsham Arya
Some snippets around pymongo package to prevent my confusion.
"""
from pymongo import MongoClient

# Initializing
client = MongoClient("mongodb://username:password@host:port/default_db?authSource=admin")
database = client.get_database("db_name")
collection = database.get_collection("collection_name")


# Creating a unique index
collection.create_index("field_name", unique=True)


# Inserting
result = collection.insert_one({
    "name": "Arsham",
    "family": "Arya",
    "age": 22
})

print(result.inserted_id)  # ObjectId("595590494")
print(result.acknowledged)  # True



# Updating
result = collection.update_one(
    {"name": "Arsham"},
    {"$set": {"profession": "programmer"}}
)

print(result.upserted_id)  # None
print(result.acknowledged)  # True
print(result.raw_result)  # {'n': 1, 'nModified': 1, 'ok': 1.0, 'updatedExisting': True}
print(result.matched_count)  # 1
print(result.modified_count)  # 1

# Run code above again and only change will be modified_count which is 0
# upserted_id is None because we didn't set upsert=True in arguments.



# Inserting items to array field
# If you want also duplicated values, you should use $push instead of $addToSet
result = collection.update_one(
    {"name": "Arsham"},
    {"$addToSet": {"loved_numbers": {"$each": [32, 24, 12]}}}
)
# Don't doubt that $each is necessary!
# And if you ommit that, there will be a nested array instead.



# Aggregating
results = collection.aggregate([
    {"$match": {"$and": [{"age": 22}, {"profession": "programmer"}]}},
    {"$addFields": {"lovely_number": "$loved_numbers"}},
    {"$project": {"name": 1, "family": 1, "lovely_number": 1}},
    {"$unwind": "$lovely_number"},
])

for item in results:
    print(type(item), item)

# <class 'dict'> {'_id': ObjectId('620a16e0f599d4631d0b1635'), 'name': 'Arsham', 'family': 'Arya', 'lovely_number': 32}
# <class 'dict'> {'_id': ObjectId('620a16e0f599d4631d0b1635'), 'name': 'Arsham', 'family': 'Arya', 'lovely_number': 24}
# <class 'dict'> {'_id': ObjectId('620a16e0f599d4631d0b1635'), 'name': 'Arsham', 'family': 'Arya', 'lovely_number': 12}
 
# Find also has same output as aggregate
# Be careful! pymongo won't return "None" for aggregate or find results, 
# it will return a Cursor class that is a iterable even if there are nothing to iterate.
# find_one has a dictionary output and will return "None" if there is no record.
results = collection.aggregate([{"$match": {"age": 748}}])
# results won't be None.