MongoDB CRUD Operations with PyMongo in Python

The article provides a step‑by‑step guide for using the PyMongo driver to interact with MongoDB from Python, covering installation, connection, and a wide range of CRUD operations.

Dependencies: Install the driver with pip install pymongo and ensure a running MongoDB instance.

Connection example:

from pymongo import MongoClient
client = MongoClient('mongodb://127.0.0.1:27017')
db = client.express
print(db.collection_names())
collection = db.delivery

Basic queries such as listing collections, finding documents, and printing results are shown, e.g.,

for row in collection.find({}):
    print(row.values())

Update operations: The guide illustrates field updates with $set, conditional updates, and options like upsert and multi. Example to change age to 50: my_set.update({"name":"zhangsan"},{"$set":{"age":50}}) Delete operations: Documents can be removed using remove with optional query criteria, e.g.,

my_set.remove({'name': 'zhangsan'})
my_set.remove(id)
db.users.remove()

Query operators: The article lists common MongoDB operators and shows Python usage, including $gt, $lt, $gte, $lte, $in, $or, $all, and array modifiers like $push, $pushAll, $pop, $pull, $pullAll. Sample snippets:

# age > 25
for i in my_set.find({"age": {"$gt": 25}}):
    print(i)

# $or example
for i in my_set.find({"$or": [{"age": 20}, {"age": 35}]}):
    print(i)

Nested field operations: Using dot notation to query and update embedded documents, for example:

# query nested field
for i in my_set.find({"contact.iphone": "11223344"}):
    print(i)

# update nested field
my_set.update({"contact.iphone": "11223344"}, {"$set": {"contact.email": "[email protected]"}})

A complete class MyMongoDB is provided, encapsulating insert, update, delete, and find methods, and demonstrating usage in a main function.

The article ends with a call to follow the author for more automation learning resources.