Python MongoDB, Final Project & Interview Path

Python MongoDB — Get Started

MongoDB stores JSON-like documents. Python uses PyMongo: pip install pymongo.

Atlas free tier or local MongoDB for practice.

Real-life example: MongoDB is a flexible notebook — each page (document) can have different fields.

Create Database

MongoDB creates database on first write. client['knowvora'] selects or creates.

Real-life example: Naming a database is labeling a new shelf — items appear when you store the first box.

import pymongo

client = pymongo.MongoClient("mongodb://localhost:27017/")
db = client["knowvora"]
print(db.name)

Create Collection

Collections group documents — like tables without fixed schema.

db.create_collection('students') or implicit on insert.

Real-life example: A collection is a folder of similar forms — job applications, receipts, etc.

students = db["students"]
# or db.create_collection("students")

Insert

insert_one({}) and insert_many([]) add documents with _id auto-generated.

Real-life example: Insert is dropping a new form into the folder.

students = db["students"]
result = students.insert_one({"name": "Aarav", "score": 88})
print(result.inserted_id)

Find

find() returns a cursor; find_one() first match. Empty filter {} gets all.

Real-life example: Find is searching the folder for every form with score above 80.

for doc in students.find({"score": {"$gte": 80}}):
    print(doc)

Query

Query operators: $gt, $lt, $in, $regex. Combine with $and, $or.

Real-life example: Query is advanced search — name starts with A AND score > 70.

query = {"name": {"$regex": "^A"}, "score": {"$gt": 70}}
print(list(students.find(query)))

Sort

sort('score', -1) orders descending. 1 = ascending.

Real-life example: Sort is arranging forms by highest score on top.

for doc in students.find().sort("score", -1):
    print(doc["name"], doc["score"])

Update

update_one(filter, {'$set': {...}}) changes fields. $inc increments numbers.

Real-life example: Update is correcting one field on a form without rewriting the whole page.

students.update_one(
    {"name": "Aarav"},
    {"$set": {"score": 92}},
)

Delete

delete_one(filter) and delete_many(filter) remove documents.

Real-life example: Delete is throwing away outdated forms — keep backups in production.

students.delete_many({"score": {"$lt": 50}})

Drop

drop() removes entire collection. drop_database() removes whole DB — dangerous.

Real-life example: Drop is shredding the whole folder, not one paper.

students.drop()

Limit

limit(5) caps results — pair with sort() for top-N queries.

Real-life example: Limit is reading only the first five sorted results.

top = students.find().sort("score", -1).limit(3)
print(list(top))

Final Project — Student Analytics CLI

Build a CLI that loads student JSON, computes stats, saves to MySQL or MongoDB, and plots scores with Matplotlib.

Combines files, OOP, databases, and visualization from this full course.

Real-life example: A school admin tool — import marks, store in DB, print chart for principal.

import json
import statistics
import matplotlib.pyplot as plt

with open("students.json", encoding="utf-8") as f:
    data = json.load(f)

scores = [s["score"] for s in data]
print("Average:", statistics.mean(scores))

plt.bar([s["name"] for s in data], scores)
plt.title("Class Scores")
plt.show()

Interview & Examples Path

After 40 lessons: practice /mcq/python-mcq, /interview/python-interview, and rebuild the final project without notes.

Review the examples in earlier lessons for one-liners on lists, RegEx, files, and sklearn.

Real-life example: Interview prep is dress rehearsal — same skills as the job stage, lower stakes.

• Know list/dict complexity and when to use set
• Explain train/test split and overfitting in plain English
• Write connect → insert → select for MySQL and MongoDB from memory
• Ship the student analytics CLI as your portfolio piece