MongoDB Compass & Shell

# Compass connection strings — paste into the Compass connection bar

# Local MongoDB (default — no authentication)
local_connection = "mongodb://localhost:27017"

# Local MongoDB with authentication
local_auth = "mongodb://username:password@localhost:27017"

# MongoDB Atlas (SRV format — replace with your actual URI)
atlas_connection = "mongodb+srv://youruser:yourpassword@cluster0.xxxxx.mongodb.net/"

# Connection steps in Compass:
steps = [
    "1. Open MongoDB Compass",
    "2. Paste your connection string into the URI field",
    "3. Click 'Connect'",
    "4. Browse your databases in the left panel",
    "5. Click 'dataplexa' → select a collection → explore documents",
]

for step in steps:
    print(step)

# Compass interface — key tabs and what they do

compass_tabs = {
    "Documents": (
        "Browse, filter, insert, edit, and delete documents visually. "
        "Use the filter bar to write MQL queries with autocomplete."
    ),
    "Aggregations": (
        "Build aggregation pipelines stage by stage with a visual editor. "
        "Each stage shows a live preview of its output — no guessing."
    ),
    "Schema": (
        "Analyse the structure of a collection automatically. "
        "Shows field types, value distributions, and cardinality across all documents."
    ),
    "Indexes": (
        "View existing indexes, create new ones, and see index usage statistics. "
        "Helps identify missing indexes causing slow queries."
    ),
    "Explain Plan": (
        "Run a query and see exactly how MongoDB executed it — "
        "which indexes were used, how many documents were scanned."
    ),
    "Validation": (
        "Create and manage JSON Schema validation rules for a collection "
        "directly from the UI."
    ),
}

for tab, description in compass_tabs.items():
    print(f"[{tab}]\n  {description}\n")

# Compass filter bar examples — paste these into the Filter input

# All premium users
filter_1 = '{ "membership": "premium" }'

# Products priced over $50 in the Electronics category
filter_2 = '{ "category": "Electronics", "price": { "$gt": 50 } }'

# Orders with status "delivered"
filter_3 = '{ "status": "delivered" }'

# Users from the UK aged 25 or over
filter_4 = '{ "country": "UK", "age": { "$gte": 25 } }'

# Products with "bestseller" in their tags array
filter_5 = '{ "tags": "bestseller" }'

filters = [filter_1, filter_2, filter_3, filter_4, filter_5]
labels  = ["Premium users", "Electronics > $50", "Delivered orders", "UK users 25+", "Bestseller products"]

for label, f in zip(labels, filters):
    print(f"{label}:\n  {f}\n")

# mongosh — connecting and essential navigation commands

# Connect to local MongoDB
# mongosh

# Connect to Atlas
# mongosh "mongodb+srv://youruser:yourpassword@cluster0.xxxxx.mongodb.net/"

# ── Navigation ──────────────────────────────────────────
# show dbs                     list all databases
# use dataplexa                switch to the dataplexa database
# show collections             list all collections in current database
# db                           print the current database name

# ── Collection info ─────────────────────────────────────
# db.products.countDocuments()            count all documents
# db.products.countDocuments({category:"Electronics"})  count with filter
# db.products.stats()                     collection statistics
# db.products.getIndexes()                list indexes

# ── Quick data checks ───────────────────────────────────
# db.products.findOne()                   return one document
# db.products.find().limit(3)             return first 3 documents
# db.products.distinct("category")        list unique category values

print("mongosh commands ready — run them in your terminal after connecting")

# Explore the Dataplexa Store dataset — run in mongosh

# Switch to the course database
# use dataplexa

# Check what collections exist
# show collections

# Count documents in each collection
# db.users.countDocuments()       → 5
# db.products.countDocuments()    → 7
# db.orders.countDocuments()      → 7
# db.reviews.countDocuments()     → 5

# Inspect a sample document from each collection
# db.users.findOne()
# db.products.findOne()
# db.orders.findOne()
# db.reviews.findOne()

# Explore unique values
# db.products.distinct("category")   → ['Electronics', 'Furniture', 'Stationery']
# db.orders.distinct("status")       → ['cancelled', 'delivered', 'processing', 'shipped']
# db.users.distinct("membership")    → ['basic', 'premium']
# db.users.distinct("country")       → ['Germany', 'Spain', 'UK', 'USA']

print("Dataset exploration commands ready — run each line in mongosh")

# Running a script file with mongosh

# Create a file called explore.js:
script_content = """
// explore.js — run with: mongosh explore.js

const db = connect("mongodb://localhost:27017/dataplexa");

print("=== Dataplexa Store Summary ===");
print("Users:    ", db.users.countDocuments());
print("Products: ", db.products.countDocuments());
print("Orders:   ", db.orders.countDocuments());
print("Reviews:  ", db.reviews.countDocuments());

print("\\nProduct categories:");
db.products.distinct("category").forEach(cat => print("  -", cat));

print("\\nOrder statuses:");
db.orders.distinct("status").forEach(s => print("  -", s));
"""

# Run the script from your terminal:
# mongosh explore.js

print("Script written — run with: mongosh explore.js")