MongoDB Study Plan
Learn MongoDB by predicting stored documents, query outputs and refused changes. Progress from a document boundary to consistency and operational reasoning.
How it works
Begin with database identity, collection handles, projections and typed filters. Then practise updates, null/array cases and aggregation grain. Design validators and indexes before relying on invariants, and finish with real transaction/session behavior plus the lending project. Hosted products need their own current setup and permissions; a local database cannot prove those services are configured.
Run in a separate MongoDB lab
Start a disposable lab automatically: in a separate empty learning folder, save package.json, run-lab.mjs and this lesson’s source with its displayed filename. Run npm install --ignore-scripts, then node run-lab.mjs study-plan.mongosh.js. mongosh lessons also need mongosh installed on PATH. The launcher downloads the pinned MongoDB server on first use, starts one authenticated loopback replica-set member, supplies private child-process credentials, runs the lesson and stops that server. Its cache, generated data and diagnostic files stay in the private .bhylu-mongodb-lab folder; it installs no service. Review downloaded code before executing it.
The following manual connection route is an alternative for readers who already have a suitable separate lab instance.
The reviewed baseline is MongoDB 8.0.12, mongosh 2.14.0, Node.js 22.15.1 and driver 6.17.0. These are tested versions, not a newest-release claim. Use a private authenticated learning server on 127.0.0.1 and an explicit non-default port, not your normal database or an Atlas project. These scripts intentionally refuse port 27017 and remote hosts. Bhylu has no MongoDB browser runner; a plain JavaScript playground cannot provide this database.
Supply your own lab connection through the child process environment variable BHYLU_MONGO_URI and set BHYLU_MONGO_LAB=YES. Keep credentials private; do not save them in source or public commands. The lab role needs permission to create and drop its generated databases and collections. No PHP, Apache or normal XAMPP service change is needed.
Save the complete download as study-plan.mongosh.js and run mongosh --nodb --norc --quiet --file study-plan.mongosh.js in a separate child process. It reads its private connection from the environment. The file uses actual mongosh APIs; it is not a Node.js module.
Every run generates a new bhylu_mongo_ database name, refuses an existing collection set, writes its own ownership marker, seeds the complete fictional dataset and finally removes only that owned database after checking the marker. Do not change the generated name to a valuable existing database. Closing the child process releases its client connections.
Example
// Bhylu MongoDB 8.0.12 lab: Study Plan
// Run only against your separate authenticated loopback learning instance.
async function main() {
if (process.env.BHYLU_MONGO_LAB !== "YES")
throw new Error("Set BHYLU_MONGO_LAB=YES for a private lab");
const raw = process.env.BHYLU_MONGO_URI;
if (!raw)
throw new Error("Set BHYLU_MONGO_URI privately; do not commit credentials");
const address = new URL(raw);
if (
address.protocol !== "mongodb:" ||
address.hostname !== "127.0.0.1" ||
!address.port ||
address.port === "27017"
)
throw new Error("Use a private loopback MongoDB on a non-default port");
const marker = new ObjectId().toString(),
dbName = "bhylu_mongo_" + marker;
const connection = new Mongo(raw);
const db = connection.getDB(dbName);
let owned = false;
const emit = (value) => print(JSON.stringify(value));
try {
if ((await db.getCollectionNames()).length)
throw new Error("Refusing an existing database");
await db.createCollection("_bhylu_owner");
await db.getCollection("_bhylu_owner").insertOne({ _id: marker });
owned = true;
await db.getCollection("kits").insertMany([
{
_id: "K1",
label: "Birdwatch pack",
category: "observation",
available: 3,
condition: "ready",
location: { room: "North", shelf: 2 },
tags: ["outdoor", "compact"],
notes: null,
checks: [
{ kind: "lens", passed: true },
{ kind: "strap", passed: false },
],
},
{
_id: "K2",
label: "Stream sampler",
category: "sampling",
available: 1,
condition: "ready",
location: { room: "South", shelf: 1 },
tags: ["outdoor", "washable"],
checks: [
{ kind: "lens", passed: false },
{ kind: "strap", passed: true },
],
},
{
_id: "K3",
label: "Soil survey set",
category: "sampling",
available: 0,
condition: "repair",
location: { room: "North", shelf: 3 },
tags: ["washable"],
notes: "Replace pouch",
checks: [],
},
{
_id: "K4",
label: "Weather logger",
category: "observation",
available: 2,
condition: "ready",
location: { room: "South", shelf: 2 },
tags: [],
notes: null,
checks: [],
},
]);
await db.getCollection("members").insertMany([
{ _id: "M1", name: "Asha", area: "North" },
{ _id: "M2", name: "Dev", area: "South" },
{ _id: "M3", name: "Noor", area: "West" },
]);
await db.getCollection("loans").insertMany([
{
_id: "L1",
kitId: "K1",
memberId: "M1",
quantity: 1,
status: "returned",
openedAt: new Date("2026-01-10T09:00:00Z"),
},
{
_id: "L2",
kitId: "K1",
memberId: "M2",
quantity: 2,
status: "open",
openedAt: new Date("2026-01-11T09:00:00Z"),
},
{
_id: "L3",
kitId: "K2",
memberId: "M1",
quantity: 1,
status: "open",
openedAt: new Date("2026-01-11T10:00:00Z"),
},
{
_id: "L4",
kitId: "K3",
memberId: "M2",
quantity: 1,
status: "returned",
openedAt: new Date("2026-01-10T11:00:00Z"),
},
{
_id: "L5",
kitId: "K4",
memberId: null,
quantity: 1,
status: "planned",
openedAt: new Date("2026-01-12T09:00:00Z"),
},
]);
const kits = db.getCollection("kits"),
loans = db.getCollection("loans"),
members = db.getCollection("members");
// Lesson commands begin here.
emit({
kitTypes: await kits.countDocuments({}),
loanEvents: await loans.countDocuments({}),
unassignedLoans: await loans.countDocuments({ memberId: null }),
});
} finally {
if (owned) {
const owner = await db
.getCollection("_bhylu_owner")
.findOne({ _id: marker });
if (!owner || !/^bhylu_mongo_[a-f0-9]{24}$/.test(dbName))
throw new Error("Refusing cleanup without matching ownership marker");
await db.dropDatabase();
}
// The noninteractive mongosh process closes its connection when it exits.
}
}
main().catch((error) => {
console.error(error.message);
exit(1);
});
Focus on the lesson operations
This excerpt omits connection guards, seed and cleanup. Use the complete download to run it.
emit({kitTypes:await kits.countDocuments({}),loanEvents:await loans.countDocuments({}),
unassignedLoans:await loans.countDocuments({memberId:null})});
Expected result
{"kitTypes":4,"loanEvents":5,"unassignedLoans":1}The script emits JSON so these small results are unambiguous. Interactive shell formatting may look different. Object IDs and owned database names are not hard-coded expected values.
A good self-check explains why the three numbers describe different facts. For each new lesson identify input validation, result grain, ordering, missing-value policy and cleanup. The plan is guidance, not saved progress or a professional qualification.