Firestore collections and documents in GCP - Mini Project: Build & Apply

Firestore Collections and Documents

📖 Scenario: You are building a simple app to store user profiles in Google Firestore. Each user has a unique ID and some basic information like name and email.

🎯 Goal: Create a Firestore collection called users and add documents with user data. Then configure a query to retrieve users with a specific email domain.

📋 What You'll Learn

Create a Firestore collection named users with three user documents

Each user document must have fields name and email with exact values

Add a configuration variable to filter users by email domain

Write a query to get all users whose email contains the configured domain

💡 Why This Matters

🌍 Real World

Managing user profiles in Firestore is common in apps that need to store and query user data efficiently.

💼 Career

Understanding Firestore collections, documents, and querying is essential for cloud developers working with Google Cloud Platform.

1

Create Firestore collection with user documents

Create a Firestore collection called users with three documents. Each document should have the fields: name and email with these exact values:

- Document ID: user1, name: Alice, email: [e-mail]
- Document ID: user2, name: Bob, email: [e-mail]
- Document ID: user3, name: Charlie, email: [e-mail]

GCP

# Initialize Firestore client and create collection 'users' with documents
# Your code here

Hint

Use client.collection('users') to get the collection reference. Use document('user1').set({...}) to add documents.

2

Add email domain filter configuration

Create a variable called email_domain and set it to the string '@example.com'. This will be used to filter users by their email domain.

GCP

from google.cloud import firestore

client = firestore.Client()

users_ref = client.collection('users')

users_ref.document('user1').set({'name': 'Alice', 'email': '[e-mail]'})
users_ref.document('user2').set({'name': 'Bob', 'email': '[e-mail]'})
users_ref.document('user3').set({'name': 'Charlie', 'email': '[e-mail]'})

# Create email_domain variable
# Your code here

Hint

Just create a variable named email_domain and assign the string '@example.com'.

3

Write query to filter users by email domain

Write a query called query that gets all documents from the users collection where the email field contains the string stored in email_domain. Use Firestore's where method with the operator array_contains is not suitable here, so instead, retrieve all users and filter in Python using a list comprehension with email_domain in the email field.

GCP

from google.cloud import firestore

client = firestore.Client()

users_ref = client.collection('users')

users_ref.document('user1').set({'name': 'Alice', 'email': '[e-mail]'})
users_ref.document('user2').set({'name': 'Bob', 'email': '[e-mail]'})
users_ref.document('user3').set({'name': 'Charlie', 'email': '[e-mail]'})

email_domain = '@example.com'

# Retrieve all users and filter by email domain
# Your code here

Hint

Firestore does not support 'contains' queries on strings. Retrieve all documents with stream() and filter in Python using a list comprehension.

4

Complete by printing filtered user names

Add a for loop to iterate over query and print the name field of each user document.

GCP

from google.cloud import firestore

client = firestore.Client()

users_ref = client.collection('users')

users_ref.document('user1').set({'name': 'Alice', 'email': '[e-mail]'})
users_ref.document('user2').set({'name': 'Bob', 'email': '[e-mail]'})
users_ref.document('user3').set({'name': 'Charlie', 'email': '[e-mail]'})

email_domain = '@example.com'

all_users = users_ref.stream()

query = [user for user in all_users if email_domain in user.to_dict().get('email', '')]

# Loop through query and print user names
# Your code here

Hint

Use a for loop over query and print the name field from each document's data.

Practice

1. What is the correct way to describe Firestore's data structure?

easy

A. Documents are the top-level containers holding collections.

B. Documents contain collections, and collections contain key-value pairs.

C. Collections contain key-value pairs directly without documents.

D. Collections contain documents, and documents contain key-value pairs.

Solution

1. Step 1: Understand Firestore data hierarchy

   Firestore organizes data with collections at the top level, which hold documents.

2. Step 2: Identify what documents contain

   Documents store data as key-value pairs, not collections directly.

3. Final Answer:

   Collections contain documents, and documents contain key-value pairs. -> Option D

4. Quick Check:

   Firestore data = collections > documents > key-value pairs [OK]

Hint: Remember: Collections hold documents, documents hold data [OK]

Common Mistakes:

• Thinking documents hold collections directly
• Assuming collections store key-value pairs without documents
• Confusing the order of collections and documents

2. Which of the following is the correct syntax to get a reference to a document named user123 inside a collection users in Firestore using Node.js?

easy

A. const docRef = firestore.doc('user123/users');

B. const docRef = firestore.collection('users').doc('user123');

C. const docRef = firestore.collection('user123').doc('users');

D. const docRef = firestore.doc('users').doc('user123');

Solution

1. Step 1: Identify correct method to access collection and document

   Use collection('users') to access the collection, then doc('user123') to get the document.

2. Step 2: Check path correctness

   Direct firestore.doc(full/path) works for existing paths, but incorrect paths, reversed order, or misusing doc() on document references fail. Chaining collection().doc() is recommended.

3. Final Answer:

   const docRef = firestore.collection('users').doc('user123'); -> Option B

4. Quick Check:

   Use collection().doc() chaining for document refs [OK]

Hint: Chain collection() then doc() for document reference [OK]

Common Mistakes:

• Swapping collection and document names
• Using firestore.doc() with incorrect path format
• Confusing collection() and doc() order

3. Given the following Firestore code snippet, what will be the output if the document user123 exists with fields {name: 'Alice', age: 30}?

const docRef = firestore.collection('users').doc('user123');
const docSnap = await docRef.get();
if (docSnap.exists) {
  console.log(docSnap.data());
} else {
  console.log('No such document!');
}

medium

A. 'No such document!'

B. undefined

C. { name: 'Alice', age: 30 }

D. Error: Document not found

Solution

1. Step 1: Check if document exists

   The code checks docSnap.exists, which is true if the document is present.

2. Step 2: Output document data

   If exists, docSnap.data() returns the document fields as an object.

3. Final Answer:

   { name: 'Alice', age: 30 } -> Option C

4. Quick Check:

   docSnap.exists true means data() returns fields [OK]

Hint: docSnap.exists true means data() returns document fields [OK]

Common Mistakes:

• Assuming data() returns undefined if document exists
• Confusing exists check with data presence
• Expecting error instead of 'No such document!' message

4. You wrote this Firestore code to get a document but docSnap.exists is false:

const docRef = firestore.collection('users').doc();
const docSnap = await docRef.get();

What is the problem?

medium

A. Missing document ID in doc() causes a reference to a non-existing document.

B. You cannot call get() on a document reference.

C. Collection name 'users' is invalid without quotes.

D. You must use firestore.doc() instead of collection().doc().

Solution

1. Step 1: Check doc() usage

   Calling doc() without an ID creates a reference to a new document with an auto-generated ID, but it does not exist yet.

2. Step 2: Understand get() on new doc reference

   Trying to get() returns a snapshot with exists=false because the document does not exist.

3. Final Answer:

   Missing document ID in doc() causes a reference to a non-existing document. -> Option A

4. Quick Check:

   doc() needs ID to get existing document [OK]

Hint: Always provide document ID in doc() to read existing document [OK]

Common Mistakes:

• Assuming doc() without ID points to existing document
• Thinking get() cannot be called on document references
• Confusing collection and document method usage

5. You want to store user profiles in Firestore where each user has multiple addresses. Which is the best Firestore structure to model this data?

hard

A. A collection 'users' with documents for each user, and each user document has a subcollection 'addresses' with address documents.

B. A single collection 'addresses' with documents containing user info and address fields combined.

C. A collection 'users' where each document stores all addresses as a large array field.

D. Multiple collections named after each user ID, each containing address documents.

Solution

1. Step 1: Understand Firestore best practice for one-to-many

   Use a main collection for users, and subcollections for related multiple items like addresses.

2. Step 2: Evaluate options

   A collection 'users' with documents for each user, and each user document has a subcollection 'addresses' with address documents. uses subcollections for addresses, which is scalable and organized. A single collection 'addresses' with documents containing user info and address fields combined. mixes user and address data in one collection, which is less clear. A collection 'users' where each document stores all addresses as a large array field. stores all addresses in one field, which can be inefficient. Multiple collections named after each user ID, each containing address documents. creates many collections dynamically, which is not recommended.

3. Final Answer:

   A collection 'users' with documents for each user, and each user document has a subcollection 'addresses' with address documents. -> Option A

4. Quick Check:

   Use subcollections for related multiple items [OK]

Hint: Use subcollections for multiple related documents per user [OK]

Common Mistakes:

• Storing multiple addresses in one array field causing size limits
• Creating dynamic collections per user causing management issues
• Mixing unrelated data in one collection