Efficient data structures in Blockchain / Solidity - Mini Project: Build & Apply

Efficient Data Structures in Blockchain

📖 Scenario: You are building a simple blockchain ledger to store transactions. Each transaction has a unique ID and an amount. Efficient data storage is important to quickly find and update transactions.

🎯 Goal: Create a dictionary to store transactions, add a threshold to filter large transactions, use dictionary comprehension to select only large transactions, and print the filtered transactions.

📋 What You'll Learn

Create a dictionary called transactions with exact transaction IDs and amounts

Create a variable called threshold with the value 1000

Use dictionary comprehension with transaction_id and amount to select transactions with amounts greater than threshold

Print the filtered dictionary called large_transactions

💡 Why This Matters

🌍 Real World

Blockchains store many transactions and need fast ways to find important data like large transfers.

💼 Career

Understanding efficient data structures helps blockchain developers optimize storage and speed in real applications.

1

Create the transactions dictionary

Create a dictionary called transactions with these exact entries: 'tx1001': 500, 'tx1002': 1500, 'tx1003': 700, 'tx1004': 2500, 'tx1005': 300

Blockchain / Solidity

# Create the transactions dictionary with given transaction IDs and amounts
# Your code here

Hint

Use curly braces {} to create a dictionary with keys as transaction IDs and values as amounts.

2

Set the threshold for large transactions

Create a variable called threshold and set it to 1000

Blockchain / Solidity

transactions = {'tx1001': 500, 'tx1002': 1500, 'tx1003': 700, 'tx1004': 2500, 'tx1005': 300}
# Create a variable called threshold and set it to 1000
# Your code here

Hint

Just assign the number 1000 to the variable threshold.

3

Filter large transactions using dictionary comprehension

Use dictionary comprehension with transaction_id and amount to create a new dictionary called large_transactions that contains only transactions where amount > threshold

Blockchain / Solidity

transactions = {'tx1001': 500, 'tx1002': 1500, 'tx1003': 700, 'tx1004': 2500, 'tx1005': 300}
threshold = 1000
# Use dictionary comprehension to filter transactions greater than threshold
# Your code here

Hint

Use {key: value for key, value in dict.items() if condition} to filter the dictionary.

4

Print the filtered large transactions

Write print(large_transactions) to display the dictionary of large transactions

Blockchain / Solidity

transactions = {'tx1001': 500, 'tx1002': 1500, 'tx1003': 700, 'tx1004': 2500, 'tx1005': 300}
threshold = 1000
large_transactions = {transaction_id: amount for transaction_id, amount in transactions.items() if amount > threshold}
# Print the large_transactions dictionary
# Your code here

Hint

Use the print() function to show the filtered dictionary.

Practice

1. Which data structure is best for quickly finding a user's balance by their blockchain address?

easy

A. Array

B. Mapping (key-value pairs)

C. Struct

D. Linked list

Solution

1. Step 1: Understand the need for quick lookup

   We want to find a balance by address fast, so we need a structure that supports direct access by key.

2. Step 2: Identify the best data structure

   Mappings provide key-value pairs allowing O(1) access by address, unlike arrays or structs which require searching.

3. Final Answer:

   Mapping (key-value pairs) -> Option B

4. Quick Check:

   Fast key-based lookup = Mapping [OK]

Hint: Use mappings for direct key lookups in blockchain [OK]

Common Mistakes:

• Choosing arrays which require looping to find an address
• Using structs alone without a key for lookup
• Thinking linked lists are efficient for random access

2. Which of the following is the correct syntax to declare a mapping from address to uint in Solidity?

easy

A. mapping(address => uint) balances;

B. mapping(address, uint) balances;

C. mapping[address] uint balances;

D. mapping{address: uint} balances;

Solution

1. Step 1: Recall Solidity mapping syntax

   Mappings use the syntax mapping(keyType => valueType) variableName;

2. Step 2: Match the correct syntax

   mapping(address => uint) balances; matches this exactly: mapping(address => uint) balances;

3. Final Answer:

   mapping(address => uint) balances; -> Option A

4. Quick Check:

   Correct mapping syntax uses '=>' [OK]

Hint: Remember mapping uses '=>' between key and value types [OK]

Common Mistakes:

• Using commas instead of '=>' in mapping
• Using square brackets or curly braces incorrectly
• Omitting the semicolon at the end

3. What will be the output of this Solidity code snippet?

struct User { uint id; string name; }
User[] users;
users.push(User(1, "Alice"));
users.push(User(2, "Bob"));
string memory name = users[1].name;

medium

A. "Alice"

B. Empty string

C. Compilation error

D. "Bob"

Solution

1. Step 1: Understand array indexing

   Arrays start at index 0, so users[0] is Alice, users[1] is Bob.

2. Step 2: Identify the accessed element

   The code accesses users[1].name, which is "Bob".

3. Final Answer:

   "Bob" -> Option D

4. Quick Check:

   Index 1 in array = "Bob" [OK]

Hint: Remember arrays start at zero index [OK]

Common Mistakes:

• Confusing index 1 with index 0
• Assuming structs print as variable names
• Expecting compilation error due to string usage

4. Identify the error in this Solidity code snippet:

mapping(address => uint) balances;
function addBalance(address user, uint amount) public {
  balances[user] += amount;
}

medium

A. Cannot use '+=' on mapping values

B. Function lacks visibility modifier

C. No initialization needed for mapping values

D. Mapping keys must be uint, not address

Solution

1. Step 1: Check mapping usage

   Mappings default to zero for uint values if key not set, so no initialization needed.

2. Step 2: Verify function and operation

   Using '+=' on balances[user] is valid; function has public visibility.

3. Final Answer:

   No initialization needed for mapping values -> Option C

4. Quick Check:

   Mapping uint defaults to 0, so '+=' works [OK]

Hint: Mapping values default to zero, no init needed [OK]

Common Mistakes:

• Thinking mapping values must be initialized before use
• Confusing visibility modifiers
• Assuming keys must be uint instead of address

5. You want to store user profiles with id, name, and balance, and quickly find a profile by id. Which data structure combination is most efficient in Solidity?

hard

A. Mapping from id to struct

B. Array of structs only

C. Struct with embedded array

D. Linked list of structs

Solution

1. Step 1: Analyze the need for quick lookup by id

   Quick lookup by id requires direct access, which arrays or linked lists cannot provide efficiently.

2. Step 2: Choose the best data structure

   Mapping from id to struct allows O(1) access to user profiles by id, combining grouping (struct) and fast lookup (mapping).

3. Final Answer:

   Mapping from id to struct -> Option A

4. Quick Check:

   Fast key access + grouped data = mapping to struct [OK]

Hint: Use mapping from id to struct for fast profile lookup [OK]

Common Mistakes:

• Using arrays which require looping to find id
• Using linked lists which are slow for random access
• Embedding arrays inside structs without mapping