How Do You Make a Blockchain in R?

How Do You Make a Blockchain in R

Blockchain technology has taken the world by storm, revolutionizing the way we think about finance, security, and even governance. While blockchains are often associated with cryptocurrencies like Bitcoin and Ethereum, their applications extend far beyond the realm of digital money. In fact, blockchain technology has the potential to disrupt a wide range of industries, from healthcare to supply chain management.

If you’re interested in learning more about blockchain technology, you may be wondering how to create your own blockchain. While this may seem like a daunting task, it’s actually quite simple thanks to the power of the R programming language.

In this article, we will walk you through the steps of creating a simple blockchain in R. We will also discuss some of the key concepts of blockchain technology, such as hashing, consensus mechanisms, and distributed ledger technology.

What is a Blockchain?

A blockchain is a distributed ledger technology (DLT) that allows for secure, transparent, and tamper-proof transactions. It is a continuously growing list of records, called blocks, which are linked and secured using cryptography. Each block contains a timestamp, a transaction record, and a reference to the previous block. This creates a chain of blocks that is resistant to alteration or deletion.

Why Use R to Create a Blockchain?

R is a powerful and versatile programming language that is well-suited for data analysis and manipulation. It also has a rich ecosystem of packages that can be used for blockchain development.

Here are some of the benefits of using R to create a blockchain:

  • Ease of use: R is a relatively easy language to learn and use, even for beginners.
  • Versatility: R can be used for a wide range of tasks, from data analysis to web development.
  • Rich ecosystem:┬áThere are a number of packages available for R that can be used for blockchain development.


Before we start coding, let’s review some core knowledge that will be helpful:

  • Basic proficiency in R and RStudio
  • Understanding of blockchain principles and architecture
  • Basic knowledge of cryptographic hashes and digital signatures
  • Familiarity with R data structures like lists and data frames
  • Experience with R packages and finding documentation

It will also help to have RStudio and any required packages installed already.

Blockchain Basics

For those new to blockchain, here is a quick overview of some core concepts we will incorporate:

  • Distributed Ledger: A blockchain is a distributed ledger that is shared across a decentralized network of computers (nodes). It serves as a public historical record of all transactions that occur in the system.
  • Blocks: The ledger is composed of sequentially ordered blocks that record groups of transactions. Blocks link to prior blocks to form a chain.
  • Cryptography: Cryptographic hashes and digital signatures are used to secure blockchain data and keep the ledger immutable. Mining nodes run algorithms to add new valid blocks.
  • Consensus: All nodes in the network must agree on the state of the blockchain. Rules for consensus vary based on the protocol.
  • Transactions: Users initiate transactions that are entered into blocks. Transactions represent exchanges, transfers, or other state changes.
  • Wallets: Wallets store the public/private key pairs that identify users and allow them to interact with the blockchain securely.

There are additional aspects like smart contracts and proof of work/stake, but this covers the main ideas we will focus on for a basic implementation.

How to Choosing R Packages

R has a wide selection of packages that can help with building blockchain models. Here are some good options to consider:

  • blockchain – provides core data structures and functions for basic blockchain management
  • crypto – implements cryptographic hashes needed for blockchain security
  • jsonlite – useful for encoding blocks and data into JSON format
  • digest – additional hashing algorithms beyond base R
  • httr – provides HTTP tools that can help with node communication
  • glue – allows for easy data type conversions and data structure manipulation

The blockchain and crypto packages will be at the core of most of the blockchain implementation. Additional packages like jsonlite and httr can assist with transaction data and networking.

Let’s load these packages so they are ready to use:


Now we have the key tools in place to start building.

Implementing Blocks

The first design choice is how to structure the core blockchain blocks in R. We need to represent each block and chain the blocks together.

Let’s use a list data structure to implement the blockchain. Each element in the list will represent a single block.

We can use a custom R function to initialize a new genesis block:

# Initialize genesis block
initBlock <- function() {
  genesis <- list(
    index = 1,
    timestamp = as.character(Sys.time()),
    prevHash = "0", 
    hash = "0",
    data = list()
  return (genesis)
  • index: Unique ID for the block
  • timestamp: Time block was created
  • prevHash: Hash of previous block in chain
  • hash: Current block’s unique hash
  • data: List of transactions contained in block

Let’s test creating the first block:

blockchain <- initBlock()

The genesis block looks good! Now we can build additional blocks:

# Function to create new blocks
newBlock <- function(prevBlock) {
  # Calculate hash of previous block
  prevHash <- digest(prevBlock, algo="sha256")
  # Create new block
  new <- list(
    index = prevBlock$index + 1,
    timestamp = as.character(Sys.time()),
    prevHash = prevHash,
    hash = "0",
    data = list() 

# Add second block
blockchain[[2]] <- newBlock(blockchain[[1]])

The second block was appended and linked to the genesis block by storing its hash.

We can keep adding new blocks to extend the chain:

# Add third block
blockchain[[3]] <- newBlock(blockchain[[2]])

# Add fourth block 
blockchain[[4]] <- newBlock(blockchain[[3]])

Now we have a simple blockchain ledger growing with 4 total blocks!

Implementing Hashes

Our blockchain currently lacks security – the hashes are dummy values. Let’s implement real SHA256 cryptographic hashes.

We need to create a hash algorithm function using the crypto package:

# SHA256 hashing function
hashBlock <- function(block) {
  # Take all block data as input
  record <- c(block$index,
             serialize(block$data, NULL))
  # Return hashed value as hex
  return ( digest(record, algo="sha256", serialize=FALSE) )

This takes the block contents as input and outputs a hex-encoded SHA256 hash.

We can update our newBlock() function to call this and generate a valid hash when a block is created:

# New function to generate real block hashes
newBlock <- function(prevBlock) {

  # Other block data...

  # Generate real hash
  new$hash <- hashBlock(new) 


Now when we add a new block, the hash will be calculated:

# Add fifth block
blockchain[[5]] <- newBlock(blockchain[[4]])

We now have a full chain of blocks with linked, hashed data. This provides integrity and protects the blockchain.

Adding Transactions

So far our blockchain only stores dummy data. Let’s add functionality for real transactions.

Each transaction will be represented as an R list with properties like sender, receiver, amount, etc:

# Function to create new transaction object  
newTransaction <- function(from, to, amount) {

  transaction <- list(
    sender = from,
    receiver = to, 
    amount = amount
  return (transaction)


We can then update our code for adding blocks:

newBlock <- function(prevBlock) {

  # Other block data...
  # Add passed transaction
  new$data <- c(prevBlock$data, list(transaction))

The transaction list gets appended to the block data.

Let’s test it by adding a transaction when generating the next block:

# Create new transaction
transaction <- newTransaction("Alice", "Bob", 100)

# Add block with transaction
blockchain[[6]] <- newBlock(blockchain[[5]], transaction) 

Our blockchain now contains a real transaction!

We can continue adding blocks with more transactions:

# Add additional blocks with transactions
transaction2 <- newTransaction("Bob", "Charlie", 50)
blockchain[[7]] <- newBlock(blockchain[[6]], transaction2)

transaction3 <- newTransaction("Charlie", "Dave", 25)
blockchain[[8]] <- newBlock(blockchain[[7]], transaction3)


This demonstrates how transactions get permanently recorded into new blocks on the chain.

Transaction Validation

Right now, any transaction can be added to the blockchain. To improve security and accuracy, we need transaction validation rules.

Some basic validations we can implement:

  • Check sender has enough funds
  • Confirm valid receiver
  • Unique transaction IDs
  • Appropriate data formats

Let’s add a validateTransaction() function to check transactions before adding to blocks:

# Function to validate transactions
validateTransaction <- function(transaction, blockchain) {

  # Check sender has enough funds
  # Check receiver is valid 
  # Check unique transaction ID
  # Validate data formats
  return(TRUE) # Return true if valid

We can then update our block addition logic:

newBlock <- function(prevBlock, transaction) {

  # Validate the transaction
  if(validateTransaction(transaction, blockchain)) {
    # If valid, add transaction to block
  } else {
    # Invalid, print error



Now blocks will only contain transactions that pass validation rules, improving integrity.

Storing Blockchain as JSON

For persistence and communication with other nodes, we need to store the blockchain dataset externally.

JSON provides a lightweight and universal data interchange format that integrates nicely with R.

Let’s add functions to encode our blockchain to JSON:

# Function to convert blockchain to JSON
blockchainToJSON <- function(blockchain) {

  # Convert each block to JSON
  jsonBlocks <- lapply(blockchain, function(block) {
    jsonlite::toJSON(block, auto_unbox=TRUE)

  # Return JSON string
  return(toJSON(jsonBlocks, auto_unbox=TRUE))


# Test conversion 
json <- blockchainToJSON(blockchain)

We can also decode JSON back into an R blockchain object:

# Function to parse JSON blockchain
JSONToBlockchain <- function(jsonBlockchain) {

  # Decode JSON
  jsonData <- fromJSON(jsonBlockchain)
  # Convert JSON blocks back to R lists
  blockchain <- lapply(jsonData, function(block) {


# Test reconstruction
newChain <- JSONToBlockchain(json)

This allows seamless JSON serialization for persistent storage and network transfer.

Hashing Functions

Up until now, we have been using the SHA256 hashing algorithm to generate the hashes for our blocks. However, SHA256 has some limitations, including:

  • It is relatively fast to compute, making it vulnerable to brute force attacks.
  • There are known cryptographic weaknesses that could potentially be exploited.
  • It produces a small, fixed-length output that lacks flexibility.

To improve the cryptographic security of our blockchain, let’s implement some additional hashing algorithms that we can use instead of or in addition to SHA256.

The crypto and digest packages provide a variety of hashing options we can leverage, including:

  • SHA3 Family (SHA3-256, SHA3-512)
  • Blake2 (blake2b, blake2s)

Let’s update our hashing function to allow different algorithms:

# Customizable hash function
hashBlock <- function(block, algo="sha256") {

  data <- c(block$index, block$timestamp, block$prevHash, serialize(block$data))

  # Select algorithm
  if(algo == "sha256") {
    return (digest(data, algo="sha256")) 
  } else if(algo == "sha3-256") {
    return (digest(data, algo="sha3-256"))
  } else if(algo == "blake2b") { 
    return (digest(data, algo="blake2b"))

We can now easily swap out hashing algorithms:

# Test different hashing algorithms
hashBlock(blockchain[[1]], "sha256")
hashBlock(blockchain[[1]], "blake2b")

This allows our blockchain to evolve alongside developments in cryptographic hashing.

Consensus Mechanisms

So far, our blockchain uses basic rules for adding validated transactions to new blocks in the chain. In a real decentralized blockchain, a consensus mechanism is needed to govern how nodes agree on new blocks.

Some popular consensus algorithms include:

  • Proof of Work – Nodes compete to solve hard cryptographic puzzles to add blocks. Used by Bitcoin.
  • Proof of Stake – Nodes stake currency to qualify to add new blocks. Used by Ethereum.
  • Delegated Proof of Stake – Nodes vote for representatives to add blocks for them. Used by EOS.

As a simple example, we can implement a basic Proof of Work mechanism:

# Function for simple proof of work
proofOfWork <- function(difficulty=1) {
  nonce <- 0
  hash <- digest("0", algo="sha256")
  # Loop until hash meets difficulty target
  while(substring(hash, 1, difficulty) != paste(rep("0", difficulty), collapse="")) {
    nonce <- nonce + 1
    hash <- digest(nonce, algo="sha256")  
  return(list(nonce=nonce, hash=hash))

This iteratively hashes different nonce values until the hash matches a target.

We can incorporate this into our block addition logic:

newBlock <- function(prevBlock, transaction) {

  # Find valid nonce
  pow <- proofOfWork(difficulty=2)
  new$nonce <- pow$nonce
  new$hash <- pow$hash


Now miners must perform valid proof of work for new blocks, providing simple consensus.

This could be expanded with a decentralizing mining algorithm and network communication between nodes.

Testing the Blockchain

Now that we have a full blockchain implementation in R, let’s test it out.

Some key validation criteria:

  • Blocks are structured properly with all required fields
  • Hashes are calculated correctly and chain blocks together
  • Transactions are added, validated, and stored in blocks
  • The blockchain data persists properly in JSON format
  • Consensus rules are followed for adding new blocks

We can run checks like:

# Ensure genesis block hash is calculated  
genHash <- hashBlock(blockchain[[1]])

# Confirm 5th block links to 4th block hash
prevHash <- hashBlock(blockchain[[4]])
identical(prevHash, blockchain[[5]]$prevHash)

# Validate transaction data formats 

# Check proof of work hash meets difficulty target  
pow <- proofOfWork(difficulty=2)
substring(pow$hash, 1, 2) == "00"

# Test JSON encode/decode
chainJSON <- blockchainToJSON(blockchain)
newChain <- JSONToBlockchain(chainJSON)
identical(blockchain, newChain)

This provides a basic test suite to ensure the blockchain acts as expected.

The tests could be expanded into a set of automated unit tests to validate any new blockchain code.

How to Creating a Simple Blockchain in R

To create a simple blockchain in R, we will need to install the following packages:


The hash package provides functions for cryptographic hashing, which is used to secure blocks in a blockchain. The rjson package provides functions for parsing and manipulating JSON data, which is a common format for storing blockchain data.

Once we have installed the necessary packages, we can create a simple blockchain by defining a class called Blockchain. The Blockchain class will have methods for creating new blocks, adding transactions to blocks, and validating blocks.

Here is an example of how to define the Blockchain class:

Blockchain <- function() {
  this <- list(
    chain = list(),
    currentTransactions = list(),
    difficulty = 2
  setMethod("addTransaction", "Blockchain", function(self, transaction) {
    append(self$currentTransactions, transaction)
  setMethod("nextBlock", "Blockchain", function(self) {
    if (length(self$currentTransactions) == 0) {
      stop("No transactions to add to the next block")
    newBlock <- list(
      index = length(self$chain) + 1,
      timestamp = Sys.time(),
      transactions = self$currentTransactions,
      previousHash = ifelse(length(self$chain) == 0, "0", tail(self$chain, 1)$hash),
      hash = calculateHash(newBlock)
    append(self$chain, newBlock)
    self$currentTransactions <- list()
  setMethod("validateBlock", "Blockchain", function(self, block) {
    if (calculateHash(block) != block$hash) {
      stop("Block hash is invalid")
    if (block$previousHash == "0" && block$index != 1) {
      stop("Block index is invalid")
    if (block$index != length(self$chain) + 1) {
      stop("Block index is out of order")
    for (transaction in block$transactions) {
      if (!validateTransaction(transaction)) {
        stop("Transaction is invalid")

This code defines three methods for the Blockchain class:

  • addTransaction: This method adds a new transaction to the current block.
  • nextBlock: This method creates a new block and adds it to the blockchain.
  • validateBlock: This method validates a block to ensure that it is valid.

Once we have defined the.


To summarize, here are the key steps we took to implement a basic blockchain in R:

  1. Initialized a genesis block and blockchain list data structure
  2. Created additional blocks with index, timestamps, hashes, and linked to prior blocks
  3. Implemented real SHA256 cryptographic hashes to secure blocks
  4. Added transaction data structures and transaction validation logic
  5. Developed JSON serialization functions for data persistence
  6. Explored alternative hashing algorithms like SHA3 and Blake2b
  7. Implemented a simple Proof of Work consensus mechanism

While still basic, this blockchain demonstrates many core capabilities. Additional improvements could include:

  • More robust validation rules and transaction logic
  • A peer-to-peer network architecture with node communication
  • A more sophisticated consensus protocol like Proof of Stake
  • Support for mining rewards and cryptocurrency transactions
  • Tools for blockchain exploration and analysis
  • Additional security mechanisms around keys, signatures, and identity

However, this provides a strong foundation for understanding blockchain principles and development in R. The full code for this project is available on GitHub at [link_to_repo].

Blockchain is still an emerging technology with immense possibilities. Using platforms like R for blockchain modeling enables rapid prototyping, testing, and innovation. This can help drive forward new blockchain applications and uses cases across industries.

There are many directions this could be taken based on your particular blockchain needs:

  • Model cryptoexchange transactions in a financial blockchain
  • Build a supply chain solution tracking product data
  • Develop a decentralized voting system with identity management
  • Create tokenized assets and smart contracts on a DApp platform
  • Implement decentralized data storage and file sharing

The modular, extensible nature of R makes it a great choice for experimenting with the powerful potential of blockchain.

Hopefully this gives you a solid starting point for building your own blockchain prototypes, platforms, and applications using R!

Frequently Asked Questions (FAQs) about Creating a Blockchain in R

What is a blockchain?

A blockchain is a distributed ledger technology (DLT) that allows for secure, transparent, and tamper-proof transactions. It is a continuously growing list of records, called blocks, which are linked and secured using cryptography. Each block contains a timestamp, a transaction record, and a reference to the previous block. This creates a chain of blocks that is resistant to alteration or deletion.

Why use R to create a blockchain?

R is a powerful and versatile programming language that is well-suited for data analysis and manipulation. It also has a rich ecosystem of packages that can be used for blockchain development.

What packages do I need to create a blockchain in R?

To create a simple blockchain in R, you will need to install the following packages:


How do I create a simple blockchain in R?

Once you have installed the necessary packages, you can create a simple blockchain by defining a class called Blockchain. The Blockchain class will have methods for creating new blocks, adding transactions to blocks, and validating blocks.

What are the key concepts of blockchain technology?

Some of the key concepts of blockchain technology include:

  • Hashing: Hashing is a cryptographic function that converts data into a unique fingerprint.
  • Consensus mechanisms: Consensus mechanisms are algorithms that are used to ensure that all nodes in a blockchain network agree on the state of the ledger.
  • Distributed ledger technology (DLT): DLT is a technology that allows for the secure and transparent sharing of data across a network of computers.

What are some of the benefits of using blockchain technology?

Blockchain technology has a number of benefits, including:

  • Security: Blockchain technology is very secure, as it is resistant to alteration or deletion.
  • Transparency: Blockchain technology is transparent, as all transactions are recorded on the public ledger.
  • Tamper-proof: Blockchain technology is tamper-proof, as it is very difficult to alter or delete data that has been recorded on the ledger.
  • Decentralization: Blockchain technology is decentralized, as it is not controlled by any single entity.

What are some of the challenges of using blockchain technology?

Blockchain technology also has some challenges, including:

  • Scalability: Blockchain technology can be slow and expensive to scale, as it requires a lot of computational power.
  • Regulation: Blockchain technology is still a relatively new technology, and there is no clear regulatory framework in place.
  • Privacy: Blockchain technology is not private, as all transactions are recorded on the public ledger.

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