Program Architecture

Summary #

  • If your data accounts are too large for the Stack, wrap them in Box to allocate them to the Heap
  • Use Zero-Copy to deal with accounts that are too large for Box (< 10MB)
  • The size and the order of fields in an account matter; put the variable length fields at the end
  • Solana can process in parallel, but you can still run into bottlenecks; be mindful of "shared" accounts that all users interacting with the program have to write to

Lesson #

Program Architecture is what separates the hobbyist from the professional. Crafting performant programs has more to do with system design than it does with the code. And you, as the designer, need to think about:

  1. What your code needs to do
  2. What possible implementations there are
  3. What are the tradeoffs between different implementations

These questions are even more important when developing for a blockchain. Not only are resources more limited than in a typical computing environment, you're also dealing with people's assets.

We'll leave most of the asset handling discussion to security course lesson, but it's important to note the nature of resource limitations in Solana development. There are, of course, limitations in a typical development environment, but there are limitations unique to blockchain and Solana development such as how much data can be stored in an account, the cost to store that data, and how many compute units are available per transaction. You, the program designer, have to be mindful of these limitations to create programs that are affordable, fast, safe, and functional. Today we will be delving into some of the more advanced considerations that should be taken when creating Solana programs.

Dealing With Large Accounts #

In modern application programming, we don't often have to think about the size of the data structures we are using. Do you want to make a string? You can put a 4000-character limit on it if you want to avoid abuse, but it's probably not an issue. Want an integer? They're pretty much always 32-bit for convenience.

In high-level languages, you are in the data-land-o-plenty! Now, in Solana land, we pay per byte stored (rent) and have limits on heap, stack, and account sizes. We have to be a little more crafty with our bytes. There are two main concerns we are going to be looking at in this section:

  1. Since we pay-per-byte, we generally want to keep our footprint as small as possible. We will delve more into optimization in another section, but we'll introduce you to the concept of data sizes here.

  2. When operating on larger data, we run into Stack and Heap constraints - to get around these, we'll look at using Box and Zero-Copy.

Sizes #

In Solana, a transaction's fee payer pays for each byte stored onchain. This is called rent.

Info

Rent is a bit of a misnomer since it never gets permanently taken. Once you deposit rent into the account, that data can stay there forever, or you can get refunded the rent if you close the account. Previously, rent was paid in intervals, similar to traditional rent, but now there's an enforced minimum balance for rent exemption. You can read more about it in the Solana documentation.

Putting data on the blockchain can be expensive, which is why NFT attributes and associated files, like images, are stored offchain. The goal is to strike a balance between keeping your program highly functional and ensuring that users aren't discouraged by the cost of storing data onchain.

The first step in optimizing for space in your program is understanding the size of your structs. Below is a helpful reference from the Anchor Book.

TypesSpace in bytesDetails/Example
bool1would only require 1 bit but still uses 1 byte
u8/i81
u16/i162
u32/i324
u64/i648
u128/i12816
[T;amount]space(T) * amounte.g. space([u16;32]) = 2 * 32 = 64
Pubkey32
Vec<T>4 + (space(T) * amount)Account size is fixed so account should be initialized with sufficient space from the beginning
String4 + length of string in bytesAccount size is fixed so account should be initialized with sufficient space from the beginning
Option<T>1 + (space(T))
Enum1 + Largest Variant Sizee.g. Enum { A, B { val: u8 }, C { val: u16 } } -> 1 + space(u16) = 3
f324serialization will fail for NaN
f648serialization will fail for NaN

Knowing these, start thinking about little optimizations you might take in a program. For example, if you have an integer field that will only ever reach 100, don't use a u64/i64, use a u8. Why? Because a u64 takes up 8 bytes, with a max value of 2^64 or 1.84 * 10^19. That's a waste of space since you only need to accommodate numbers up to 100. A single byte will give you a max value of 255 which, in this case, would be sufficient. Similarly, there's no reason to use i8 if you'll never have negative numbers.

Be careful with small number types, though. You can quickly run into unexpected behavior due to overflow. For example, a u8 type that is iteratively incremented will reach 255 and then go back to 0 instead of 256. For more real-world context, look up the Y2K bug.

If you want to read more about Anchor sizes, take a look at Sec3's blog post about it .

Box #

Now that you know a little bit about data sizes, let's skip forward and look at a problem you'll run into if you want to deal with larger data accounts. Say you have the following data account:

#[account]
pub struct SomeBigDataStruct {
    pub big_data: [u8; 5000],
}
 
#[derive(Accounts)]
pub struct SomeFunctionContext<'info> {
    pub some_big_data: Account<'info, SomeBigDataStruct>,
}

If you try to pass SomeBigDataStruct into the function with the SomeFunctionContext context, you'll run into the following compiler warning:

// Stack offset of XXXX exceeded max offset of 4096 by XXXX bytes, please minimize large stack variables

And if you try to run the program it will just hang and fail.

Why is this?

It has to do with the Stack. Every time you call a function in Solana it gets a 4KB stack frame. This is static memory allocation for local variables. This is where that entire SomeBigDataStruct gets stored in memory and since 5000 bytes, or 5KB, is greater than the 4KB limit, it will throw a stack error. So how do we fix this?

The answer is the Box<T> type!

#[account]
pub struct SomeBigDataStruct {
    pub big_data: [u8; 5000],
}
 
#[derive(Accounts)]
pub struct SomeFunctionContext<'info> {
    pub some_big_data: Box<Account<'info, SomeBigDataStruct>>, // <- Box Added!
}

In Anchor, Box<T> is used to allocate the account to the Heap, not the Stack. Which is great since the Heap gives us 32KB to work with. The best part is you don't have to do anything different within the function. All you need to do is add Box<…> around all of your big data accounts.

But Box is not perfect. You can still overflow the stack with sufficiently large accounts. We'll learn how to fix this in the next section.

Zero Copy #

Okay, so now you can deal with medium-sized accounts using Box. But what if you need to use really big accounts like the max size of 10MB? Take the following as an example:

#[account]
pub struct SomeReallyBigDataStruct {
    pub really_big_data: [u128; 1024], // 16,384 bytes
}

This account will make your program fail, even wrapped in a Box. To get around this, you can use zero_copy and AccountLoader. Simply add zero_copy to your account struct, add zero as a constraint in the account validation struct, and wrap the account type in the account validation struct in an AccountLoader.

#[account(zero_copy)]
pub struct SomeReallyBigDataStruct {
    pub really_big_data: [u128; 1024], // 16,384 bytes
}
 
pub struct ConceptZeroCopy<'info> {
    #[account(zero)]
    pub some_really_big_data: AccountLoader<'info, SomeReallyBigDataStruct>,
}

Note: In older versions of anchor < 0.28.0 you may have to use: zero_copy(unsafe)) ( Thanks @0xk2_ for this find )

To understand what's happening here, take a look at the rust Anchor documentation

Info

Other than being more efficient, the most salient benefit [zero_copy] provides the ability to define account types larger than the max stack or heap size. When using borsh, the account has to be copied and deserialized into a new data structure and thus is constrained by stack and heap limits imposed by the BPF VM. With zero copy deserialization, all bytes from the account's backing RefCell<&mut [u8]> are simply re-interpreted as a reference to the data structure. No allocations or copies are necessary. Hence the ability to get around stack and heap limitations.

Basically, your program never actually loads zero-copy account data into the stack or heap. It instead gets pointer access to the raw data. The AccountLoader ensures this doesn't change too much about how you interact with the account from your code.

There are a couple of caveats using zero_copy. First, you cannot use the init constraint in the account validation struct like you may be used to. This is due to there being a CPI limit on accounts bigger than 10KB.

pub struct ConceptZeroCopy<'info> {
    #[account(zero, init)] // <- Can't do this
    pub some_really_big_data: AccountLoader<'info, SomeReallyBigDataStruct>,
}

Instead, your client has to create a large account and pay for its rent in a separate instruction.

const accountSize = 16_384 + 8;
const ix = anchor.web3.SystemProgram.createAccount({
  fromPubkey: wallet.publicKey,
  newAccountPubkey: someReallyBigData.publicKey,
  lamports:
    await program.provider.connection.getMinimumBalanceForRentExemption(
      accountSize,
    ),
  space: accountSize,
  programId: program.programId,
});
 
const txHash = await program.methods
  .conceptZeroCopy()
  .accounts({
    owner: wallet.publicKey,
    someReallyBigData: someReallyBigData.publicKey,
  })
  .signers([someReallyBigData])
  .preInstructions([ix])
  .rpc();

The second caveat is that you'll have to call one of the following methods from inside your rust instruction handler to load the account:

  • load_init when first initializing an account (this will ignore the missing account discriminator that gets added only after the user's instruction code)
  • load when the account is not mutable
  • load_mut when the account is mutable

For example, if you wanted to init and manipulate the SomeReallyBigDataStruct from above, you'd call the following in the function

let some_really_big_data = &mut ctx.accounts.some_really_big_data.load_init()?;

After you do that, then you can treat the account like normal! Go ahead and experiment with this in the code yourself to see everything in action!

For a better understanding of how this all works, Solana put together a really nice video and code explaining Box and Zero-Copy in vanilla Solana.

Dealing with Accounts #

Now that you know the nuts and bolts of space consideration on Solana, let's look at some higher-level considerations. In Solana, everything is an account, so for the next couple sections, we'll look at some account architecture concepts.

Data Order #

This first consideration is fairly simple. As a rule of thumb, keep all variable length fields at the end of the account. Take a look at the following:

#[account] // Anchor hides the account discriminator
pub struct BadState {
    pub flags: Vec<u8>, // 0x11, 0x22, 0x33 ...
    pub id: u32         // 0xDEAD_BEEF
}

The flags field is variable length. This makes looking up a specific account by the id field very difficult, as an update to the data in flags changes the location of id on the memory map.

To make this more clear, observe what this account's data looks like onchain when flags has four items in the vector vs eight items. If you were to call solana account ACCOUNT_KEY you'd get a data dump like the following: solana account ACCOUNT_KEY you'd get a data dump like the following:

0000:   74 e4 28 4e    d9 ec 31 0a  -> Account Discriminator (8)
0008:   04 00 00 00    11 22 33 44  -> Vec Size (4) | Data 4*(1)
0010:   DE AD BE EF                 -> id (4)
 
--- vs ---
 
0000:   74 e4 28 4e    d9 ec 31 0a  -> Account Discriminator (8)
0008:   08 00 00 00    11 22 33 44  -> Vec Size (8) | Data 4*(1)
0010:   55 66 77 88    DE AD BE EF  -> Data 4*(1) | id (4)

In both cases, the first eight bytes are the Anchor account discriminator. In the first case, the next four bytes represent the size of the flags vector, followed by another four bytes for the data, and finally the id field's data.

In the second case, the id field moved from address 0x0010 to 0x0014 because the data in the flags field took up four more bytes.

The main problem with this is lookup. When you query Solana, you use filters that look at the raw data of an account. These are called a memcmp filters, or memory compare filters. You give the filter an offset and bytes, and the filter then looks directly at the memory, offset from the start by the offset you provide, and compares the bytes in memory to the bytes you provide.

For example, you know that the flags struct will always start at the address 0x0008 since the first 8 bytes contain the account discriminator. Querying all accounts where the flags length is equal to four is possible because we know that the four bytes at 0x0008 represent the length of the data in flags. Since the account discriminator is

const states = await program.account.badState.all([
  {
    memcmp: {
      offset: 8,
      bytes: bs58.encode([0x04]),
    },
  },
]);

However, if you wanted to query by the id, you wouldn't know what to put for the offset since the location of id is variable based on the length of flags. That doesn't seem very helpful. IDs are usually there to help with flags. That doesn't seem very helpful. IDs are usually there to help with queries! The simple fix is to flip the order.

#[account] // Anchor hides the account discriminator
pub struct GoodState {
    pub id: u32         // 0xDEAD_BEEF
    pub flags: Vec<u8>, // 0x11, 0x22, 0x33 ...
}

With variable length fields at the end of the struct, you can always query accounts based on all the fields up to the first variable length field. To echo the beginning of this section: As a rule of thumb, keep all variable length structs at the end of the account.

Account Flexibility and Future-Proofing #

When developing Solana programs, it's crucial to design your account structures with future upgrades and backward compatibility in mind. Solana offers powerful features like account resizing and Anchor's InitSpace attribute to handle these challenges efficiently. Let's explore a more dynamic and flexible approach using a game state example:

use anchor_lang::prelude::*;
 
#[account]
#[derive(InitSpace)]
pub struct GameState {  // V1
    pub version: u8,
    pub health: u64,
    pub mana: u64,
    pub experience: Option<u64>,
    #[max_len(50)]
    pub event_log: Vec<String>
}

In this GameState, we have:

  • A version field to track account structure changes
  • Basic character attributes (health, mana)
  • An experience field as Option<u64> for backward compatibility
  • An event_log with a specified maximum length

Key advantages of this approach:

  1. Automatic Space Calculation: The InitSpace attribute automatically calculates the required account space.
  2. Versioning: The version field allows for easy identification of account structure versions.
  3. Flexible Fields: Using Option<T> for new fields maintains compatibility with older versions.
  4. Defined Limits: The max_len attribute on Vec fields clearly communicates size constraints.

When you need to upgrade your account structure, such as increasing the length of event_log or adding new fields, you can use a single upgrade instruction with Anchor's realloc constraint:

  1. Update the GameState struct with new fields or increased max_len attributes:

    #[account]
    #[derive(InitSpace)]
    pub struct GameState {
        pub version: u8,
        pub health: u64,
        pub mana: u64,
        pub experience: Option<u64>,
        #[max_len(100)]  // Increased from 50
        pub event_log: Vec<String>,
        pub new_field: Option<u64>, // Added new field
    }
  2. Use a single UpgradeGameState context for all upgrades with Anchor's realloc constraint for GameState:

    #[derive(Accounts)]
    pub struct UpgradeGameState<'info> {
        #[account(
            mut,
            realloc = GameState::INIT_SPACE,
            realloc::payer = payer,
            realloc::zero = false,
        )]
        pub game_state: Account<'info, GameState>,
        #[account(mut)]
        pub payer: Signer<'info>,
        pub system_program: Program<'info, System>,
    }
  3. Implement the upgrade logic in a single function:

    pub fn upgrade_game_state(ctx: Context<UpgradeGameState>) -> Result<()> {
     let game_state = &mut ctx.accounts.game_state;
     
     match game_state.version {
         1 => {
             game_state.version = 2;
             game_state.experience = Some(0);
             msg!("Upgraded to version 2");
         },
         2 => {
             game_state.version = 3;
             game_state.new_field = Some(0);
             msg!("Upgraded to version 3");
         },
         _ => return Err(ErrorCode::AlreadyUpgraded.into()),
     }
     
     Ok(())
     }

The example to demonstrate this approach:

use anchor_lang::prelude::*;
 
#[account]
#[derive(InitSpace)]
pub struct GameState {
    pub version: u8,
    pub health: u64,
    pub mana: u64,
    pub experience: Option<u64>,
    #[max_len(100)]  // Increased from 50
    pub event_log: Vec<String>,
    pub new_field: Option<u64>,
}
 
#[derive(Accounts)]
pub struct UpgradeGameState<'info> {
    #[account(
        mut,
        realloc = GameState::INIT_SPACE,
        realloc::payer = payer,
        realloc::zero = false,
    )]
    pub game_state: Account<'info, GameState>,
    #[account(mut)]
    pub payer: Signer<'info>,
    pub system_program: Program<'info, System>,
}
 
#[program]
pub mod your_program {
    use super::*;
 
    // ... other instructions ...
 
    pub fn upgrade_game_state(ctx: Context<UpgradeGameState>) -> Result<()> {
        let game_state = &mut ctx.accounts.game_state;
 
        match game_state.version {
            1 => {
                game_state.version = 2;
                game_state.experience = Some(0);
                msg!("Upgraded to version 2");
            },
            2 => {
                game_state.version = 3;
                game_state.new_field = Some(0);
                msg!("Upgraded to version 3");
            },
            _ => return Err(ErrorCode::AlreadyUpgraded.into()),
        }
 
        Ok(())
    }
}
 
#[error_code]
pub enum ErrorCode {
    #[msg("Account is already at the latest version")]
    AlreadyUpgraded,
}

This approach:

  • Uses the Anchor's realloc constraint to automatically handle account resizing.
  • The InitSpace derive macro automatically implements the Space trait for the GameState struct. This trait includes the INIT_SPACE associated constant , which calculates the total space required for the account.
  • Designates a payer for any additional rent with realloc::payer = payer.
  • Keeps existing data with realloc::zero = false.
Info

Account data can be increased within a single call by up to solana_program::entrypoint::MAX_PERMITTED_DATA_INCREASE bytes.

Memory used to grow is already zero-initialized upon program entrypoint and re-zeroing it wastes compute units. If within the same call a program reallocs from larger to smaller and back to larger again the new space could contain stale data. Pass true for zero_init in this case, otherwise compute units will be wasted re-zero-initializing.

Caution

While account resizing is powerful, use it judiciously. Consider the trade-offs between frequent resizing and initial allocation based on your specific use case and expected growth patterns.

  • Always ensure your account remains rent-exempt before resizing.
  • The payer of the transaction is responsible for providing the additional lamports.
  • Consider the cost implications of frequent resizing in your program design.

In native Rust, you can resize accounts using the realloc() method. For more details, refer to the account resizing program.

Data Optimization #

The idea here is to be aware of wasted bits. For example, if you have a field that represents the month of the year, don't use a u64. There will only ever that represents the month of the year, don't use a u64. There will only ever be 12 months. Use a u8. Better yet, use a u8 Enum and label the months.

To get even more aggressive on bit savings, be careful with booleans. Look at the below struct composed of eight boolean flags. While a boolean can be represented as a single bit, borsh deserialization will allocate an entire byte to each of these fields. That means that eight booleans wind up being eight bytes instead of eight bits, an eight times increase in size.

#[account]
pub struct BadGameFlags { // 8 bytes
    pub is_frozen: bool,
    pub is_poisoned: bool,
    pub is_burning: bool,
    pub is_blessed: bool,
    pub is_cursed: bool,
    pub is_stunned: bool,
    pub is_slowed: bool,
    pub is_bleeding: bool,
}

To optimize this, you could have a single field as a u8. Then you can use bitwise operations to look at each bit and determine if it's "toggled on" or not.

const IS_FROZEN_FLAG: u8 = 1 << 0;
const IS_POISONED_FLAG: u8 = 1 << 1;
const IS_BURNING_FLAG: u8 = 1 << 2;
const IS_BLESSED_FLAG: u8 = 1 << 3;
const IS_CURSED_FLAG: u8 = 1 << 4;
const IS_STUNNED_FLAG: u8 = 1 << 5;
const IS_SLOWED_FLAG: u8 = 1 << 6;
const IS_BLEEDING_FLAG: u8 = 1 << 7;
const NO_EFFECT_FLAG: u8 = 0b00000000;
#[account]
pub struct GoodGameFlags { // 1 byte
    pub status_flags: u8,
}

That saves you 7 bytes of data! The tradeoff, of course, is now you have to do bitwise operations. But that's worth having in your toolkit.

Indexing #

This last account concept is fun and illustrates the power of PDAs. When creating program accounts, you can specify the seeds used to derive the PDA. This is exceptionally powerful since it lets you derive your account addresses rather than store them.

The best example of this is good ‘ol Associated Token Accounts (ATAs)!

function findAssociatedTokenAddress(
  walletAddress: PublicKey,
  tokenMintAddress: PublicKey,
): PublicKey {
  return PublicKey.findProgramAddressSync(
    [
      walletAddress.toBuffer(),
      TOKEN_PROGRAM_ID.toBuffer(),
      tokenMintAddress.toBuffer(),
    ],
    SPL_ASSOCIATED_TOKEN_ACCOUNT_PROGRAM_ID,
  )[0];
}

This is how most of your SPL tokens are stored. Rather than keep a database table of SPL token account addresses, the only thing you have to know is your wallet address and the mint address. The ATA address can be calculated by hashing these together and viola! You have your token account address.

Depending on the seeding you can create all sorts of relationships:

  • One-Per-Program (Global Account) - If you create an account with a determined seeds=[b"ONE PER PROGRAM"], only one can ever exist for that seed in that program. For example, if your program needs a lookup table, you could seed it with seeds=[b"Lookup"]. Just be careful to provide appropriate access restrictions.
  • One-Per-Owner - Say you're creating a video game player account and you only want one player account per wallet. Then you'd seed the account with seeds=[b"PLAYER", owner.key().as_ref()]. This way, you'll always know where to look for a wallet's player account and there can only ever be one of
  • One-Per-Owner - Say you're creating a video game player account and you only want one player account per wallet. Then you'd seed the account with seeds=[b"PLAYER", owner.key().as_ref()]. This way, you'll always know where to look for a wallet's player account and there can only ever be one of them.
  • Multiple-Per-Owner - Okay, but what if you want multiple accounts per wallet? Say you want to mint podcast episodes. Then you could seed your Podcast account like this: seeds=[b"Podcast", owner.key().as_ref(), episode_number.to_be_bytes().as_ref()]. Now, if you want to look up episode 50 from a specific wallet, you can! And you can have as many episodes as you want per owner.
  • One-Per-Owner-Per-Account - This is effectively the ATA example we saw above. Where we have one token account per wallet and mint account. seeds=[b"Mock ATA", owner.key().as_ref(), mint.key().as_ref()]

From there you can mix and match in all sorts of clever ways! But the preceding list should give you enough to get started.

The big benefit of really paying attention to this aspect of design is answering the ‘indexing' problem. Without PDAs and seeds, all users would have to keep track of all of the addresses of all of the accounts they've ever used. This isn't feasible for users, so they'd have to depend on a centralized entity to store their addresses in a database. In many ways that defeats the purpose of a globally distributed network. PDAs are a much better solution.

To drive this all home, here's an example of a scheme from a production podcasting program. The program needed the following accounts:

  • Channel Account
    • Name
    • Episodes Created (u64)
  • Podcast Account(s)
    • Name
    • Audio URL

To properly index each account address, the accounts use the following seeds:

// Channel Account
seeds=[b"Channel", owner.key().as_ref()]
 
// Podcast Account
seeds=[b"Podcast", channel_account.key().as_ref(), episode_number.to_be_bytes().as_ref()]

You can always find the channel account for a particular owner. And since the channel stores the number of episodes created, you always know the upper bound of where to search for queries. Additionally, you always know what index to create a new episode at: index = episodes_created.

Podcast 0: seeds=[b"Podcast", channel_account.key().as_ref(), 0.to_be_bytes().as_ref()]
Podcast 1: seeds=[b"Podcast", channel_account.key().as_ref(), 1.to_be_bytes().as_ref()]
Podcast 2: seeds=[b"Podcast", channel_account.key().as_ref(), 2.to_be_bytes().as_ref()]
...
Podcast X: seeds=[b"Podcast", channel_account.key().as_ref(), X.to_be_bytes().as_ref()]

Dealing with Concurrency #

One of the main reasons to choose Solana for your blockchain environment is its parallel transaction execution. That is, Solana can run transactions in parallel as long as those transactions aren't trying to write data to the same account. This improves program throughput out of the box, but with some proper planning, you can avoid concurrency issues and really boost your program's performance.

Shared Accounts #

If you've been around crypto for a while, you may have experienced a big NFT mint event. A new NFT project is coming out, everyone is really excited about it, and then the candymachine goes live. It's a mad dash to click accept transaction as fast as you can. If you were clever, you may have written a bot to enter the transactions faster than the website's UI could. This mad rush to mint creates a lot of failed transactions. But why? Because everyone is trying to write data to the same Candy Machine account.

Take a look at a simple example:

Alice and Bob are trying to pay their friends Carol and Dean respectively. All four accounts change, but neither depends on other. Both transactions can run at the same time.

Alice -- pays --> Carol
 
Bob ---- pays --> Dean

But if Alice and Bob both try to pay Carol at the same time, they'll run into issues.

Alice -- pays --> |
                      -- > Carol
Bob   -- pays --- |

Since both of these transactions write to Carol's token account, only one of them can go through at a time. Fortunately, Solana is very fast, so it'll probably seem like they get paid at the same time. But what happens if more than just Alice and Bob try to pay Carol?

Alice -- pays --> |
                      -- > Carol
x1000 -- pays --- |
Bob   -- pays --- |

What if 1000 people try to pay Carol at the same time? Each of the 1000 instructions will be queued up to run in sequence. To some of them, the payment will seem like it went through right away. They'll be the lucky ones whose instruction got included early. But some of them will end up waiting quite a bit. And for some, their transaction will simply fail.

While it seems unlikely for 1000 people to pay Carol at the same time, it's actually very common to have an event, like an NFT mint, where many people are trying to write data to the same account all at once.

Imagine you create a super popular program and you want to take a fee on every transaction you process. For accounting reasons, you want all of those fees to go to one wallet. With that setup, on a surge of users, your protocol will become slow and or become unreliable. Not great. So what's the solution? Separate the data transaction from the fee transaction.

For example, imagine you have a data account called DonationTally. Its only function is to record how much you have donated to a specific hard-coded community wallet.

#[account]
pub struct DonationTally {
    is_initialized: bool,
    lamports_donated: u64,
    lamports_to_redeem: u64,
    owner: Pubkey,
}

First, let's look at the suboptimal solution.

pub fn run_concept_shared_account_bottleneck(ctx: Context<ConceptSharedAccountBottleneck>, lamports_to_donate: u64) -> Result<()> {
 
    let donation_tally = &mut ctx.accounts.donation_tally;
 
    if !donation_tally.is_initialized {
        donation_tally.is_initialized = true;
        donation_tally.owner = ctx.accounts.owner.key();
        donation_tally.lamports_donated = 0;
        donation_tally.lamports_to_redeem = 0;
    }
 
    let cpi_context = CpiContext::new(
        ctx.accounts.system_program.to_account_info(),
        Transfer {
            from: ctx.accounts.owner.to_account_info(),
            to: ctx.accounts.community_wallet.to_account_info(),
        });
    transfer(cpi_context, lamports_to_donate)?;
 
 
    donation_tally.lamports_donated = donation_tally.lamports_donated.checked_add(lamports_to_donate).unwrap();
    donation_tally.lamports_to_redeem = 0;
 
    Ok(())
}

You can see that the transfer to the hardcoded community_wallet happens in the same function that you update the tally information. This is the most straightforward solution, but if you run the tests for this section, you'll see a slowdown.

Now look at the optimized solution:

pub fn run_concept_shared_account(ctx: Context<ConceptSharedAccount>, lamports_to_donate: u64) -> Result<()> {
 
    let donation_tally = &mut ctx.accounts.donation_tally;
 
    if !donation_tally.is_initialized {
        donation_tally.is_initialized = true;
        donation_tally.owner = ctx.accounts.owner.key();
        donation_tally.lamports_donated = 0;
        donation_tally.lamports_to_redeem = 0;
    }
 
    let cpi_context = CpiContext::new(
        ctx.accounts.system_program.to_account_info(),
        Transfer {
            from: ctx.accounts.owner.to_account_info(),
            to: donation_tally.to_account_info(),
        });
    transfer(cpi_context, lamports_to_donate)?;
 
    donation_tally.lamports_donated = donation_tally.lamports_donated.checked_add(lamports_to_donate).unwrap();
    donation_tally.lamports_to_redeem = donation_tally.lamports_to_redeem.checked_add(lamports_to_donate).unwrap();
 
    Ok(())
}
 
pub fn run_concept_shared_account_redeem(ctx: Context<ConceptSharedAccountRedeem>) -> Result<()> {
    let transfer_amount: u64 = ctx.accounts.donation_tally.lamports_donated;
 
    // Decrease balance in donation_tally account
    **ctx.accounts.donation_tally.to_account_info().try_borrow_mut_lamports()? -= transfer_amount;
 
    // Increase balance in community_wallet account
    **ctx.accounts.community_wallet.to_account_info().try_borrow_mut_lamports()? += transfer_amount;
 
    // Reset lamports_donated and lamports_to_redeem
    ctx.accounts.donation_tally.lamports_to_redeem = 0;
 
    Ok(())
}

Here, in the run_concept_shared_account function, instead of transferring to the bottleneck, we transfer to the donation_tally PDA. This way, we're only the bottleneck, we transfer to the donation_tally PDA. This way, we're only effecting the donator's account and their PDA - so no bottleneck! Additionally, we keep an internal tally of how many lamports need to be redeemed, i.e. be transferred from the PDA to the community wallet at a later time. At some point in the future, the community wallet will go around and clean up all the straggling lamports. It's important to note that anyone should be able to sign for the redeem function since the PDA has permission over itself.

If you want to avoid bottlenecks at all costs, this is one way to tackle them. Ultimately this is a design decision and the simpler, less optimal solution might be okay for some programs. But if your program is going to have high traffic, it's worth trying to optimize. You can always run a simulation to see your worst, best, and median cases.

See it in Action #

All of the code snippets from this lesson are part of a Solana program we created to illustrate these concepts. Each concept has an accompanying program and test file. For example, the Sizes concept can be found in:

program - programs/architecture/src/concepts/sizes.rs

test - cd tests/sizes.ts

Now that you've read about each of these concepts, feel free to jump into the code to experiment a little. You can change existing values, try to break the program, and generally try to understand how everything works.

You can fork and/or clone this program from Github to get started. Before building and running the test suite, remember to update the lib.rs and Anchor.toml with your local program ID.

You can run the entire test suite or add .only to the describe call in a specific test file to only run that file's tests. Feel free to customize it and make it your own.

Conclusion #

We've talked about quite a few program architecture considerations: bytes, accounts, bottlenecks, and more. Whether you wind up running into any of these specific considerations or not, hopefully, the examples and discussion sparked some thought. At the end of the day, you're the designer of your system. Your job is to weigh the pros and cons of various solutions. Be forward-thinking, but be practical. There is no "one good way" to design anything. Just know the trade-offs.

Lab #

Let's use all of these concepts to create a simple, but optimized, RPG game engine in Solana. This program will have the following features:

  • Let users create a game (Game account) and become a "game master" (the authority over the game)
  • Game masters are in charge of their game's configuration
  • Anyone from the public can join a game as a player - each player/game combination will have a Player account
  • Players can spawn and fight monsters (Monster account) by spending action points; we'll use lamports as the action points
  • Spent action points go to a game's treasury as listed in the Game account

We'll walk through the tradeoffs of various design decisions as we go to give you a sense of why we do things. Let's get started!

1. Program Setup #

We'll build this from scratch. Start by creating a new Anchor project:

anchor init rpg
Info

This lab was created with Anchor version 0.30.1 in mind. If there are problems compiling, please refer to the solution code for the environment setup.

Next, run the command anchor keys sync that will automatically sync your program ID. This command updates the program IDs in your program files (including Anchor.toml) with the actual pubkey from the program keypair file.

Finally, let's scaffold out the program in the lib.rs file. Copy the following into your file before we get started:

lib.rs
use anchor_lang::prelude::*;
use anchor_lang::solana_program::log::sol_log_compute_units;
 
declare_id!("YOUR_KEY_HERE__YOUR_KEY_HERE");
 
#[program]
pub mod rpg {
    use super::*;
 
    pub fn create_game(ctx: Context<CreateGame>, max_items_per_player: u8) -> Result<()> {
        run_create_game(ctx, max_items_per_player)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn create_player(ctx: Context<CreatePlayer>) -> Result<()> {
        run_create_player(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn spawn_monster(ctx: Context<SpawnMonster>) -> Result<()> {
        run_spawn_monster(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn attack_monster(ctx: Context<AttackMonster>) -> Result<()> {
        run_attack_monster(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn deposit_action_points(ctx: Context<CollectActionPoints>) -> Result<()> {
        run_collect_action_points(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
}

2. Create Account Structures #

Now that our initial setup is ready, let's create our accounts. We'll have 3:

  1. Game - This account represents and manages a game. It includes the treasury for game participants to pay into and a configuration struct that game masters can use to customize the game. It should include the following fields:
    • game_master - effectively the owner/authority
    • treasury - the treasury to which players will send action points (we'll just be using lamports for action points)
    • action_points_collected - tracks the number of action points collected by the treasury
    • game_config - a config struct for customizing the game
  2. Player - A PDA account whose address is derived using the game account address and the player's wallet address as seeds. It has a lot of fields needed to track the player's game state:
    • player - the player's public key
    • game - the address of the corresponding game account
    • action_points_spent - the number of action points spent
    • action_points_to_be_collected - the number of action points that still need to be collected
    • status_flag - the player's status
    • experience - the player's experience
    • kills - number of monsters killed
    • next_monster_index - the index of the next monster to face
    • inventory - a vector of the player's inventory
  3. Monster - A PDA account whose address is derived using the game account address, the player's wallet address, and an index (the one stored as next_monster_index in the Player account).
    • player - the player the monster is facing
    • game - the game the monster is associated with
    • hitpoints - how many hit points the monster has left

This is the final project structure:

src/
├── constants.rs              # Constants used throughout the program
├── error/                    # Error module
   ├── errors.rs             # Custom error definitions
   └── mod.rs                # Module declarations for error handling
├── helpers.rs                # Helper functions used across the program
├── instructions/             # Instruction handlers for different game actions
   ├── attack_monster.rs     # Handles attacking a monster
   ├── collect_points.rs     # Handles collecting points
   ├── create_game.rs        # Handles game creation
   ├── create_player.rs      # Handles player creation
   ├── mod.rs                # Module declarations for instructions
   └── spawn_monster.rs      # Handles spawning a new monster
├── lib.rs                    # Main entry point for the program
└── state/                    # State module for game data structures
    ├── game.rs               # Game state representation
    ├── mod.rs                # Module declarations for state
    ├── monster.rs            # Monster state representation
    └── player.rs             # Player state representation

When added to the program, the accounts should look like this:

// ----------- ACCOUNTS ----------
 
// Inside `state/game.rs`
use anchor_lang::prelude::*;
#[account]
#[derive(InitSpace)]
pub struct Game {
    pub game_master: Pubkey,
    pub treasury: Pubkey,
    pub action_points_collected: u64,
    pub game_config: GameConfig,
}
 
#[derive(AnchorSerialize, AnchorDeserialize, Clone, InitSpace)]
pub struct GameConfig {
    pub max_items_per_player: u8
}
 
// Inside `state/player.rs`
use anchor_lang::prelude::*;
#[account]
#[derive(InitSpace)]
pub struct Player { // 8 bytes
    pub player: Pubkey,                 // 32 bytes
    pub game: Pubkey,                   // 32 bytes
 
    pub action_points_spent: u64,               // 8 bytes
    pub action_points_to_be_collected: u64,     // 8 bytes
 
    pub status_flag: u8,                // 8 bytes
    pub experience: u64,                 // 8 bytes
    pub kills: u64,                     // 8 bytes
    pub next_monster_index: u64,        // 8 bytes
 
    pub inventory: Vec<InventoryItem>,  // Max 8 items
}
 
#[derive(AnchorSerialize, AnchorDeserialize, Clone, InitSpace)]
pub struct InventoryItem {
    pub name: [u8; 32], // Fixed Name up to 32 bytes
    pub amount: u64
}
 
 
// Inside `state/monster.rs`
use anchor_lang::prelude::*;
#[account]
#[derive(InitSpace)]
pub struct Monster {
    pub player: Pubkey,
    pub game: Pubkey,
    pub hitpoints: u64,
}

There aren't a lot of complicated design decisions here, but let's talk about the inventory field on the Player struct. Since inventory is variable in length we decided to place it at the end of the account to make querying easier.

3. Create Ancillary Types #

The next thing we need to do is add some of the types our accounts reference that we haven't created yet.

Let's start with the game config struct. Technically, this could have gone in the Game account, but it's nice to have some separation and encapsulation. This struct should store the max items allowed per player.

game.rs
// ----------- GAME CONFIG ----------
// Inside `state/game.rs`
#[derive(AnchorSerialize, AnchorDeserialize, Clone, InitSpace)]
pub struct GameConfig {
    pub max_items_per_player: u8
}

Reallocating accounts in Solana programs has become more flexible due to Anchor's realloc account constraint and Solana's account resizing capabilities. While adding fields at the end of an account structure remains straightforward, modern practices allow for more adaptable designs:

  1. Use Anchor's realloc constraint in the #[account()] attribute to specify resizing parameters:

    #[account(
        mut,
        realloc = AccountStruct::INIT_SPACE,
        realloc::payer = payer,
        realloc::zero = false,
    )]
  2. Use Anchor's InitSpace attribute to automatically calculate account space.

  3. For variable-length fields like Vec or String, use the max_len attribute to specify maximum size.

  4. When adding new fields, consider using Option<T> for backward compatibility.

  5. Implement a versioning system in your account structure to manage different layouts.

  6. Ensure the payer account is mutable and a signer to cover reallocation costs:

    #[account(mut)]
    pub payer: Signer<'info>,

This approach allows for easier account structure evolution, regardless of where new fields are added, while maintaining efficient querying and serialization/deserialization through Anchor's built-in capabilities. It enables resizing accounts as needed, automatically handling rent-exemption.

Next, let's create our status flags. Remember, we could store our flags as booleans but we save space by storing multiple flags in a single byte. Each flag takes up a different bit within the byte. We can use the << operator to place 1 in the correct bit.

constants.rs
// ----------- STATUS ----------
 
pub const IS_FROZEN_FLAG: u8 = 1 << 0;
pub const IS_POISONED_FLAG: u8 = 1 << 1;
pub const IS_BURNING_FLAG: u8 = 1 << 2;
pub const IS_BLESSED_FLAG: u8 = 1 << 3;
pub const IS_CURSED_FLAG: u8 = 1 << 4;
pub const IS_STUNNED_FLAG: u8 = 1 << 5;
pub const IS_SLOWED_FLAG: u8 = 1 << 6;
pub const IS_BLEEDING_FLAG: u8 = 1 << 7;
 
pub const NO_EFFECT_FLAG: u8 = 0b00000000;
pub const ANCHOR_DISCRIMINATOR: usize = 8;
pub const MAX_INVENTORY_ITEMS: usize = 8;

Finally, let's create our InventoryItem. This should have fields for the item's name and amount.

player.rs
// ----------- INVENTORY ----------
 
// Inside `state/player.rs`
#[derive(AnchorSerialize, AnchorDeserialize, Clone, InitSpace)]
pub struct InventoryItem {
    pub name: [u8; 32], // Fixed Name up to 32 bytes
    pub amount: u64
}
 

4. Create a helper function for spending action points #

The last thing we'll do before writing the program's instructions is create a helper function for spending action points. Players will send action points (lamports) to the game treasury as payment for performing actions in the game.

Since sending lamports to a treasury requires writing data to that treasury account, we could easily end up with a performance bottleneck if many players are trying to write to the same treasury concurrently (See Dealing With Concurrency).

Instead, we'll send them to the player PDA account and create an instruction that will send the lamports from that account to the treasury in one fell swoop. This alleviates any concurrency issues since every player has their own account, but also allows the program to retrieve those lamports at any time.

helper.rs
// ----------- HELPER ----------
 
// Inside /src/helpers.rs
use anchor_lang::{prelude::*, system_program};
 
use crate::{error::RpgError, Player};
 
pub fn spend_action_points<'info>(
    action_points: u64,
    player_account: &mut Account<'info, Player>,
    player: &AccountInfo<'info>,
    system_program: &AccountInfo<'info>,
) -> Result<()> {
    player_account.action_points_spent = player_account
        .action_points_spent
        .checked_add(action_points)
        .ok_or(error!(RpgError::ArithmeticOverflow))?;
 
    player_account.action_points_to_be_collected = player_account
        .action_points_to_be_collected
        .checked_add(action_points)
        .ok_or(error!(RpgError::ArithmeticOverflow))?;
 
    system_program::transfer(
        CpiContext::new(
            system_program.to_account_info(),
            system_program::Transfer {
                from: player.to_account_info(),
                to: player_account.to_account_info(),
            },
        ),
        action_points,
    )?;
 
    msg!("Minus {} action points", action_points);
 
    Ok(())
}

5. Create Game #

Our first instruction will create the game account. Anyone can be a game_master and create their own game, but once a game has been created there are certain constraints.

For one, the game account is a PDA using its treasury wallet. This ensures that the same game_master can run multiple games if they use a different treasury for each.

Info

The treasury is a signer on the instruction. This is to make sure whoever is creating the game has the private keys to the treasury. This is a design decision rather than "the right way." Ultimately, it's a security measure to ensure the game master will be able to retrieve their funds.

create_game.rs
// ----------- CREATE GAME ----------
 
// Inside src/instructions/create_game.rs
use anchor_lang::prelude::*;
 
use crate::{error::RpgError, Game, ANCHOR_DISCRIMINATOR};
 
#[derive(Accounts)]
pub struct CreateGame<'info> {
    #[account(
        init,
        seeds = [b"GAME", treasury.key().as_ref()],
        bump,
        payer = game_master,
        space = ANCHOR_DISCRIMINATOR + Game::INIT_SPACE
    )]
    pub game: Account<'info, Game>,
    #[account(mut)]
    pub game_master: Signer<'info>,
    pub treasury: Signer<'info>,
    pub system_program: Program<'info, System>,
}
 
pub fn run_create_game(ctx: Context<CreateGame>, max_items_per_player: u8) -> Result<()> {
    if max_items_per_player == 0 {
        return Err(error!(RpgError::InvalidGameConfig));
    }
 
    let game = &mut ctx.accounts.game;
    game.game_master = ctx.accounts.game_master.key();
    game.treasury = ctx.accounts.treasury.key();
    game.action_points_collected = 0;
    game.game_config.max_items_per_player = max_items_per_player;
 
    msg!("Game created!");
    Ok(())
}

6. Create Player #

Our second instruction will create the player account. There are three tradeoffs to note about this instruction:

  1. The player account is a PDA account derived using the game and player wallet. This let's players participate in multiple games but only have one player account per game.
  2. We wrap the game account in a Box to place it on the heap, ensuring we don't max out the Stack.
  3. The first action any player makes is spawning themselves in, so we call spend_action_points. Right now we hardcode action_points_to_spend to be 100 lamports, but this could be something added to the game config in the future.
create_player.rs
// ----------- CREATE PLAYER ----------
 
// Inside src/instructions/create_player.rs
use anchor_lang::prelude::*;
 
use crate::{
    error::RpgError, helpers::spend_action_points, Game, Player, ANCHOR_DISCRIMINATOR,
    CREATE_PLAYER_ACTION_POINTS, NO_EFFECT_FLAG,
};
 
#[derive(Accounts)]
pub struct CreatePlayer<'info> {
    pub game: Box<Account<'info, Game>>,
    #[account(
        init,
        seeds = [
            b"PLAYER",
            game.key().as_ref(),
            player.key().as_ref()
        ],
        bump,
        payer = player,
        space = ANCHOR_DISCRIMINATOR + Player::INIT_SPACE
    )]
    pub player_account: Account<'info, Player>,
    #[account(mut)]
    pub player: Signer<'info>,
    pub system_program: Program<'info, System>,
}
 
pub fn run_create_player(ctx: Context<CreatePlayer>) -> Result<()> {
    let player_account = &mut ctx.accounts.player_account;
    player_account.player = ctx.accounts.player.key();
    player_account.game = ctx.accounts.game.key();
    player_account.status_flag = NO_EFFECT_FLAG;
    player_account.experience = 0;
    player_account.kills = 0;
 
    msg!("Hero has entered the game!");
 
    // Spend 100 lamports to create player
    let action_points_to_spend = CREATE_PLAYER_ACTION_POINTS;
 
    spend_action_points(
        action_points_to_spend,
        player_account,
        &ctx.accounts.player.to_account_info(),
        &ctx.accounts.system_program.to_account_info(),
    )
    .map_err(|_| error!(RpgError::InsufficientActionPoints))?;
 
    Ok(())
}

7. Spawn Monster #

Now that we have a way to create players, we need a way to spawn monsters for them to fight. This instruction will create a new Monster account whose address is a PDA derived from the game account, player account, and an index representing the number of monsters the player has faced. There are two design decisions here we should talk about:

  1. The PDA seeds let us keep track of all the monsters a player has spawned
  2. We wrap both the game and player accounts in Box to allocate them to the Heap
spawn_monster.rs
// ----------- SPAWN MONSTER ----------
 
// Inside src/instructions/spawn_monster.rs
use anchor_lang::prelude::*;
 
use crate::{helpers::spend_action_points, Game, Monster, Player, SPAWN_MONSTER_ACTION_POINTS, ANCHOR_DISCRIMINATOR};
 
#[derive(Accounts)]
pub struct SpawnMonster<'info> {
    pub game: Box<Account<'info, Game>>,
    #[account(
        mut,
        has_one = game,
        has_one = player,
    )]
    pub player_account: Box<Account<'info, Player>>,
    #[account(
        init,
        seeds = [
            b"MONSTER",
            game.key().as_ref(),
            player.key().as_ref(),
            player_account.next_monster_index.to_le_bytes().as_ref()
        ],
        bump,
        payer = player,
        space = ANCHOR_DISCRIMINATOR + Monster::INIT_SPACE
    )]
    pub monster: Account<'info, Monster>,
    #[account(mut)]
    pub player: Signer<'info>,
    pub system_program: Program<'info, System>,
}
 
pub fn run_spawn_monster(ctx: Context<SpawnMonster>) -> Result<()> {
    let monster = &mut ctx.accounts.monster;
    monster.player = ctx.accounts.player.key();
    monster.game = ctx.accounts.game.key();
    monster.hitpoints = 100;
 
    let player_account = &mut ctx.accounts.player_account;
    player_account.next_monster_index = player_account.next_monster_index.checked_add(1).unwrap();
 
    msg!("Monster Spawned!");
 
    // Spend 5 lamports to spawn monster
    let action_point_to_spend = SPAWN_MONSTER_ACTION_POINTS;
    spend_action_points(
        action_point_to_spend,
        player_account,
        &ctx.accounts.player.to_account_info(),
        &ctx.accounts.system_program.to_account_info(),
    )?;
 
    Ok(())
}

8. Attack Monster #

Now! Let's attack those monsters and start gaining some exp!

The logic here is as follows:

  • Players spend 1 action_point to attack and gain 1 experience
  • If the player kills the monster, their kill count goes up

As far as design decisions, we've wrapped each of the rpg accounts in Box to allocate them to the Heap. Additionally, we've used saturating_add when incrementing experience and kill counts.

The saturating_add function ensures the number will never overflow. Say the kills was a u8 and my current kill count was 255 (0xFF). If I killed another and added normally, e.g. 255 + 1 = 0 (0xFF + 0x01 = 0x00) = 0, the kill count would end up as 0. saturating_add will keep it at its max if it's about to would end up as 0. saturating_add will keep it at its max if it's about to roll over, so 255 + 1 = 255. The checked_add function will throw an error if it's about to overflow. Keep this in mind when doing math in Rust. Even though kills is a u64 and will never roll with it's current programming, it's good it's about to overflow. Keep this in mind when doing math in Rust. Even though kills is a u64 and will never roll with it's current programming, it's good practice to use safe math and consider roll-overs.

attack_monster.rs
// ----------- ATTACK MONSTER ----------
 
// Inside src/instructions/attack_monster.rs
use anchor_lang::prelude::*;
use crate::{helpers::spend_action_points, Monster, Player, ATTACK_ACTION_POINTS, error::RpgError};
 
#[derive(Accounts)]
pub struct AttackMonster<'info> {
    #[account(
        mut,
        has_one = player,
    )]
    pub player_account: Box<Account<'info, Player>>,
    #[account(
        mut,
        has_one = player,
        constraint = monster.game == player_account.game @ RpgError::GameMismatch
    )]
    pub monster: Box<Account<'info, Monster>>,
    #[account(mut)]
    pub player: Signer<'info>,
    pub system_program: Program<'info, System>,
}
 
pub fn run_attack_monster(ctx: Context<AttackMonster>) -> Result<()> {
    let player_account = &mut ctx.accounts.player_account;
    let monster = &mut ctx.accounts.monster;
 
    let hp_before_attack = monster.hitpoints;
    let hp_after_attack = monster.hitpoints.saturating_sub(1);
    let damage_dealt = hp_before_attack.saturating_sub(hp_after_attack);
    monster.hitpoints = hp_after_attack;
 
    if damage_dealt > 0 {
        msg!("Damage Dealt: {}", damage_dealt);
        player_account.experience = player_account.experience.saturating_add(1);
        msg!("+1 EXP");
 
        if hp_after_attack == 0 {
            player_account.kills = player_account.kills.saturating_add(1);
            msg!("You killed the monster!");
        }
    } else {
        msg!("Stop it's already dead!");
    }
 
    // Spend 1 lamport to attack monster
    let action_point_to_spend = ATTACK_ACTION_POINTS;
 
    spend_action_points(
        action_point_to_spend,
        player_account,
        &ctx.accounts.player.to_account_info(),
        &ctx.accounts.system_program.to_account_info()
    )?;
 
    Ok(())
}

9. Redeem to Treasury #

This is our last instruction. This instruction lets anyone send the spent action_points to the treasury wallet.

Again, let's box the rpg accounts and use safe math.

collect_points.rs
// ----------- REDEEM TO TREASUREY ----------
 
// Inside src/instructions/collect_points.rs
use anchor_lang::prelude::*;
use crate::{error::RpgError, Game, Player};
 
#[derive(Accounts)]
pub struct CollectActionPoints<'info> {
    #[account(
        mut,
        has_one = treasury @ RpgError::InvalidTreasury
    )]
    pub game: Box<Account<'info, Game>>,
    #[account(
        mut,
        has_one = game @ RpgError::PlayerGameMismatch
    )]
    pub player: Box<Account<'info, Player>>,
    #[account(mut)]
    /// CHECK: It's being checked in the game account
    pub treasury: UncheckedAccount<'info>,
    pub system_program: Program<'info, System>,
}
 
// Literally anyone who pays for the TX fee can run this command - give it to a clockwork bot
pub fn run_collect_action_points(ctx: Context<CollectActionPoints>) -> Result<()> {
    let transfer_amount = ctx.accounts.player.action_points_to_be_collected;
 
    // Transfer lamports from player to treasury
    let player_info = ctx.accounts.player.to_account_info();
    let treasury_info = ctx.accounts.treasury.to_account_info();
 
    **player_info.try_borrow_mut_lamports()? = player_info
        .lamports()
        .checked_sub(transfer_amount)
        .ok_or(RpgError::InsufficientFunds)?;
 
    **treasury_info.try_borrow_mut_lamports()? = treasury_info
        .lamports()
        .checked_add(transfer_amount)
        .ok_or(RpgError::ArithmeticOverflow)?;
 
    ctx.accounts.player.action_points_to_be_collected = 0;
 
    ctx.accounts.game.action_points_collected = ctx.accounts.game
        .action_points_collected
        .checked_add(transfer_amount)
        .ok_or(RpgError::ArithmeticOverflow)?;
 
    msg!("The treasury collected {} action points", transfer_amount);
 
    Ok(())
}

10. Error Handling #

Now, let's add all the errors that we have used till now in errors.rs file.

errors.rs
// ------------RPG ERRORS--------------
 
// Inside src/error/errors.rs
 
use anchor_lang::prelude::*;
 
#[error_code]
pub enum RpgError {
    #[msg("Arithmetic overflow occurred")]
    ArithmeticOverflow,
    #[msg("Invalid game configuration")]
    InvalidGameConfig,
    #[msg("Player not found")]
    PlayerNotFound,
    #[msg("Monster not found")]
    MonsterNotFound,
    #[msg("Insufficient action points")]
    InsufficientActionPoints,
    #[msg("Invalid attack")]
    InvalidAttack,
    #[msg("Maximum inventory size reached")]
    MaxInventoryReached,
    #[msg("Invalid item operation")]
    InvalidItemOperation,
    #[msg("Monster and player are not in the same game")]
    GameMismatch,
    #[msg("Invalid treasury account")]
    InvalidTreasury,
    #[msg("Player does not belong to the specified game")]
    PlayerGameMismatch,
    #[msg("Insufficient funds for transfer")]
    InsufficientFunds
}

11. Module Declarations #

We need to declare all the modules used in the project as follows:

 
// Inside src/error/mod.rs
pub mod errors;
pub use errors::RpgError;   // Expose the custom error type
 
// Inside src/instructions/mod.rs
pub mod attack_monster;
pub mod collect_points;
pub mod create_game;
pub mod create_player;
pub mod spawn_monster;
 
pub use attack_monster::*;   // Expose attack_monster functions
pub use collect_points::*;    // Expose collect_points functions
pub use create_game::*;       // Expose create_game functions
pub use create_player::*;     // Expose create_player functions
pub use spawn_monster::*;     // Expose spawn_monster functions
 
// Inside src/state/mod.rs
pub mod game;
pub mod monster;
pub mod player;
 
pub use game::*;      // Expose game state
pub use monster::*;   // Expose monster state
pub use player::*;    // Expose player state

12. Putting it all Together #

Now that all of our instruction logic is written, let's add these functions to actual instructions in the program. It can also be helpful to log compute units for each instruction.

lib.rs
 
// Insider src/lib.rs
use anchor_lang::prelude::*;
use anchor_lang::solana_program::log::sol_log_compute_units;
 
mod state;
mod instructions;
mod constants;
mod helpers;
mod error;
 
use state::*;
use constants::*;
use instructions::*;
 
declare_id!("5Sc3gJv4tvPiFzE75boYMJabbNRs44zRhtT23fLdKewz");
 
#[program]
pub mod rpg {
    use super::*;
 
    pub fn create_game(ctx: Context<CreateGame>, max_items_per_player: u8) -> Result<()> {
        run_create_game(ctx, max_items_per_player)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn create_player(ctx: Context<CreatePlayer>) -> Result<()> {
        run_create_player(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn spawn_monster(ctx: Context<SpawnMonster>) -> Result<()> {
        run_spawn_monster(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn attack_monster(ctx: Context<AttackMonster>) -> Result<()> {
        run_attack_monster(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
 
    pub fn deposit_action_points(ctx: Context<CollectActionPoints>) -> Result<()> {
        run_collect_action_points(ctx)?;
        sol_log_compute_units();
        Ok(())
    }
}

If you added in all of the sections correctly, you should be able to build successfully.

anchor build

Testing #

Now, let's put everything together and see it in action!

We'll begin by setting up the tests/rpg.ts file. We will be writing each test step by step. But before diving into the tests, we need to initialize a few important accounts, specifically the gameMaster and the treasury accounts.

rpg.ts
import * as anchor from "@coral-xyz/anchor";
import { Program } from "@coral-xyz/anchor";
import { Rpg } from "../target/types/rpg";
import { assert } from "chai";
import {
  Keypair,
  LAMPORTS_PER_SOL,
  PublicKey,
  TransactionSignature,
  TransactionConfirmationStrategy,
} from "@solana/web3.js";
import NodeWallet from "@coral-xyz/anchor/dist/cjs/nodewallet";
 
const GAME_SEED = "GAME";
const PLAYER_SEED = "PLAYER";
const MONSTER_SEED = "MONSTER";
const MAX_ITEMS_PER_PLAYER = 8;
const INITIAL_MONSTER_HITPOINTS = 100;
const AIRDROP_AMOUNT = 10 * LAMPORTS_PER_SOL;
const CREATE_PLAYER_ACTION_POINTS = 100;
const SPAWN_MONSTER_ACTION_POINTS = 5;
const ATTACK_MONSTER_ACTION_POINTS = 1;
const MONSTER_INDEX_BYTE_LENGTH = 8;
 
const provider = anchor.AnchorProvider.env();
anchor.setProvider(provider);
 
const program = anchor.workspace.Rpg as Program<Rpg>;
const wallet = provider.wallet as NodeWallet;
const gameMaster = wallet;
const player = wallet;
 
const treasury = Keypair.generate();
 
const findProgramAddress = (seeds: Buffer[]): [PublicKey, number] =>
  PublicKey.findProgramAddressSync(seeds, program.programId);
 
const confirmTransaction = async (
  signature: TransactionSignature,
  provider: anchor.Provider,
) => {
  const latestBlockhash = await provider.connection.getLatestBlockhash();
  const confirmationStrategy: TransactionConfirmationStrategy = {
    signature,
    blockhash: latestBlockhash.blockhash,
    lastValidBlockHeight: latestBlockhash.lastValidBlockHeight,
  };
 
  try {
    const confirmation =
      await provider.connection.confirmTransaction(confirmationStrategy);
    if (confirmation.value.err) {
      throw new Error(
        `Transaction failed: ${confirmation.value.err.toString()}`,
      );
    }
  } catch (error) {
    throw new Error(`Transaction confirmation failed: ${error.message}`);
  }
};
 
const createGameAddress = () =>
  findProgramAddress([Buffer.from(GAME_SEED), treasury.publicKey.toBuffer()]);
 
const createPlayerAddress = (gameAddress: PublicKey) =>
  findProgramAddress([
    Buffer.from(PLAYER_SEED),
    gameAddress.toBuffer(),
    player.publicKey.toBuffer(),
  ]);
 
const createMonsterAddress = (
  gameAddress: PublicKey,
  monsterIndex: anchor.BN,
) =>
  findProgramAddress([
    Buffer.from(MONSTER_SEED),
    gameAddress.toBuffer(),
    player.publicKey.toBuffer(),
    monsterIndex.toArrayLike(Buffer, "le", MONSTER_INDEX_BYTE_LENGTH),
  ]);
 
describe("RPG game", () => {
  it("creates a new game", async () => {});
 
  it("creates a new player", async () => {});
 
  it("spawns a monster", async () => {});
 
  it("attacks a monster", async () => {});
 
  it("deposits action points", async () => {});
});

Now lets add in the creates a new game test. Just call createGame with eight items, be sure to pass in all the accounts, and make sure the treasury account signs the transaction.

it("creates a new game", async () => {
  try {
    const [gameAddress] = createGameAddress();
 
    const createGameSignature = await program.methods
      .createGame(MAX_ITEMS_PER_PLAYER)
      .accounts({
        game: gameAddress,
        gameMaster: gameMaster.publicKey,
        treasury: treasury.publicKey,
        systemProgram: anchor.web3.SystemProgram.programId,
      })
      .signers([treasury])
      .rpc();
 
    await confirmTransaction(createGameSignature, provider);
  } catch (error) {
    throw new Error(`Failed to create game: ${error.message}`);
  }
});

Go ahead and check that your test runs:

yarn install
anchor test

Hacky workaround: If for some reason, the yarn install command results in some .pnp.* files and no node_modules, you may want to call rm -rf .pnp.* followed by npm i and then yarn install. That should work.

Now that everything is running, let's implement the creates a new player, spawns a monster, and attacks a monster tests. Run each test as you complete them to make sure things are running smoothly.

it("creates a new player", async () => {
  try {
    const [gameAddress] = createGameAddress();
    const [playerAddress] = createPlayerAddress(gameAddress);
 
    const createPlayerSignature = await program.methods
      .createPlayer()
      .accounts({
        game: gameAddress,
        playerAccount: playerAddress,
        player: player.publicKey,
        systemProgram: anchor.web3.SystemProgram.programId,
      })
      .rpc();
 
    await confirmTransaction(createPlayerSignature, provider);
  } catch (error) {
    throw new Error(`Failed to create player: ${error.message}`);
  }
});
 
it("spawns a monster", async () => {
  try {
    const [gameAddress] = createGameAddress();
    const [playerAddress] = createPlayerAddress(gameAddress);
 
    const playerAccount = await program.account.player.fetch(playerAddress);
    const [monsterAddress] = createMonsterAddress(
      gameAddress,
      playerAccount.nextMonsterIndex,
    );
 
    const spawnMonsterSignature = await program.methods
      .spawnMonster()
      .accounts({
        game: gameAddress,
        playerAccount: playerAddress,
        monster: monsterAddress,
        player: player.publicKey,
        systemProgram: anchor.web3.SystemProgram.programId,
      })
      .rpc();
 
    await confirmTransaction(spawnMonsterSignature, provider);
  } catch (error) {
    throw new Error(`Failed to spawn monster: ${error.message}`);
  }
});
 
it("attacks a monster", async () => {
  try {
    const [gameAddress] = createGameAddress();
    const [playerAddress] = createPlayerAddress(gameAddress);
 
    const playerAccount = await program.account.player.fetch(playerAddress);
    const [monsterAddress] = createMonsterAddress(
      gameAddress,
      playerAccount.nextMonsterIndex.subn(1),
    );
 
    const attackMonsterSignature = await program.methods
      .attackMonster()
      .accounts({
        playerAccount: playerAddress,
        monster: monsterAddress,
        player: player.publicKey,
        systemProgram: anchor.web3.SystemProgram.programId,
      })
      .rpc();
 
    await confirmTransaction(attackMonsterSignature, provider);
 
    const monsterAccount = await program.account.monster.fetch(monsterAddress);
    assert(
      monsterAccount.hitpoints.eqn(INITIAL_MONSTER_HITPOINTS - 1),
      "Monster hitpoints should decrease by 1 after attack",
    );
  } catch (error) {
    throw new Error(`Failed to attack monster: ${error.message}`);
  }
});

Notice the monster that we choose to attack is playerAccount.nextMonsterIndex.subn(1).toBuffer('le', 8). This allows us to attack the most recent monster spawned. Anything below the nextMonsterIndex should be okay. Lastly, since seeds are just an array of bytes we have to turn the index into the u64, which is a little endian le at 8 bytes.

Run anchor test to deal some damage!

Finally, let's write a test to gather all the deposited action points. This test may feel complex for what it's doing. That's because we're generating some new accounts to show that anyone could call the redeem function depositActionPoints. We use names like clockwork for these because if this game were running continuously, it probably makes sense to use something like clockwork cron jobs.

it("deposits action points", async () => {
  try {
    const [gameAddress] = createGameAddress();
    const [playerAddress] = createPlayerAddress(gameAddress);
 
    // To show that anyone can deposit the action points
    // Ie, give this to a clockwork bot
    const clockworkWallet = anchor.web3.Keypair.generate();
 
    // To give it a starting balance
    const clockworkProvider = new anchor.AnchorProvider(
      program.provider.connection,
      new NodeWallet(clockworkWallet),
      anchor.AnchorProvider.defaultOptions(),
    );
 
    // Have to give the accounts some lamports else the tx will fail
    const amountToInitialize = 10000000000;
 
    const clockworkAirdropTx =
      await clockworkProvider.connection.requestAirdrop(
        clockworkWallet.publicKey,
        amountToInitialize,
      );
 
    await confirmTransaction(clockworkAirdropTx, clockworkProvider);
 
    const treasuryAirdropTx = await clockworkProvider.connection.requestAirdrop(
      treasury.publicKey,
      amountToInitialize,
    );
 
    await confirmTransaction(treasuryAirdropTx, clockworkProvider);
 
    const depositActionPointsSignature = await program.methods
      .depositActionPoints()
      .accounts({
        game: gameAddress,
        player: playerAddress,
        treasury: treasury.publicKey,
        systemProgram: anchor.web3.SystemProgram.programId,
      })
      .rpc();
 
    await confirmTransaction(depositActionPointsSignature, provider);
 
    const expectedActionPoints =
      CREATE_PLAYER_ACTION_POINTS +
      SPAWN_MONSTER_ACTION_POINTS +
      ATTACK_MONSTER_ACTION_POINTS;
    const treasuryBalance = await provider.connection.getBalance(
      treasury.publicKey,
    );
    assert(
      treasuryBalance === AIRDROP_AMOUNT + expectedActionPoints,
      "Treasury balance should match expected action points",
    );
 
    const gameAccount = await program.account.game.fetch(gameAddress);
    assert(
      gameAccount.actionPointsCollected.eqn(expectedActionPoints),
      "Game action points collected should match expected",
    );
 
    const playerAccount = await program.account.player.fetch(playerAddress);
    assert(
      playerAccount.actionPointsSpent.eqn(expectedActionPoints),
      "Player action points spent should match expected",
    );
    assert(
      playerAccount.actionPointsToBeCollected.eqn(0),
      "Player should have no action points to be collected",
    );
  } catch (error) {
    throw new Error(`Failed to deposit action points: ${error.message}`);
  }
});

Finally, run anchor test to see everything working.

 
RPG game
 creates a new game (317ms)
 creates a new player (399ms)
 spawns a monster (411ms)
 attacks a monster (413ms)
 deposits action points (1232ms)

Congratulations! This was a lot to cover, but you now have a mini RPG game engine. If things aren't quite working, go back through the lab and find where you went wrong. If you need to, you can refer to the main branch of the solution code.

Be sure to put these concepts into practice in your own programs. Each little optimization adds up!

Challenge #

Now it's your turn to practice independently. Go back through the lab code looking for additional optimizations and/or expansions you can make. Think through new systems and features you would add and how you would optimize them.

You can find some example modifications on the challenge-solution branch of the RPG repository.

Finally, go through one of your own programs and think about optimizations you can make to improve memory management, storage size, and/or concurrency.

Completed the lab?

Push your code to GitHub and tell us what you thought of this lesson!