### Canopydb: Create Database and Basic CRUD Operations in Rust

Source: https://context7.com/arthurprs/canopydb/llms.txt

Demonstrates how to create a new Canopydb database, begin write and read transactions, perform basic CRUD operations (insert, get, delete) on keys within a tree (keyspace), and commit changes. It also shows how to verify data persistence after committing.

```rust
use canopydb::Database;
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    // Create a new database in a temporary directory
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Begin a write transaction
    let tx = db.begin_write()?;

    // Create or get a tree (keyspace) within the transaction
    let mut tree = tx.get_or_create_tree(b"my_tree")?;

    // Insert key-value pairs
    tree.insert(b"key1", b"value1")?;
    tree.insert(b"key2", b"value2")?;
    tree.insert(b"key3", b"value3")?;

    // Read within the same write transaction
    let value = tree.get(b"key1")?;
    assert_eq!(value.as_deref(), Some(&b"value1"[..]));

    // Delete a key
    let deleted = tree.delete(b"key2")?;
    assert!(deleted);

    // Drop tree reference before commit
    drop(tree);

    // Commit the transaction to persist changes
    let tx_id = tx.commit()?;
    println!("Committed transaction: {}", tx_id);

    // Begin a read-only transaction
    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"my_tree")?.unwrap();

    // Verify persisted data
    assert_eq!(tree.get(b"key1")?.as_deref(), Some(&b"value1"[..]));
    assert_eq!(tree.get(b"key2")?, None); // Was deleted
    assert_eq!(tree.get(b"key3")?.as_deref(), Some(&b"value3"[..]));

    Ok(())
}

```

--------------------------------

### Configure CanopyDB Tree Options for Large Value Compression

Source: https://context7.com/arthurprs/canopydb/llms.txt

Illustrates how to set tree-specific options in CanopyDB, focusing on enabling compression for large values. This example demonstrates storing and retrieving a large value that exceeds the specified compression threshold. It requires the 'canopydb' and 'tempfile' crates.

```rust
use canopydb::{Database, TreeOptions};
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Configure tree with compression for large values
    let mut options = TreeOptions::default();
    options.compress_overflow_values = Some(8 * 1024); // Compress values > 8KB

    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree_with(b"documents", options)?;

    // Store a large compressible value (JSON-like)
    let large_value = r#"{ 
        "title": "Lorem Ipsum", 
        "content": "Lorem ipsum dolor sit amet, consectetur adipiscing elit. 
        Sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. 
        Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris. 
        Duis aute irure dolor in reprehenderit in voluptate velit esse cillum. 
        "#.repeat(100); // ~30KB of text

    tree.insert(b"doc:1", large_value.as_bytes())?;

    // Store smaller values (won't be compressed)
    tree.insert(b"doc:2", b"Small document content")?;

    drop(tree);
    tx.commit()?;

    // Read back the data
    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"documents")?.unwrap();

    let doc1 = tree.get(b"doc:1")?.unwrap();
    let doc2 = tree.get(b"doc:2")?.unwrap();

    println!("Document 1 size: {} bytes", doc1.len());
    println!("Document 2 size: {} bytes", doc2.len());
    println!("Total documents: {}", tree.len());

    Ok(())
}

```

--------------------------------

### Optimize Storage with Fixed-Length Keys and Values (Rust)

Source: https://context7.com/arthurprs/canopydb/llms.txt

Illustrates how to configure CanopyDB trees for fixed-length keys and values, optimizing storage for structured numeric data. This example shows storing and querying integer pairs using big-endian for keys and native-endian for values.

```rust
use canopydb::{Database, TreeOptions};
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Configure tree for fixed-length key-value pairs
    let mut options = TreeOptions::default();
    options.fixed_key_len = 8;   // 8-byte keys (u64)
    options.fixed_value_len = 8; // 8-byte values (u64)

    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree_with(b"integers", options)?;

    // Store integer pairs (use big-endian for proper sorting)
    for i in 0u64..100 {
        let key = i.to_be_bytes();      // Big-endian for sorted iteration
        let value = (i * i).to_ne_bytes(); // Native-endian for values
        tree.insert(&key, &value)?;
    }
    drop(tree);
    tx.commit()?;

    // Query the data
    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"integers")?.unwrap();

    // Get a specific value
    let key = 7u64.to_be_bytes();
    let value = tree.get(&key)?
        .map(|v| u64::from_ne_bytes(v.as_ref().try_into().unwrap()));
    println!("7^2 = {:?}", value); // Should be 49

    // Range query: keys 10..20
    let start = 10u64.to_be_bytes();
    let end = 20u64.to_be_bytes();

    println!("\nSquares from 10 to 19:");
    for result in tree.range(&start[..]..&end[..])? {
        let (k, v) = result?;
        let key = u64::from_be_bytes(k.as_ref().try_into().unwrap());
        let value = u64::from_ne_bytes(v.as_ref().try_into().unwrap());
        println!("  {}^2 = {}", key, value);
    }

    // Tree statistics
    println!("\nTree height: {}", tree.height());
    println!("Total entries: {}", tree.len());

    Ok(())
}

```

--------------------------------

### Concurrent Write Transactions with Retry Logic in Rust

Source: https://github.com/arthurprs/canopydb/blob/master/README.md

Demonstrates how to perform concurrent write transactions with retry logic in Rust using CanopyDB. This example shows multiple threads attempting to concurrently update a key-value pair, handling write conflicts by retrying the transaction.

```rust
const THREADS: usize = 4;
const INC_PER_THREAD: usize = 5_000;
let _dir = tempfile::tempdir().unwrap();
let db = canopydb::Database::new(_dir.path()).unwrap();

std::thread::scope(|scope| {
    for _thread in 0..THREADS {
        scope.spawn(|| {
            let mut successes = 0;
            while successes < INC_PER_THREAD {
                // This write txn will run concurrently with other concurrent transactions.
                // But they may conflict at commit time.
                let tx = db.begin_write_concurrent().unwrap();
                let mut tree = tx.get_or_create_tree(b"tree").unwrap();
                // Each thread will independently increment a counter INC_PER_THREAD times
                let prev = if let Some(value) = tree.get(b"key").unwrap() {
                    usize::from_ne_bytes(value.as_ref().try_into().unwrap())
                } else {
                    0
                };
                tree.insert(b"key", &(prev + 1).to_ne_bytes()).unwrap();
                drop(tree);
                match tx.commit() {
                    Ok(_tx_id) => {
                        successes += 1;
                    }
                    Err(canopydb::Error::WriteConflict) => {
                        // Conflict, retry...
                    }
                    Err(e) => panic!("Commit error: {e}"),
                }
            }
        });
    }
});
let rx = db.begin_read().unwrap();
let tree = rx.get_tree(b"tree").unwrap().unwrap();
let value = tree.get(b"key").unwrap().unwrap();
let value_usize = usize::from_ne_bytes(value.as_ref().try_into().unwrap());
println!("Final value: {value_usize}");
assert_eq!(THREADS * INC_PER_THREAD, value_usize);
```

--------------------------------

### Managing Multiple Named Trees in a Database Transaction (Rust)

Source: https://context7.com/arthurprs/canopydb/llms.txt

Illustrates how to organize data into multiple logical keyspaces using named trees within a single database transaction. This example shows creating, reading, renaming, and deleting trees. It demonstrates efficient data management by grouping related data under distinct tree names.

```rust
use canopydb::Database;
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Create multiple trees in a single transaction
    let tx = db.begin_write()?;

    // Users tree
    let mut users = tx.get_or_create_tree(b"users")?;
    users.insert(b"1", b"Alice")?;
    users.insert(b"2", b"Bob")?;
    drop(users);

    // Orders tree
    let mut orders = tx.get_or_create_tree(b"orders")?;
    orders.insert(b"order:1001", b"user:1,product:A,qty:2")?;
    orders.insert(b"order:1002", b"user:2,product:B,qty:1")?;
    drop(orders);

    // Products tree
    let mut products = tx.get_or_create_tree(b"products")?;
    products.insert(b"A", b"Widget")?;
    products.insert(b"B", b"Gadget")?;
    drop(products);

    tx.commit()?;

    // Read from multiple trees
    let rx = db.begin_read()?;

    // List all trees in the database
    let tree_names = rx.list_trees()?;
    println!("Trees in database:");
    for name in &tree_names {
        println!("  - {:?}", String::from_utf8_lossy(name));
    }

    // Access each tree
    let users = rx.get_tree(b"users")?.unwrap();
    let orders = rx.get_tree(b"orders")?.unwrap();
    let products = rx.get_tree(b"products")?.unwrap();

    println!("\nUsers: {} entries", users.len());
    println!("Orders: {} entries", orders.len());
    println!("Products: {} entries", products.len());

    // Rename and delete trees
    let tx = db.begin_write()?;
    tx.rename_tree(b"users", b"customers")?;
    tx.delete_tree(b"products")?;
    tx.commit()?;

    let rx = db.begin_read()?;
    assert!(rx.get_tree(b"customers")?.is_some());
    assert!(rx.get_tree(b"users")?.is_none());
    assert!(rx.get_tree(b"products")?.is_none());

    Ok(())
}

```

--------------------------------

### Concurrent Write Transactions with Retry Logic in Rust

Source: https://context7.com/arthurprs/canopydb/llms.txt

Demonstrates how to perform concurrent write transactions using optimistic concurrency control and automatic retry logic for handling write conflicts. This is crucial for high-throughput workloads where multiple threads might attempt to modify the same data simultaneously. The example initializes a counter, spawns multiple threads to increment it concurrently, and verifies the final count.

```rust
use canopydb::{Database, Error};
use tempfile::tempdir;
use std::thread;

const THREADS: usize = 4;
const INCREMENTS_PER_THREAD: usize = 1000;

fn main() -> Result<(), Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Initialize counter
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"counters")?;
    tree.insert(b"counter", &0u64.to_ne_bytes())?;
    drop(tree);
    tx.commit()?;

    // Spawn multiple threads performing concurrent increments
    thread::scope(|scope| {
        for thread_id in 0..THREADS {
            scope.spawn(|| {
                let mut successes = 0;
                let mut conflicts = 0;

                while successes < INCREMENTS_PER_THREAD {
                    // Begin a concurrent write transaction
                    let tx = db.begin_write_concurrent().unwrap();
                    let mut tree = tx.get_or_create_tree(b"counters").unwrap();

                    // Read current value
                    let current = tree.get(b"counter").unwrap()
                        .map(|v| u64::from_ne_bytes(v.as_ref().try_into().unwrap()))
                        .unwrap_or(0);

                    // Increment and write back
                    tree.insert(b"counter", &(current + 1).to_ne_bytes()).unwrap();
                    drop(tree);

                    // Attempt to commit - may conflict with other transactions
                    match tx.commit() {
                        Ok(_) => successes += 1,
                        Err(Error::WriteConflict) => {
                            conflicts += 1;
                            // Retry the transaction
                        }
                        Err(e) => panic!("Unexpected error: {}", e),
                    }
                }

                println!("Thread {}: {} successes, {} conflicts",
                    thread_id, successes, conflicts);
            });
        }
    });

    // Verify final count
    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"counters")?.unwrap();
    let final_value = tree.get(b"counter")?
        .map(|v| u64::from_ne_bytes(v.as_ref().try_into().unwrap()))
        .unwrap();

    assert_eq!(final_value, (THREADS * INCREMENTS_PER_THREAD) as u64);
    println!("Final counter value: {}", final_value);

    Ok(())
}

```

--------------------------------

### Configure CanopyDB Database Options

Source: https://context7.com/arthurprs/canopydb/llms.txt

Demonstrates how to configure environment and database options for CanopyDB. This includes setting page cache size, WAL limits, commit behavior, and checkpointing parameters. It requires the 'canopydb' and 'tempfile' crates.

```rust
use canopydb::{Database, EnvOptions, DbOptions};
use std::time::Duration;
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();

    // Environment options
    let mut env_opts = EnvOptions::new(dir.path());
    env_opts.page_cache_size = 256 * 1024 * 1024;  // 256MB page cache
    env_opts.use_checksums = true;                  // Enable page checksums
    env_opts.max_wal_size = 64 * 1024 * 1024;      // 64MB max WAL size
    env_opts.wal_background_sync_interval = Some(Duration::from_millis(500));
    env_opts.file_lock_timeout = Duration::from_secs(10);

    // Database options
    let mut db_opts = DbOptions::default();
    db_opts.use_wal = true;                         // Enable Write-Ahead Log
    db_opts.default_commit_sync = false;            // Async commits by default
    db_opts.checkpoint_interval = Duration::from_secs(30);
    db_opts.checkpoint_target_size = 32 * 1024 * 1024; // 32MB checkpoint target
    db_opts.write_txn_memory_limit = 64 * 1024 * 1024; // 64MB uncommitted limit

    let db = Database::with_options(env_opts, db_opts)?;

    // Perform operations
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"data")?;

    for i in 0..10000 {
        let key = format!("key:{:06}", i);
        let value = format!("value:{}", i);
        tree.insert(key.as_bytes(), value.as_bytes())?;
    }
    drop(tree);

    // Commit with explicit sync for durability
    tx.commit_with(true)?; // sync=true forces fsync

    // Manual checkpoint to persist in-memory state to disk
    db.checkpoint()?;

    // Sync to ensure WAL is durable
    db.sync()?;

    println!("Database configured and checkpointed successfully");

    Ok(())
}

```

--------------------------------

### Create Environment with Multiple Databases and Atomic Commits (Rust)

Source: https://context7.com/arthurprs/canopydb/llms.txt

Demonstrates how to set up an environment with multiple databases in CanopyDB, perform independent transactions, and execute atomic cross-database commits. This is useful for maintaining data consistency across related datasets.

```rust
use canopydb::{Environment, EnvOptions, DbOptions};
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();

    // Configure environment options
    let mut env_options = EnvOptions::new(dir.path());
    env_options.page_cache_size = 512 * 1024 * 1024; // 512MB shared cache
    env_options.max_wal_size = 128 * 1024 * 1024;    // 128MB WAL limit

    let env = Environment::with_options(env_options)?;

    // Create multiple databases in the environment
    let db1 = env.get_or_create_database("accounts")?;
    let db2 = env.get_or_create_database("transactions")?;

    // Independent transactions on each database
    let tx1 = db1.begin_write()?;
    let mut accounts = tx1.get_or_create_tree(b"data")?;
    accounts.insert(b"acc:1", b"balance:1000")?;
    accounts.insert(b"acc:2", b"balance:500")?;
    drop(accounts);
    tx1.commit()?;

    let tx2 = db2.begin_write()?;
    let mut txns = tx2.get_or_create_tree(b"data")?;
    txns.insert(b"txn:1", b"from:1,to:2,amount:100")?;
    drop(txns);
    tx2.commit()?;

    // Atomic cross-database commit (both or neither)
    let tx1 = db1.begin_write()?;
    let tx2 = db2.begin_write()?;

    // Update account balances
    let mut accounts = tx1.get_or_create_tree(b"data")?;
    accounts.insert(b"acc:1", b"balance:900")?;
    accounts.insert(b"acc:2", b"balance:600")?;
    drop(accounts);

    // Record the transaction
    let mut txns = tx2.get_or_create_tree(b"data")?;
    txns.insert(b"txn:2", b"from:1,to:2,amount:100")?;
    drop(txns);

    // Commit both databases atomically
    env.group_commit([tx1, tx2], true)?; // sync=true for durability

    println!("Cross-database atomic commit successful!");

    // Verify both databases
    let rx1 = db1.begin_read()?;
    let rx2 = db2.begin_read()?;

    let acc = rx1.get_tree(b"data")?.unwrap();
    let txn = rx2.get_tree(b"data")?.unwrap();

    println!("Accounts: {} entries", acc.len());
    println!("Transactions: {} entries", txn.len());

    Ok(())
}

```

--------------------------------

### Canopydb: Range Queries and Iteration in Rust

Source: https://context7.com/arthurprs/canopydb/llms.txt

Illustrates how to perform various data retrieval operations using Canopydb's ordered map API, including full tree iteration, range queries based on key bounds, prefix scans, and retrieving the first/last entries. It also shows efficient keys-only iteration.

```rust
use canopydb::Database;
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Populate the database
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"users")?;
    tree.insert(b"user:alice", b"Alice Smith")?;
    tree.insert(b"user:bob", b"Bob Jones")?;
    tree.insert(b"user:charlie", b"Charlie Brown")?;
    tree.insert(b"admin:root", b"Root Admin")?;
    drop(tree);
    tx.commit()?;

    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"users")?.unwrap();

    // Full iteration (sorted by key)
    println!("All entries:");
    for result in tree.iter()? {
        let (key, value) = result?;
        println!("  {:?} => {:?}",
            String::from_utf8_lossy(&key),
            String::from_utf8_lossy(&value));
    }

    // Range query: keys from "user:bob" onwards
    println!("\nFrom 'user:bob' onwards:");
    for result in tree.range(&b"user:bob"[..]..)? {
        let (key, value) = result?;
        println!("  {:?} => {:?}",
            String::from_utf8_lossy(&key),
            String::from_utf8_lossy(&value));
    }

    // Prefix scan: all keys starting with "user:"
    println!("\nAll users (prefix 'user:'):");
    for result in tree.prefix(&b"user:")? {
        let (key, value) = result?;
        println!("  {:?} => {:?}",
            String::from_utf8_lossy(&key),
            String::from_utf8_lossy(&value));
    }

    // Get first and last entries
    let first = tree.first()?;
    let last = tree.last()?;
    println!("\nFirst: {:?}", first.map(|(k, _)| String::from_utf8_lossy(&k).to_string()));
    println!("Last: {:?}", last.map(|(k, _)| String::from_utf8_lossy(&k).to_string()));

    // Keys-only iteration (more efficient when values not needed)
    println!("\nAll keys:");
    for result in tree.keys()? {
        let key = result?;
        println!("  {:?}", String::from_utf8_lossy(&key));
    }

    Ok(())
}

```

--------------------------------

### Atomic Cross-Database Commits in Rust

Source: https://github.com/arthurprs/canopydb/blob/master/README.md

Illustrates how to perform atomic commits across multiple databases within the same CanopyDB environment using Rust. This is useful for ensuring data consistency between different databases.

```rust
let sample_data = [
    (&b"baz"[..], &b"qux"[..]),
    (&b"foo"[..], &b"bar"[..]),
    (&b"qux"[..], &b"quux"[..]),
];
let _dir = tempfile::tempdir().unwrap();
let mut options = canopydb::EnvOptions::new(_dir.path());
// all databases in the same environment will share this 1GB cache
options.page_cache_size = 1024 * 1024 * 1024;
let env = canopydb::Environment::new(_dir.path()).unwrap();

let db1 = env.get_or_create_database("db1").unwrap();
let db2 = env.get_or_create_database("db2").unwrap();
// Each database unique write transaction is independent.
let tx1 = db1.begin_write().unwrap();
let tx2 = db2.begin_write().unwrap();
let mut tree = tx1.get_or_create_tree(b"my_tree").unwrap();
tree.insert(b"foo", b"bar").unwrap();
drop(tree);
tx1.commit().unwrap();
tx2.rollback().unwrap();

// Write transactions for databases in the same environment
// can be committed together atomically.
// This allows stablishing a consistent state between them.
let tx1 = db1.begin_write().unwrap();
let tx2 = db2.begin_write().unwrap();
// Use tx1 and tx2 here..
env.group_commit([tx1, tx2], false).unwrap();
```

--------------------------------

### Compact CanopyDB Database to Reclaim Space

Source: https://context7.com/arthurprs/canopydb/llms.txt

Illustrates how to compact a CanopyDB database to reclaim disk space after significant data deletion. This process defragments the database file, making it smaller. It's typically performed after large-scale deletions to optimize storage.

```rust
use canopydb::Database;
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Insert a lot of data
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"data")?;

    for i in 0..50000 {
        let key = format!("key:{:08}", i);
        let value = format!("value:{:0100}", i); // 100+ byte values
        tree.insert(key.as_bytes(), value.as_bytes())?;
    }
    drop(tree);
    tx.commit()?;

    // Force checkpoint to write data to disk
    db.checkpoint()?;

    // Delete most of the data
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"data")?;

    // Keep only keys 40000-50000
    tree.delete_range(&b"key:00000000"[..]..&b"key:00040000"[..])?;

    drop(tree);
    tx.commit()?;
    db.checkpoint()?;

    println!("Before compaction - check file size in: {:?}", dir.path());

    // Compact the database to reclaim space
    // This defragments and shrinks the database file
    db.compact()?;

    println!("After compaction - file should be smaller");

    // Verify data integrity
    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"data")?.unwrap();
    println!("Remaining entries: {}", tree.len());

    Ok(())
}

```

--------------------------------

### Delete Key Ranges from CanopyDB Tree

Source: https://context7.com/arthurprs/canopydb/llms.txt

Demonstrates how to efficiently delete a range of keys from a specified tree within a CanopyDB database. This operation is useful for managing time-series data or cleaning up specific data segments. It requires a mutable transaction and a reference to the tree.

```rust
use canopydb::Database;
use tempfile::tempdir;

fn main() -> Result<(), canopydb::Error> {
    let dir = tempdir().unwrap();
    let db = Database::new(dir.path())?;

    // Populate with time-series data
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"events")?;

    for day in 1..=31 {
        for hour in 0..24 {
            let key = format!("2024-01-{:02}T{:02}:00", day, hour);
            let value = format!("event_data_{}", day * 100 + hour);
            tree.insert(key.as_bytes(), value.as_bytes())?;
        }
    }
    drop(tree);
    tx.commit()?;

    println!("Initial count:");
    let rx = db.begin_read()?;
    println!("  {} events", rx.get_tree(b"events")?.unwrap().len());
    drop(rx);

    // Delete a range of keys (e.g., first week of January)
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"events")?;

    // Delete all events from Jan 1-7
    let start = b"2024-01-01";
    let end = b"2024-01-08"; // Exclusive
    tree.delete_range(&start[..]..&end[..])?;

    drop(tree);
    tx.commit()?;

    println!("\nAfter deleting first week:");
    let rx = db.begin_read()?;
    let tree = rx.get_tree(b"events")?.unwrap();
    println!("  {} events remaining", tree.len());

    // Verify first remaining event
    let first = tree.first()?;
    if let Some((key, _)) = first {
        println!("  First event: {}", String::from_utf8_lossy(&key));
    }

    // Clear entire tree
    let tx = db.begin_write()?;
    let mut tree = tx.get_or_create_tree(b"events")?;
    tree.clear()?;
    drop(tree);
    tx.commit()?;

    let rx = db.begin_read()?;
    println!("\nAfter clear: {} events", rx.get_tree(b"events")?.unwrap().len());

    Ok(())
}

```

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