这个crate提供了方便的宏和trait,可帮助编写SQL查询并将其结果收集到静态类型的结构中。
示例代码:
// Connect to the database
let client: Client = connect(/* ... */);
// Construct the query
let query = query!(
"SELECT name, age FROM people WHERE age >= $min_age",
min_age = 18
);
// Define the structure of the data returned from the query
#[derive(FromSqlRow)]
struct Person {
age: i32,
name: String,
}
// Execute the query
let people: Vec<Person> = query.fetch(&client).await?;
// Use the results
for person in people {
println!("{} is {} years young", person.name, person.age);
}
Github
分词器的核心是用Rust编写的。提供当今最常用的分词器的实现,重点是性能和多功能性。
示例代码
use tokenizers::tokenizer::{Result, Tokenizer, EncodeInput};
use tokenizers::models::bpe::BPE;
fn main() -> Result<()> {
let bpe_builder = BPE::from_files("./path/to/vocab.json", "./path/to/merges.txt")?;
let bpe = bpe_builder
.dropout(0.1)
.unk_token("[UNK]".into())
.build()?;
let mut tokenizer = Tokenizer::new(Box::new(bpe));
let encoding = tokenizer.encode(EncodeInput::Single("Hey there!".into()))?;
println!("{:?}", encoding.get_tokens());
Ok(())
}
Github
使用Rust 1.40时,类似函数的宏可以生成macro_rules!,因此,删除对proc-macro-hack
的依赖非常容易。