CSV 处理
读取 CSV 记录
将标准的 CSV 记录读入 csv::StringRecord
——一种弱类型的数据表示方式,它需要 CSV 中的行数据是有效的 UTF-8 字符编码。另外,csv::ByteRecord
对 UTF-8 不做任何预设。
use csv::Error; fn main() -> Result<(), Error> { let csv = "year,make,model,description 1948,Porsche,356,Luxury sports car 1967,Ford,Mustang fastback 1967,American car"; let mut reader = csv::Reader::from_reader(csv.as_bytes()); for record in reader.records() { let record = record?; println!( "In {}, {} built the {} model. It is a {}.", &record[0], &record[1], &record[2], &record[3] ); } Ok(()) }
Serde 将数据反序列化为强类型结构体。具体查阅 csv::Reader::deserialize
方法。
use serde::Deserialize; #[derive(Deserialize)] struct Record { year: u16, make: String, model: String, description: String, } fn main() -> Result<(), csv::Error> { let csv = "year,make,model,description 1948,Porsche,356,Luxury sports car 1967,Ford,Mustang fastback 1967,American car"; let mut reader = csv::Reader::from_reader(csv.as_bytes()); for record in reader.deserialize() { let record: Record = record?; println!( "In {}, {} built the {} model. It is a {}.", record.year, record.make, record.model, record.description ); } Ok(()) }
读取有不同分隔符的 CSV 记录
使用制表(tab)分隔符 delimiter
读取 CSV 记录。
use csv::Error; use serde::Deserialize; #[derive(Debug, Deserialize)] struct Record { name: String, place: String, #[serde(deserialize_with = "csv::invalid_option")] id: Option<u64>, } use csv::ReaderBuilder; fn main() -> Result<(), Error> { let data = "name\tplace\tid Mark\tMelbourne\t46 Ashley\tZurich\t92"; let mut reader = ReaderBuilder::new().delimiter(b'\t').from_reader(data.as_bytes()); for result in reader.deserialize::<Record>() { println!("{:?}", result?); } Ok(()) }
筛选匹配断言的 CSV 记录
仅仅 返回 data
中字段(field)与 query
匹配的的行。
use error_chain::error_chain; use std::io; error_chain!{ foreign_links { Io(std::io::Error); CsvError(csv::Error); } } fn main() -> Result<()> { let query = "CA"; let data = "\ City,State,Population,Latitude,Longitude Kenai,AK,7610,60.5544444,-151.2583333 Oakman,AL,,33.7133333,-87.3886111 Sandfort,AL,,32.3380556,-85.2233333 West Hollywood,CA,37031,34.0900000,-118.3608333"; let mut rdr = csv::ReaderBuilder::new().from_reader(data.as_bytes()); let mut wtr = csv::Writer::from_writer(io::stdout()); wtr.write_record(rdr.headers()?)?; for result in rdr.records() { let record = result?; if record.iter().any(|field| field == query) { wtr.write_record(&record)?; } } wtr.flush()?; Ok(()) }
免责声明:此实例改编自csv crate 教程。
用 Serde 处理无效的 CSV 数据
CSV 文件通常包含无效数据。对于这些情形,csv
crate 提供了一个自定义的反序列化程序 csv::invalid_option
,它自动将无效数据转换为 None 值。
use csv::Error; use serde::Deserialize; #[derive(Debug, Deserialize)] struct Record { name: String, place: String, #[serde(deserialize_with = "csv::invalid_option")] id: Option<u64>, } fn main() -> Result<(), Error> { let data = "name,place,id mark,sydney,46.5 ashley,zurich,92 akshat,delhi,37 alisha,colombo,xyz"; let mut rdr = csv::Reader::from_reader(data.as_bytes()); for result in rdr.deserialize() { let record: Record = result?; println!("{:?}", record); } Ok(()) }
将记录序列化为 CSV
本实例展示了如何序列化 Rust 元组。csv::writer
支持从 Rust 类型到 CSV 记录的自动序列化。write_record
只写入包含字符串数据的简单记录。具有更复杂值(如数字、浮点和选项)的数据使用 serialize
进行序列化。因为 csv::writer
使用内部缓冲区,所以在完成时总是显式刷新 flush
。
use error_chain::error_chain; use std::io; error_chain! { foreign_links { CSVError(csv::Error); IOError(std::io::Error); } } fn main() -> Result<()> { let mut wtr = csv::Writer::from_writer(io::stdout()); wtr.write_record(&["Name", "Place", "ID"])?; wtr.serialize(("Mark", "Sydney", 87))?; wtr.serialize(("Ashley", "Dublin", 32))?; wtr.serialize(("Akshat", "Delhi", 11))?; wtr.flush()?; Ok(()) }
用 Serde 将记录序列化为 CSV
下面的实例展示如何使用 serde crate 将自定义结构体序列化为 CSV 记录。
use error_chain::error_chain; use serde::Serialize; use std::io; error_chain! { foreign_links { IOError(std::io::Error); CSVError(csv::Error); } } #[derive(Serialize)] struct Record<'a> { name: &'a str, place: &'a str, id: u64, } fn main() -> Result<()> { let mut wtr = csv::Writer::from_writer(io::stdout()); let rec1 = Record { name: "Mark", place: "Melbourne", id: 56}; let rec2 = Record { name: "Ashley", place: "Sydney", id: 64}; let rec3 = Record { name: "Akshat", place: "Delhi", id: 98}; wtr.serialize(rec1)?; wtr.serialize(rec2)?; wtr.serialize(rec3)?; wtr.flush()?; Ok(()) }
转换 CSV 文件的列
将包含颜色名称和十六进制颜色值的 CSV 文件转换为具有颜色名称和 rgb 颜色值的 CSV 文件。使用 csv crate 读写 csv 文件,使用 serde crate 对行输入字节进行反序列化,对行输出字节进行序列化。
详细请参阅 csv::Reader::deserialize
、serde::Deserialize
,以及 std::str::FromStr
。
use error_chain::error_chain; use csv::{Reader, Writer}; use serde::{de, Deserialize, Deserializer}; use std::str::FromStr; error_chain! { foreign_links { CsvError(csv::Error); ParseInt(std::num::ParseIntError); CsvInnerError(csv::IntoInnerError<Writer<Vec<u8>>>); IO(std::fmt::Error); UTF8(std::string::FromUtf8Error); } } #[derive(Debug)] struct HexColor { red: u8, green: u8, blue: u8, } #[derive(Debug, Deserialize)] struct Row { color_name: String, color: HexColor, } impl FromStr for HexColor { type Err = Error; fn from_str(hex_color: &str) -> std::result::Result<Self, Self::Err> { let trimmed = hex_color.trim_matches('#'); if trimmed.len() != 6 { Err("Invalid length of hex string".into()) } else { Ok(HexColor { red: u8::from_str_radix(&trimmed[..2], 16)?, green: u8::from_str_radix(&trimmed[2..4], 16)?, blue: u8::from_str_radix(&trimmed[4..6], 16)?, }) } } } impl<'de> Deserialize<'de> for HexColor { fn deserialize<D>(deserializer: D) -> std::result::Result<Self, D::Error> where D: Deserializer<'de>, { let s = String::deserialize(deserializer)?; FromStr::from_str(&s).map_err(de::Error::custom) } } fn main() -> Result<()> { let data = "color_name,color red,#ff0000 green,#00ff00 blue,#0000FF periwinkle,#ccccff magenta,#ff00ff" .to_owned(); let mut out = Writer::from_writer(vec![]); let mut reader = Reader::from_reader(data.as_bytes()); for result in reader.deserialize::<Row>() { let res = result?; out.serialize(( res.color_name, res.color.red, res.color.green, res.color.blue, ))?; } let written = String::from_utf8(out.into_inner()?)?; assert_eq!(Some("magenta,255,0,255"), written.lines().last()); println!("{}", written); Ok(()) }