csv 0.15.0

CSV parsing with automatic type based decoding and encoding.

Crate csv [] [src]

This crate provides a streaming CSV (comma separated values) writer and reader that works with the serialize crate to do type based encoding and decoding. There are two primary goals of this project:

  1. The default mode of parsing should just work. This means the parser will bias toward providing a parse over a correct parse (with respect to RFC 4180).
  2. Convenient to use by default, but when performance is needed, the API will provide an escape hatch.

Simple example

This shows how you can decode records into Rust types. This saves a ton of boiler plate, e.g., converting strings to numeric types.

let data = "
sticker,mortals,7
bribed,personae,7
wobbling,poncing,4
interposed,emmett,9
chocolate,refile,7";

let mut rdr = csv::Reader::from_string(data).has_headers(false);
for row in rdr.decode() {
    let (n1, n2, dist): (String, String, u32) = row.unwrap();
    println!("{}, {}: {}", n1, n2, dist);
}

If you just want a Vec of all the records, then you can use the collect method defined on iterators:

let data = "
sticker,mortals,7
bribed,personae,7
wobbling,poncing,4
interposed,emmett,9
chocolate,refile,7";

type Row = (String, String, u32);

let mut rdr = csv::Reader::from_string(data).has_headers(false);
let rows = rdr.decode().collect::<csv::Result<Vec<Row>>>().unwrap();
assert_eq!(rows.len(), 5);

Please see the Reader type for more documentation and examples.

Iteratoring over records

This crate exposes 4 distinct ways of iterating over CSV records. In the majority of use cases, you should use the decode method as shown above because it is the most convenient. But other types of iterators are exposed for when you need them.

The iterators listed below are presented in order of performance. The first (type based decoding) is the slowest and the last (zero allocation) is the fastest. There is clear evidence of this claim in the benchmarks. (Just run cargo bench.)

Decoded records

As shown above. This uses type based decoding on each record.

String records

Yields each record as a Vec<String>. Namely, this assumes that all CSV data is UTF-8 encoded. This is the standard CSV interface that you've probably come to expect from using other CSV parsers.

let data = "
sticker,mortals,7
bribed,personae,7
wobbling,poncing,4
interposed,emmett,9
chocolate,refile,7";

let mut rdr = csv::Reader::from_string(data).has_headers(false);
for row in rdr.records().map(|r| r.unwrap()) {
    println!("{:?}", row);
}

Byte string records

Yields each record as a Vec<ByteString>. Namely, this allows reading CSV data that is not UTF-8 encoded (or improperly encoded!).

let data = b"
sti\xffcker,mortals,7
chocolate,refile,7";

let mut rdr = csv::Reader::from_bytes(&data[..]).has_headers(false);
for row in rdr.byte_records().map(|r| r.unwrap()) {
    println!("{:?}", row);
}

Byte slice records

This iterator is defined on the Reader type itself and yields fields instead of records (unlike the other iterators). Each field is a &[u8]. No allocation is performed during parsing (unlike the other iterators, which at least allocate a Vec<u8> for each field and a Vec<_> for each record). Since no allocation is performed, this "iterator" doesn't actually implement the Iterator trait (since it cannot be done safely).

This is the lowest level interface and should only be used when you need the performance.

let data = "
sticker,mortals,7
bribed,personae,7
wobbling,poncing,4
interposed,emmett,9
chocolate,refile,7";

let mut rdr = csv::Reader::from_string(data);
while !rdr.done() {
    while let Some(r) = rdr.next_bytes().into_iter_result() {
        print!("{:?} ", r.unwrap());
    }
    println!("");
}

There is more explanation for how this iterator interface works on the Reader type.

Indexing

This crate has experimental support for CSV record indexing. It's very simplistic, but once the index is created, you can seek a csv::Reader to any record instantly. See the csv::index sub-module for more details and examples.

Compliance with RFC 4180

RFC 4180 seems to the closest thing to an official specification for CSV. Currently, the parser in this crate will read a strict superset of RFC 4180 while the writer will always write CSV data that conforms to RFC 4180 (unless configured to do otherwise). This approach was taken because CSV data is commonly malformed and there is nothing worse than trying to read busted CSV data with a library that says it can't do it.

With that said, a "strict" mode may be added that will only read CSV data that conforms to RFC 4180.

Here are a few notes on compatibility with RFC 4180:

  • Both CRLF and LF line endings are supported. This is seamless in the parser. By default, the encoder uses LF line endings but can be instructed to use CRLF with the crlf method.
  • The first record is read as a "header" by default, but this can be disabled by calling has_headers(false) before reading any records. (N.B. The encoder has no explicit support for headers. Simply encode a vector of strings instead.)
  • By default, the delimiter is a comma, but it can be changed to any ASCII byte character with the delimiter method (for either writing or reading).
  • By default, both the writer and reader will enforce the invariant that all records are the same length. (This is what RFC 4180 demands.) If a record with a different length is found, an error is returned. This behavior may be turned off by calling flexible with true.
  • Empty lines (that do not include other whitespace) are ignored by the parser.
  • This crates parses CSV data at the byte level, which means all delimiter and quote characters must be ASCII. While unfortunate, this means that CSV data that is not UTF-8 encoded can be parsed. In general, the writer and reader API biases toward using Unicode strings while providing an outlet to use byte strings.

Modules

index

This sub-module provides experimental CSV record indexing.

Structs

ByteRecords

An iterator of ByteString records.

Decoded

A record to be decoded.

DecodedRecords

An iterator of decoded records.

Encoded

A record to be encoded.

LocatableError

An error tagged with a location at which it occurred.

Reader

A CSV reader.

StringRecords

An iterator of String records.

Writer

A CSV writer.

Enums

Error

An error produced by an operation on CSV data.

NextField

NextField is the result of parsing a single CSV field.

ParseError

A description of a CSV parse error.

QuoteStyle

The quoting style to use when writing CSV data.

RecordTerminator

A record terminator.

Traits

BorrowBytes

A trait that permits borrowing byte vectors.

Type Definitions

ByteString

A convenience type for referring to a plain byte string.

Result

A convenience type for representing the result of most CSV reader/writer operations.