Struct csv_async::AsyncSerializer
source · pub struct AsyncSerializer<W: AsyncWrite + Unpin> { /* private fields */ }
Expand description
An already configured CSV serde
serializer.
A CSV serializer takes as input Rust structures that implement serde::Serialize
trait
and writes those data in a valid CSV output.
While CSV writing is considerably easier than parsing CSV, a proper writer will do a number of things for you:
- Quote fields when necessary.
- Check that all records have the same number of fields.
- Write records with a single empty field correctly.
- Automatically serialize normal Rust types to CSV records. When that type is a struct, a header row is automatically written corresponding to the fields of that struct.
- Use buffering intelligently and otherwise avoid allocation. (This means that callers should not do their own buffering.)
All of the above can be configured using a
AsyncWriterBuilder
.
However, a AsyncSerializer
has convenient constructor (from_writer
)
that use the default configuration.
Note that the default configuration of a AsyncSerializer
uses \n
for record
terminators instead of \r\n
as specified by RFC 4180. Use the
terminator
method on AsyncWriterBuilder
to set the terminator to \r\n
if
it’s desired.
Implementations§
source§impl<W: AsyncWrite + Unpin> AsyncSerializer<W>
impl<W: AsyncWrite + Unpin> AsyncSerializer<W>
sourcepub fn from_writer(wtr: W) -> AsyncSerializer<W>
pub fn from_writer(wtr: W) -> AsyncSerializer<W>
Build a CSV serializer with a default configuration that writes data to
ser
.
Note that the CSV serializer is buffered automatically, so you should not
wrap ser
in a buffered writer.
§Example
use std::error::Error;
use csv_async::AsyncSerializer;
use serde::Serialize;
#[derive(Serialize)]
struct Row<'a> {
name: &'a str,
x: u64,
y: u64,
}
async fn example() -> Result<(), Box<dyn Error>> {
let mut ser = AsyncSerializer::from_writer(vec![]);
ser.serialize(Row {name: "p1", x: 1, y: 2}).await?;
ser.serialize(Row {name: "p2", x: 3, y: 4}).await?;
let data = String::from_utf8(ser.into_inner().await?)?;
assert_eq!(data, "name,x,y\np1,1,2\np2,3,4\n");
Ok(())
}
sourcepub async fn serialize<S: Serialize>(&mut self, record: S) -> Result<()>
pub async fn serialize<S: Serialize>(&mut self, record: S) -> Result<()>
Serialize a single record using Serde.
§Example
This shows how to serialize normal Rust structs as CSV records. The
fields of the struct are used to write a header row automatically.
(Writing the header row automatically can be disabled by building the
CSV writer with a WriterBuilder
and
calling the has_headers
method.)
use std::error::Error;
use csv_async::AsyncSerializer;
use serde::Serialize;
#[derive(Serialize)]
struct Row<'a> {
city: &'a str,
country: &'a str,
// Serde allows us to name our headers exactly,
// even if they don't match our struct field names.
#[serde(rename = "popcount")]
population: u64,
}
async fn example() -> Result<(), Box<dyn Error>> {
let mut ser = AsyncSerializer::from_writer(vec![]);
ser.serialize(Row {
city: "Boston",
country: "United States",
population: 4628910,
}).await?;
ser.serialize(Row {
city: "Concord",
country: "United States",
population: 42695,
}).await?;
let data = String::from_utf8(ser.into_inner().await?)?;
assert_eq!(data, indoc::indoc! {"
city,country,popcount
Boston,United States,4628910
Concord,United States,42695
"});
Ok(())
}
§Rules
The behavior of serialize
is fairly simple:
-
Nested containers (tuples,
Vec
s, structs, etc.) are always flattened (depth-first order). -
If
has_headers
istrue
and the type contains field names, then a header row is automatically generated.
However, some container types cannot be serialized, and if
has_headers
is true
, there are some additional restrictions on the
types that can be serialized. See below for details.
For the purpose of this section, Rust types can be divided into three categories: scalars, non-struct containers, and structs.
§Scalars
Single values with no field names are written like the following. Note that some of the outputs may be quoted, according to the selected quoting style.
Name | Example Type | Example Value | Output |
---|---|---|---|
boolean | bool | true | true |
integers | i8 , i16 , i32 , i64 , i128 , u8 , u16 , u32 , u64 , u128 | 5 | 5 |
floats | f32 , f64 | 3.14 | 3.14 |
character | char | '☃' | ☃ |
string | &str | "hi" | hi |
bytes | &[u8] | b"hi"[..] | hi |
option | Option | None | empty |
option | Some(5) | 5 | |
unit | () | () | empty |
unit struct | struct Foo; | Foo | Foo |
unit enum variant | enum E { A, B } | E::A | A |
newtype struct | struct Foo(u8); | Foo(5) | 5 |
newtype enum variant | enum E { A(u8) } | E::A(5) | 5 |
Note that this table includes simple structs and enums. For example, to serialize a field from either an integer or a float type, one can do this:
use std::error::Error;
use csv_async::AsyncSerializer;
use serde::Serialize;
#[derive(Serialize)]
struct Row {
label: String,
value: Value,
}
#[derive(Serialize)]
enum Value {
Integer(i64),
Float(f64),
}
async fn example() -> Result<(), Box<dyn Error>> {
let mut ser = AsyncSerializer::from_writer(vec![]);
ser.serialize(Row {
label: "foo".to_string(),
value: Value::Integer(3),
}).await?;
ser.serialize(Row {
label: "bar".to_string(),
value: Value::Float(3.14),
}).await?;
let data = String::from_utf8(ser.into_inner().await?)?;
assert_eq!(data, indoc::indoc! {"
label,value
foo,3
bar,3.14
"});
Ok(())
}
§Non-Struct Containers
Nested containers are flattened to their scalar components, with the exception of a few types that are not allowed:
Name | Example Type | Example Value | Output |
---|---|---|---|
sequence | Vec<u8> | vec![1, 2, 3] | 1,2,3 |
tuple | (u8, bool) | (5, true) | 5,true |
tuple struct | Foo(u8, bool) | Foo(5, true) | 5,true |
tuple enum variant | enum E { A(u8, bool) } | E::A(5, true) | error |
struct enum variant | enum E { V { a: u8, b: bool } } | E::V { a: 5, b: true } | error |
map | BTreeMap<K, V> | BTreeMap::new() | error |
§Structs
Like the other containers, structs are flattened to their scalar components:
Name | Example Type | Example Value | Output |
---|---|---|---|
struct | struct Foo { a: u8, b: bool } | Foo { a: 5, b: true } | 5,true |
If has_headers
is false
, then there are no additional restrictions;
types can be nested arbitrarily. For example:
use std::error::Error;
use csv_async::AsyncWriterBuilder;
use serde::Serialize;
#[derive(Serialize)]
struct Row {
label: String,
values: Vec<f64>,
}
async fn example() -> Result<(), Box<dyn Error>> {
let mut ser = AsyncWriterBuilder::new()
.has_headers(false)
.create_serializer(vec![]);
ser.serialize(Row {
label: "foo".to_string(),
values: vec![1.1234, 2.5678, 3.14],
}).await?;
let data = String::from_utf8(ser.into_inner().await?)?;
assert_eq!(data, indoc::indoc! {"
foo,1.1234,2.5678,3.14
"});
Ok(())
}
However, if has_headers
were enabled in the above example, then
serialization would return an error. Specifically, when has_headers
is
true
, there are two restrictions:
-
Named field values in structs must be scalars.
-
All scalars must be named field values in structs.
Other than these two restrictions, types can be nested arbitrarily. Here are a few examples:
Value | Header | Record |
---|---|---|
(Foo { x: 5, y: 6 }, Bar { z: true }) | x,y,z | 5,6,true |
vec![Foo { x: 5, y: 6 }, Foo { x: 7, y: 8 }] | x,y,x,y | 5,6,7,8 |
(Foo { x: 5, y: 6 }, vec![Bar { z: Baz(true) }]) | x,y,z | 5,6,true |
Foo { x: 5, y: (6, 7) } | error: restriction 1 | 5,6,7 |
(5, Foo { x: 6, y: 7 } | error: restriction 2 | 5,6,7 |
(Foo { x: 5, y: 6 }, true) | error: restriction 2 | 5,6,true |
sourcepub async fn into_inner(self) -> Result<W, IntoInnerError<AsyncSerializer<W>>>
pub async fn into_inner(self) -> Result<W, IntoInnerError<AsyncSerializer<W>>>
Flush the contents of the internal buffer and return the underlying writer.