import fs2.data.json.jq.Compiler
val queryCompiler = Compiler[IO]
-// queryCompiler: Compiler[IO] = fs2.data.json.jq.internal.ESPJqCompiler@6d39cb4d
+// queryCompiler: Compiler[IO] = fs2.data.json.jq.internal.ESPJqCompiler@46ad49b4
val queryPipe = queryCompiler.compile(query).unsafeRunSync()
// queryPipe: fs2.package.Pipe[IO, json.Token, json.Token] = <function1>
diff --git a/documentation/cbor-json/index.html b/documentation/cbor-json/index.html
index ee859df9..e7b6e3e1 100644
--- a/documentation/cbor-json/index.html
+++ b/documentation/cbor-json/index.html
@@ -264,7 +264,7 @@ The generic derivation for cell decoders also supports renaming and deriving instances for unary product types (case classes with one field):
@@ -213,9 +213,9 @@import fs2.data.csv.generic.semiauto._
implicit val MyRowDecoder: CsvRowDecoder[MyRow, String] = deriveCsvRowDecoder[MyRow]
-// MyRowDecoder: CsvRowDecoder[MyRow, String] = fs2.data.csv.generic.internal.DerivedCsvRowDecoder$$anon$1@56296e6f
+// MyRowDecoder: CsvRowDecoder[MyRow, String] = fs2.data.csv.generic.internal.DerivedCsvRowDecoder$$anon$1@40eafeb3
val decoded = stream.through(decodeUsingHeaders[MyRow]())
// decoded: Stream[[x]Fallible[x], MyRow] = Stream(..)
diff --git a/documentation/csv/index.html b/documentation/csv/index.html
index 118387e8..f8c2aca5 100644
--- a/documentation/csv/index.html
+++ b/documentation/csv/index.html
@@ -200,9 +200,9 @@ val
textStream = Stream.emit(input).covary[Fallible]
// textStream: Stream[Fallible, String] = Stream(..)
implicit val myRowDecoder: CsvRowDecoder[MyRow, String] = deriveCsvRowDecoder
-// myRowDecoder: CsvRowDecoder[MyRow, String] = fs2.data.csv.generic.internal.DerivedCsvRowDecoder$$anon$1@43a21a38
+// myRowDecoder: CsvRowDecoder[MyRow, String] = fs2.data.csv.generic.internal.DerivedCsvRowDecoder$$anon$1@f64ffe3
implicit val myRowEncoder: CsvRowEncoder[MyRow, String] = deriveCsvRowEncoder
-// myRowEncoder: CsvRowEncoder[MyRow, String] = fs2.data.csv.generic.internal.DerivedCsvRowEncoder$$anonfun$productWriter$2@2d03a145
+// myRowEncoder: CsvRowEncoder[MyRow, String] = fs2.data.csv.generic.internal.DerivedCsvRowEncoder$$anonfun$productWriter$2@509730df
// decodeUsingHeaders can take a `Char` indicating the separator to use
// for example `decodeUsingHeaders[MyRow](';') for a semi-colon separated csv
@@ -453,7 +453,7 @@ implicit
val parseableMyHeaders: ParseableHeader[MyHeaders] = ParseableHeader.instance[MyHeaders] { name =>
MyHeaders.withNameInsensitiveOption(name).toRight(new HeaderError(s"Unknown header $name"))
}
-// parseableMyHeaders: ParseableHeader[MyHeaders] = fs2.data.csv.ParseableHeader$$$Lambda$14212/0x0000000803868c40@35988cf9
+// parseableMyHeaders: ParseableHeader[MyHeaders] = fs2.data.csv.ParseableHeader$$$Lambda$14289/0x0000000803864040@2a8538f4
val withMyHeaders = stream.through(lowlevel.headers[Fallible, MyHeaders])
// withMyHeaders: Stream[[x]Fallible[x], CsvRow[MyHeaders]] = Stream(..)
@@ -559,10 +559,10 @@ For CellEncoder, it is even easier to define your own as encoding can't fail, so basically it's just a function A => String. The easiest ways to roll your own are using Scala's single abstract method sugar:
case class Wrapper(content: String)
implicit val wrapperCellEncoder: CellEncoder[Wrapper] = (w: Wrapper) => w.content
-// wrapperCellEncoder: CellEncoder[Wrapper] = repl.MdocSession$MdocApp$$anonfun$9@663833a8
+
// wrapperCellEncoder: CellEncoder[Wrapper] = repl.MdocSession$MdocApp$$anonfun$9@2b641a0
or using contramap on an existing encoder:
implicit val wrapperCellEncoder2: CellEncoder[Wrapper] = CellEncoder[String].contramap(_.content)
-// wrapperCellEncoder2: CellEncoder[Wrapper] = fs2.data.csv.CellEncoder$$anonfun$contramap$2@5681bfa3RowDecoder & RowEncoderRowDecoders can be used to decode an entire CSV row based on field positions. For instance if you want to decode the CSV data into shapeless HList: