I'm trying to parse a file, using FParsec, which consists of either float or int values. I'm facing two problems that I can't find a good solution for.
1
Both pint32
and pfloat
will successfully parse the same string, but give different answers, e.g pint32
will return 3
when parsing the string "3.0"
and pfloat
will return 3.0
when parsing the same string. Is it possible to try parsing a floating point value using pint32
and have it fail if the string is "3.0"
?
In other words, is there a way to make the following code work:
let parseFloatOrInt lines =
let rec loop intvalues floatvalues lines =
match lines with
| [] -> floatvalues, intvalues
| line::rest ->
match run floatWs line with
| Success (r, _, _) -> loop intvalues (r::floatvalues) rest
| Failure _ ->
match run intWs line with
| Success (r, _, _) -> loop (r::intvalues) floatvalues rest
| Failure _ -> loop intvalues floatvalues rest
loop [] [] lines
This piece of code will correctly place all floating point values in the floatvalues
list, but because pfloat
returns "3.0"
when parsing the string "3"
, all integer values will also be placed in the floatvalues
list.
2
The above code example seems a bit clumsy to me, so I'm guessing there must be a better way to do it. I considered combining them using choice
, however both parsers must return the same type for that to work. I guess I could make a discriminated union with one option for float and one for int and convert the output from pint32
and pfloat
using the |>>
operator. However, I'm wondering if there is a better solution?
You're on the right path thinking about defining domain data and separating definition of parsers and their usage on source data. This seems to be a good approach, because as your real-life project grows further, you would probably need more data types.
Here's how I would write it:
/// The resulting type, or DSL
type MyData =
| IntValue of int
| FloatValue of float
| Error // special case for all parse failures
// Then, let's define individual parsers:
let pMyInt =
pint32
|>> IntValue
// this is an alternative version of float parser.
// it ensures that the value has non-zero fractional part.
// caveat: the naive approach would treat values like 42.0 as integer
let pMyFloat =
pfloat
>>= (fun x -> if x % 1 = 0 then fail "Not a float" else preturn (FloatValue x))
let pError =
// this parser must consume some input,
// otherwise combined with `many` it would hang in a dead loop
skipAnyChar
>>. preturn Error
// Now, the combined parser:
let pCombined =
[ pMyFloat; pMyInt; pError ] // note, future parsers will be added here;
// mind the order as float supersedes the int,
// and Error must be the last
|> List.map (fun p -> p .>> ws) // I'm too lazy to add whitespase skipping
// into each individual parser
|> List.map attempt // each parser is optional
|> choice // on each iteration, one of the parsers must succeed
|> many // a loop
Note, the code above is capable working with any sources: strings, streams, or whatever. Your real app may need to work with files, but unit testing can be simplified by using just string list
.
// Now, applying the parser somewhere in the code:
let maybeParseResult =
match run pCombined myStringData with
| Success(result, _, _) -> Some result
| Failure(_, _, _) -> None // or anything that indicates general parse failure
UPD. I have edited the code according to comments. pMyFloat
was updated to ensure that the parsed value has non-zero fractional part.
FParsec has the numberLiteral
parser that can be used to solve the problem.
As a start you can use the example available at the link above:
open FParsec
open FParsec.Primitives
open FParsec.CharParsers
type Number = Int of int64
| Float of float
// -?[0-9]+(\.[0-9]*)?([eE][+-]?[0-9]+)?
let numberFormat = NumberLiteralOptions.AllowMinusSign
||| NumberLiteralOptions.AllowFraction
||| NumberLiteralOptions.AllowExponent
let pnumber : Parser<Number, unit> =
numberLiteral numberFormat "number"
|>> fun nl ->
if nl.IsInteger then Int (int64 nl.String)
else Float (float nl.String)```
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