f# how to access the data from another function? - f#

I am having trouble with accessing a value from another function in f sharp. Below is my code, I am taking the user input a student name and 3 exam scores and calculating their averages and saving that in the variable "let average" of the InputStudents function. Now I am trying to access that value in another function PringtAverages as shown below, but it would not compile. I need help to fix this issue. Appreciate if you can help. Thank you.
let rec InputStudents students =
let line = System.Console.ReadLine()
match line with
| "#" -> (List.rev students)
| _ ->
let data = line.Split ' '
//Getting the student name at data.[0], and getting the 3 exam
//scores in data.[1]..[3].
let student = (data.[0], [int(data.[1]); int(data.[2]); int(data.[3])])
//calculating the average by for the 3 exam scores
let average = (data.[0], [(float(data.[1]) + float(data.[2]) + float(data.[3]))/3.0])
InputStudents (student:: students)
//Function below I am trying to get the above-calculated averages and print
let rec PrintAverages L =
match L with
| [] -> ()
| e::rest ->
let avg = InputStudents[]
printfn "%A: %A" "netid" avg.average //Here I am trying to print
//the average calculated in the function
//InputStudents[] above
PrintAverages rest

That is not possible.
You cannot access internal calculations from another function. What you need to do is return the values that you need to use outside.
In your case your function InputStudents has the following signature:
(string * int list) list -> (string * int list) list
Which means it returns a list with each student name and notes. The average is calculated but then is lost, because it is not used anywhere. If you want to be able to print it in another function you need to include it as part of the return value:
...
let name = data.[0]
let scores = [float data.[1]
float data.[2]
float data.[3] ]
//calculating the average by for the 3 exam scores
let average = List.average scores
InputStudents ((name, scores, average) :: students)
now the signature is this:
(string * float list * float) list -> (string * float list * float) list
indicating it returns a tuple for each student that includes name, notes and average.
Now lets address the PrintAverages function.
The function has a problem: it calls InputStudents and it calls itself recursively. What you want to do is call first InputStudents and then pass the result to PrintAverages:
InputStudents [] |> PrintAverages
Also in your match statement you can unpack the tuple that you are receiving. Right now you have e::rest which gives you one element and the rest of the list. That element would be of type string * float list * float which you can unpack like this:
let name, notes, average = e
or directly in the match statement:
match L with
| [] -> ()
| (name, notes, average) :: rest ->

Related

F# Change element in list and return full new list

I have a list of type (string * (int * int)) list. I want to be able to search through the list, finding the right element by it's string identifier, do a calculation on one of the ints, and then return the full, modified list.
Example:
Given a list
let st = [("a1",(100,10)); ("a2",(50,20)); ("a3",(25,40))]
I'm trying to make a function which gets one of the elements and subtracts number from one of the ints in the tuple.
get ("a2",10) st
//Expected result: st' = [("a1",(100,10)); ("a2",(40,20)); ("a3",(25,40))]
I feel I'm almost there, but am a little stuck with the following function:
let rec get (a,k) st =
match st with
| (a',(n',p'))::rest when a'=a && k<=n' -> (n'-k,p')::rest
| (a',(n',p'))::rest -> (n',p')::get (a,k) rest
| _ -> failwith "Illegal input"
This returns [("a2",(40,20)); ("a3",(25,40))] and is thus missing the first a1 element. Any hints?
Lists are immutable, so if you want to "change one element" you are really creating a new list with one element transformed. The easiest way to do a transformation like this is to use List.map function. I would write something like:
let updateElement key f st =
st |> List.map (fun (k, v) -> if k = key then k, f v else k, v)
updateElement is a helper that takes a key, update function and an input. It returns list where the element with the given key has been transformed using the given function. For example, to increment the first number associated with a2, you can write:
let st = [("a1",(100,10)); ("a2",(50,20)); ("a3",(25,40))]
st |> updateElement "a2" (fun (a, b) -> a + 10, b)
I was looking for a function which would update an element in a list based on the element's data. I couldn't find one in F#5, so wrote one using Tomas' solution:
let updateAt (elemFindFunc: 'a -> bool) (newElem: 'a) (source: 'a list) : 'a list =
source
|> List.map
(fun elem ->
let foundElem = elemFindFunc elem
if foundElem then newElem else elem)
elemFindFunc is the function which consumes an element and returns true if this is the element we want to replace. If this function returns true for multiple elements, then those will be replaced by newElem. Also, if elemFindFunc evaluates to false for all elements, the list will be unaltered.
newElem is the new value you want to replace with. newElem could be replaced by a function like valueFunc: 'a -> 'a if you want to process the element before inserting it.

Add calculated key to collection

Please consider this dataset, composed by man and woman, and that I filter in a second moment according to few variables:
type ls = JsonProvider<"...">
let dt = ls.GetSamples()
let dt2 =
dt |> Seq.filter (fun c -> c.Sex = "male" && c.Height > Some 150)
dt2
[{"sex":"male","height":180,"weight":85},
{"sex":"male","height":160" "weight":60},
{"sex":"male","height":180,"weight":85}]
Lets suppose that I would like to add a fourth key "body mass index" or "bmi", and that its value is roughly given by "weight"/"height". Hence I expect:
[{"sex":"male","height":180,"weight":85, "bmi":(180/85)},
{"sex":"male","height":160" "weight":60, "bmi":(160/60},
{"sex":"male","height":180,"weight":85, "bmi":(180/85)}]
I thought that map.Add may help.
let dt3 = dt2.Add("bmi", (dt2.Height/dt2.Weight))
Unfortunately, it returns an error:
error FS0039: The field, constructor or member 'Add' is not defined
I am sure there are further errors in my code, but without this function I cannot actually look for them. Am I, at least, approaching the problem correctly?
Creating modified versions of the JSON is sadly one thing that the F# Data type provider does not make particularly easy. What makes that hard is the fact that we can infer the type from the source JSON, but we cannot "predict" what kind of fields people might want to add.
To do this, you'll need to access the underlying representation of the JSON value and operate on that. For example:
type ls = JsonProvider<"""
[{"sex":"male","height":180,"weight":85},
{"sex":"male","height":160,"weight":60},
{"sex":"male","height":180,"weight":85}]""">
let dt = ls.GetSamples()
let newJson =
dt
|> Array.map (fun recd ->
// To do the calculation, you can access the fields via inferred types
let bmi = float recd.Height / float recd.Weight
// But now we need to look at the underlying value, check that it is
// a record and extract the properties, which is an array of key-value pairs
match recd.JsonValue with
| JsonValue.Record props ->
// Append the new property to the existing properties & re-create record
Array.append [| "bmi", JsonValue.Float bmi |] props
|> JsonValue.Record
| _ -> failwith "Unexpected format" )
// Re-create a new JSON array and format it as JSON
JsonValue.Array(newJson).ToString()

F# Finding a Set in a Map

So I have a database containing cars with an associated number and description. That database looks like this:
type Database = Map<CarNo, CarDesc>
type CarNo = int
type CarDesc = Name * Price
type Name = string
type Price = int
If I want to get the sum of the price of all the cars, based on the numbers, how would I make that function? I'm a little stuck on how to begin.
Any hints appreciated!
I would imagine that a function like this one would sum the prices of all the cars in your map. But contra the question title, there's no sets involved here.
let sumPrices (db:Database) =
db |> Map.fold (fun acc _ (_, price) -> acc + float price) 0.0
db |> Seq.sumBy (fun (KeyValue (_, (_, price))) -> price)

F# Read Fixed Width Text File

Hi I'm looking to find the best way to read in a fixed width text file using F#. The file will be plain text, from one to a couple of thousand lines long and around 1000 characters wide. Each line contains around 50 fields, each with varying lengths. My initial thoughts were to have something like the following
type MyRecord = {
Name : string
Address : string
Postcode : string
Tel : string
}
let format = [
(0,10)
(10,50)
(50,7)
(57,20)
]
and read each line one by one, assigning each field by the format tuple(where the first item is the start character and the second is the number of characters wide).
Any pointers would be appreciated.
The hardest part is probably to split a single line according to the column format. It can be done something like this:
let splitLine format (line : string) =
format |> List.map (fun (index, length) -> line.Substring(index, length))
This function has the type (int * int) list -> string -> string list. In other words, format is an (int * int) list. This corresponds exactly to your format list. The line argument is a string, and the function returns a string list.
You can map a list of lines like this:
let result = lines |> List.map (splitLine format)
You can also use Seq.map or Array.map, depending on how lines is defined. Such a result will be a string list list, and you can now map over such a list to produce a MyRecord list.
You can use File.ReadLines to get a lazily evaluated sequence of strings from a file.
Please note that the above is only an outline of a possible solution. I left out boundary checks, error handling, and such. The above code may contain off-by-one errors.
Here's a solution with a focus on custom validation and error handling for each field. This might be overkill for a data file consisting of just numeric data!
First, for these kinds of things, I like to use the parser in Microsoft.VisualBasic.dll as it's already available without using NuGet.
For each row, we can return the array of fields, and the line number (for error reporting)
#r "Microsoft.VisualBasic.dll"
// for each row, return the line number and the fields
let parserReadAllFields fieldWidths textReader =
let parser = new Microsoft.VisualBasic.FileIO.TextFieldParser(reader=textReader)
parser.SetFieldWidths fieldWidths
parser.TextFieldType <- Microsoft.VisualBasic.FileIO.FieldType.FixedWidth
seq {while not parser.EndOfData do
yield parser.LineNumber,parser.ReadFields() }
Next, we need a little error handling library (see http://fsharpforfunandprofit.com/rop/ for more)
type Result<'a> =
| Success of 'a
| Failure of string list
module Result =
let succeedR x =
Success x
let failR err =
Failure [err]
let mapR f xR =
match xR with
| Success a -> Success (f a)
| Failure errs -> Failure errs
let applyR fR xR =
match fR,xR with
| Success f,Success x -> Success (f x)
| Failure errs,Success _ -> Failure errs
| Success _,Failure errs -> Failure errs
| Failure errs1, Failure errs2 -> Failure (errs1 # errs2)
Then define your domain model. In this case, it is the record type with a field for each field in the file.
type MyRecord =
{id:int; name:string; description:string}
And then you can define your domain-specific parsing code. For each field I have created a validation function (validateId, validateName, etc).
Fields that don't need validation can pass through the raw data (validateDescription).
In fieldsToRecord the various fields are combined using applicative style (<!> and <*>).
For more on this, see http://fsharpforfunandprofit.com/posts/elevated-world-3/#validation.
Finally, readRecords maps each input row to the a record Result and chooses the successful ones only. The failed ones are written to a log in handleResult.
module MyFileParser =
open Result
let createRecord id name description =
{id=id; name=name; description=description}
let validateId (lineNo:int64) (fields:string[]) =
let rawId = fields.[0]
match System.Int32.TryParse(rawId) with
| true, id -> succeedR id
| false, _ -> failR (sprintf "[%i] Can't parse id '%s'" lineNo rawId)
let validateName (lineNo:int64) (fields:string[]) =
let rawName = fields.[1]
if System.String.IsNullOrWhiteSpace rawName then
failR (sprintf "[%i] Name cannot be blank" lineNo )
else
succeedR rawName
let validateDescription (lineNo:int64) (fields:string[]) =
let rawDescription = fields.[2]
succeedR rawDescription // no validation
let fieldsToRecord (lineNo,fields) =
let (<!>) = mapR
let (<*>) = applyR
let validatedId = validateId lineNo fields
let validatedName = validateName lineNo fields
let validatedDescription = validateDescription lineNo fields
createRecord <!> validatedId <*> validatedName <*> validatedDescription
/// print any errors and only return good results
let handleResult result =
match result with
| Success record -> Some record
| Failure errs -> printfn "ERRORS %A" errs; None
/// return a sequence of records
let readRecords parserOutput =
parserOutput
|> Seq.map fieldsToRecord
|> Seq.choose handleResult
Here's an example of the parsing in practice:
// Set up some sample text
let text = """01name1description1
02name2description2
xxname3badid-------
yy badidandname
"""
// create a low-level parser
let textReader = new System.IO.StringReader(text)
let fieldWidths = [| 2; 5; 11 |]
let parserOutput = parserReadAllFields fieldWidths textReader
// convert to records in my domain
let records =
parserOutput
|> MyFileParser.readRecords
|> Seq.iter (printfn "RECORD %A") // print each record
The output will look like:
RECORD {id = 1;
name = "name1";
description = "description";}
RECORD {id = 2;
name = "name2";
description = "description";}
ERRORS ["[3] Can't parse id 'xx'"]
ERRORS ["[4] Can't parse id 'yy'"; "[4] Name cannot be blank"]
By no means is this the most efficient way to parse a file (I think there are some CSV parsing libraries available on NuGet that can do validation while parsing) but it does show how you can have complete control over validation and error handling if you need it.
A record of 50 fields is a bit unwieldy, therefore alternate approaches which allow dynamic generation of the data structure may be preferable (eg. System.Data.DataRow).
If it has to be a record anyway, you could spare at least the manual assignment to each record field and populate it with the help of Reflection instead. This trick relies on the field order as they are defined. I am assuming that every column of fixed width represents a record field, so that start indices are implied.
open Microsoft.FSharp.Reflection
type MyRecord = {
Name : string
Address : string
City : string
Postcode : string
Tel : string } with
static member CreateFromFixedWidth format (line : string) =
let fields =
format
|> List.fold (fun (index, acc) length ->
let str = line.[index .. index + length - 1].Trim()
index + length, box str :: acc )
(0, [])
|> snd
|> List.rev
|> List.toArray
FSharpValue.MakeRecord(
typeof<MyRecord>,
fields ) :?> MyRecord
Example data:
"Postman Pat " +
"Farringdon Road " +
"London " +
"EC1A 1BB" +
"+44 20 7946 0813"
|> MyRecord.CreateFromFixedWidth [16; 16; 16; 8; 16]
// val it : MyRecord = {Name = "Postman Pat";
// Address = "Farringdon Road";
// City = "London";
// Postcode = "EC1A 1BB";
// Tel = "+44 20 7946 0813";}

Appropriate use of active patterns in F#

I'm using an active pattern to parse usage events in a csv formatted usage log. The active pattern part is listed below. Parsing the whole file in works well and the sequence that is produced is filled with all sorts of UsageEvents.
type SystemName = string
type SystemVersion = string
type MAC = string
type Category = string
type Game = string
type Setting = string
type StartupLocation = string
type UsageEvent =
| SystemStart of DateTime * SystemVersion * SystemName * MAC
| SystemEnd of DateTime
| GameStart of DateTime * Category * Game * Setting * StartupLocation
| GameEnd of DateTime * Category * Game
| Other
let (|SystemStart|SystemEnd|GameStart|GameEnd|Other|) (input : string list) =
match List.nth input 0 with
| "SystemStartedEvent" ->
SystemStart (DateTime.Parse (List.nth input 1), List.nth input 2, List.nth input 3, List.nth input 4)
| "SystemEndedEvent" ->
SystemEnd (DateTime.Parse (List.nth input 1))
| "GameStartedEvent" ->
GameStart (DateTime.Parse (List.nth input 1), List.nth input 2, List.nth input 3, List.nth input 4, List.nth input 5)
| "GameEndedEvent" ->
GameEnd (DateTime.Parse (List.nth input 1), List.nth input 2, List.nth input 3)
| _ ->
Other
The problem I have is that I'm probably using the ActivePattern in the wrong way. I'd like to walk the list to create a tree out of it based on some logic, but I have no way to match an entry in the sequence after parsing.
let CountSystemStart (entries : UsageEvent list) =
let rec loop sum = function
| SystemStart(_,_,_,_) -> sum + 1
| _ -> sum
loop 0 entries
This matching does not work because the loop function required a string list. In what other way could I use the data contained in the unions or should I match the input and then store it in a regular type?
To add to #Petr's answer - UsageEvent cases and your active pattern cases have the same names, so the active pattern which is defined later shadows the union type. That's where the string list thing comes from, most likely.
I would just drop the active pattern altogether, and add a Parse function (or rather a ParseParts, since you want to feed it a list of strings) to the UsageEvent.
type UsageEvent =
| SystemStart of DateTime * SystemVersion * SystemName * MAC
| (...and so on...)
static member ParseParts (input: string list) =
match input with
| ["SystemStartedEvent"; date; version; name; mac] ->
SystemStart (DateTime.Parse date, version, name, mac)
| (...and so on...)
Active patterns are cute, but you really need a good scenario for them to shine. Otherwise if you can get away with using a plain function, just use a plain function.
There are 2 problems with this code:
Discriminated union UsageEvent and active pattern choice functions have the same names
recursive loop function is not recursive as it is written - it doesn't call itself.
When you are matching on UsageEvent list try use full type name.
I would rewrite your CountSystemStart function as:
let CountSystemStart (entries : UsageEvent list) =
let rec loop sum = function
| [] -> sum
| (UsageEvent.SystemStart(_))::rest -> loop (sum + 1) rest
| _::rest -> loop sum rest
loop 0 entries

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