Does Go std lib have a func to read csv file into []map[string]string?

Based on reply, it sounds like there is nothing in the standard libraries, like ioutil, to read a csv file into a map.

The following function given a path to a csv file will convert it into a slice of map[string]string.

Update: based on a comment I decided to provide my CSVFileToMap() and MapToCSV() func that writes the map back to a csv file.

    package main

    import (
        "os"
    "encoding/csv"
        "fmt"
    "strings"
    )



    // CSVFileToMap  reads csv file into slice of map
    // slice is the line number
    // map[string]string where key is column name
    func CSVFileToMap(filePath string) (returnMap []map[string]string, err error) {



        // read csv file
        csvfile, err := os.Open(filePath)
        if err != nil {
            return nil, fmt.Errorf(err.Error())
        }

        defer csvfile.Close()

        reader := csv.NewReader(csvfile)

        rawCSVdata, err := reader.ReadAll()
        if err != nil {
            return nil, fmt.Errorf(err.Error())
        }

        header := []string{} // holds first row (header)
        for lineNum, record := range rawCSVdata {

            // for first row, build the header slice
            if lineNum == 0 {
                for i := 0; i < len(record); i++ {
                    header = append(header, strings.TrimSpace(record[i]))
                }
            } else {
                // for each cell, map[string]string k=header v=value
                line := map[string]string{}
                for i := 0; i < len(record); i++ {
                    line[header[i]] = record[i]
                }
                returnMap = append(returnMap, line)
            }
        }

        return
    }



    // MapToCSVFile  writes slice of map into csv file
    // filterFields filters to only the fields in the slice, and maintains order when writing to file
    func MapToCSVFile(inputSliceMap []map[string]string, filePath string, filterFields []string) (err error) {

        var headers []string  // slice of each header field
        var line []string     // slice of each line field
        var csvLine string    // string of line converted to csv
        var CSVContent string // final output of csv containing header and lines

        // iter over slice to get all possible keys (csv header) in the maps
        // using empty Map[string]struct{} to get UNIQUE Keys; no value needed
        var headerMap = make(map[string]struct{})
        for _, record := range inputSliceMap {
            for k, _ := range record {
                headerMap[k] = struct{}{}
            }
        }

        // convert unique headersMap to slice
        for headerValue, _ := range headerMap {
            headers = append(headers, headerValue)
        }

        // filter to filteredFields and maintain order
        var filteredHeaders []string
        if len(filterFields) > 0 {
            for _, filterField := range filterFields {
                for _, headerValue := range headers {
                    if filterField == headerValue {
                        filteredHeaders = append(filteredHeaders, headerValue)
                    }
                }
            }
        } else {
            filteredHeaders = append(filteredHeaders, headers...)
            sort.Strings(filteredHeaders) // alpha sort headers
        }

        // write headers as the first line
        csvLine, _ = WriteAsCSV(filteredHeaders)
        CSVContent += csvLine + "\n"

        // iter over inputSliceMap to get values for each map
        // maintain order provided in header slice
        // write to csv
        for _, record := range inputSliceMap {
            line = []string{}

            // lines
            for k, _ := range filteredHeaders {
                line = append(line, record[filteredHeaders[k]])
            }
            csvLine, _ = WriteAsCSV(line)
            CSVContent += csvLine + "\n"
        }

        // make the dir incase it's not there
        err = os.MkdirAll(filepath.Dir(filePath), os.ModePerm)
        if err != nil {
            return err
        }

        // write out the csv contents to file
        ioutil.WriteFile(filePath, []byte(CSVContent), os.FileMode(0644))
        if err != nil {
            return err
        }

        return
    }

    func WriteAsCSV(vals []string) (string, error) {
        b := &bytes.Buffer{}
        w := csv.NewWriter(b)
        err := w.Write(vals)
        if err != nil {
            return "", err
        }
        w.Flush()
        return strings.TrimSuffix(b.String(), "\n"), nil
    }

Finally, here is a test case to show it's usage:

    func TestMapToCSVFile(t *testing.T) {
    // note: test case requires the file ExistingCSVFile exist on disk with a 
    // few rows of csv data
        SomeKey := "some_column"
        ValueForKey := "some_value"
        OutputCSVFile := `.\someFile.csv`
        ExistingCSVFile := `.\someExistingFile.csv`

        // read csv file
        InputCSVSliceMap, err := CSVFileToMap(ExistingCSVFile)
        if err != nil {
            t.Fatalf("MapToCSVFile() failed %v", err)
        }

        // add a field in the middle of csv
        InputCSVSliceMap[2][SomeKey] = ValueForKey // add a new column name 
        "some_key" with a value of "some_value" to the second line. 

        err = MapToCSVFile(InputCSVSliceMap, OutputReport, nil)
        if err != nil {
            t.Fatalf("MapToCSVFile() failed writing outputReport %v", err)
        }

        // VALIDATION: check that Key field is present in MapToCSVFile output file
        // read Output csv file
        OutputCSVSliceMap, err := CSVFileToMap(OutputCSVFile)
        if err != nil {
            t.Fatalf("MapToCSVFile() failed reading output file %v", err)
        }

        // check that the added key has a value for Key
        if OutputCSVSliceMap[2][SomeKey] != ValueForKey {
            t.Fatalf("MapToCSVFile() expected row to contains key value: %v", ValueForKey)
        }
    }

It is disappointing that the Go csv package does not contain anything as useful as the csv.DictReader we have in Python (https://docs.python.org/3/library/csv.html#csv.DictReader).

However, I have found the csvutil package (https://github.com/jszwec/csvutil) very useful. It doesn't seem to support unmarshalling records to map[string]string but you can unmarshal directly to a struct type, which IMO is more useful.