feat(medusa): Parsing CSV files (#1572)
* add: csv parser * fix: tests * fix: linting + comment * add: missing dependency * fix: generic transformers * fix: address comments * fix: make parser options generic * add: support regex columns + fix missing columns bug * improve test case * add: support for reducer + tests * fix: add comments to csv parser
This commit is contained in:
Zakaria El Asri
@@ -0,0 +1,42 @@
|
||||
/**
|
||||
* Generic parsing interface. All different parsing implementations (csv, json, etc.) should implement this interface
|
||||
*/
|
||||
export interface IParser<TResult, TParseOptions> {
|
||||
/**
|
||||
*
|
||||
* @param readableStream readable stream to parse
|
||||
* @param options options used for parsing by underlying parser implementation
|
||||
*/
|
||||
parse(
|
||||
readableStream: NodeJS.ReadableStream,
|
||||
options?: TParseOptions
|
||||
): Promise<TResult[]>
|
||||
}
|
||||
|
||||
/**
|
||||
* Abstract class implementation of the IParser interface. All different parsing implementations should extend this class
|
||||
*/
|
||||
export abstract class AbstractParser<
|
||||
TSchema,
|
||||
TParserResult,
|
||||
TParseOptions,
|
||||
TOutputResult
|
||||
> implements IParser<TParserResult, TParseOptions>
|
||||
{
|
||||
protected readonly $$schema: TSchema
|
||||
|
||||
protected constructor(schema: TSchema) {
|
||||
this.$$schema = schema
|
||||
}
|
||||
|
||||
public abstract parse(
|
||||
readableStream: NodeJS.ReadableStream,
|
||||
options?: TParseOptions
|
||||
): Promise<TParserResult[]>
|
||||
|
||||
/**
|
||||
*
|
||||
* @param data data to be built after parsing. Includes validation according to schema, transformation of values, etc.
|
||||
*/
|
||||
public abstract buildData(data: TParserResult[]): Promise<TOutputResult[]>
|
||||
}
|
||||
@@ -0,0 +1,73 @@
|
||||
import { AwilixContainer } from "awilix"
|
||||
|
||||
/**
|
||||
* Generic validation interface used to run validation logic on every line or record.
|
||||
* All different validation objects should implement this interface
|
||||
*/
|
||||
export interface ICsvValidator<TCsvLine, TBuiltLine> {
|
||||
/**
|
||||
*
|
||||
* @param value value of column or property
|
||||
* @param context includes contextual information such as line number, line, etc.
|
||||
*/
|
||||
validate: (
|
||||
value: TBuiltLine,
|
||||
context: CsvParserContext<TCsvLine>
|
||||
) => Promise<boolean | never>
|
||||
}
|
||||
|
||||
export type CsvParserContext<TLine> = LineContext<TLine> & {
|
||||
column: string
|
||||
}
|
||||
|
||||
export type LineContext<TLine> = {
|
||||
lineNumber: number
|
||||
line: TLine
|
||||
}
|
||||
|
||||
/**
|
||||
* Abstract class implementation of the IValidator interface.
|
||||
* All validation objects part of the schema should extend this class.
|
||||
*/
|
||||
export abstract class AbstractCsvValidator<TCsvLine, TBuiltLine>
|
||||
implements ICsvValidator<TCsvLine, TBuiltLine>
|
||||
{
|
||||
constructor(protected readonly container: AwilixContainer) {}
|
||||
|
||||
abstract validate(
|
||||
builtLine: TBuiltLine,
|
||||
context: CsvParserContext<TCsvLine>
|
||||
): Promise<boolean | never>
|
||||
}
|
||||
|
||||
export type CsvSchemaColumn<TCsvLine, TBuiltLine> = {
|
||||
name: string
|
||||
required?: boolean
|
||||
validator?: AbstractCsvValidator<TCsvLine, TBuiltLine>
|
||||
} & (
|
||||
| {
|
||||
mapTo?: string
|
||||
transform?: ColumnTransformer<TCsvLine>
|
||||
}
|
||||
| {
|
||||
match?: RegExp
|
||||
reducer?: ColumnReducer<TCsvLine, TBuiltLine>
|
||||
transform?: ColumnTransformer<TCsvLine>
|
||||
}
|
||||
)
|
||||
|
||||
export type ColumnTransformer<TCsvLine> = (
|
||||
value: string,
|
||||
context: CsvParserContext<TCsvLine>
|
||||
) => unknown
|
||||
|
||||
export type ColumnReducer<TCsvLine = unknown, TBuiltLine = unknown> = (
|
||||
builtLine: TBuiltLine,
|
||||
key: string,
|
||||
value: string,
|
||||
context: CsvParserContext<TCsvLine>
|
||||
) => TBuiltLine
|
||||
|
||||
export type CsvSchema<TCsvLine = unknown, TBuiltLine = unknown> = {
|
||||
columns: CsvSchemaColumn<TCsvLine, TBuiltLine>[]
|
||||
}
|
||||
@@ -0,0 +1,403 @@
|
||||
import { createContainer } from "awilix"
|
||||
import { Readable } from "stream"
|
||||
import { AbstractCsvValidator } from "../../interfaces/csv-parser"
|
||||
import CsvParser from "../csv-parser"
|
||||
import { currencies } from "../../utils/currencies"
|
||||
|
||||
describe("CsvParser", () => {
|
||||
describe("parse", () => {
|
||||
const csvParser = new CsvParser(createContainer(), {
|
||||
columns: [],
|
||||
})
|
||||
|
||||
let csvContent =
|
||||
'title,subtitle\n"T-shirt","summer tee"\n"Sunglasses","Red sunglasses"'
|
||||
|
||||
let expectedProducts = [
|
||||
{
|
||||
title: "T-shirt",
|
||||
subtitle: "summer tee",
|
||||
},
|
||||
{
|
||||
title: "Sunglasses",
|
||||
subtitle: "Red sunglasses",
|
||||
},
|
||||
]
|
||||
|
||||
afterEach(() => {
|
||||
jest.clearAllMocks()
|
||||
})
|
||||
|
||||
it("given a readable stream, can parse the stream content", async () => {
|
||||
const stream = Readable.from(csvContent)
|
||||
const content = await csvParser.parse(stream)
|
||||
|
||||
expect(content).toEqual(expectedProducts)
|
||||
})
|
||||
})
|
||||
|
||||
describe("buildData", () => {
|
||||
describe("schema validation", () => {
|
||||
class TitleValidator extends AbstractCsvValidator {
|
||||
async validate(builtLine) {
|
||||
if (/\d/.test(builtLine["title"])) {
|
||||
throw new Error("title should not contain a number")
|
||||
}
|
||||
return true
|
||||
}
|
||||
}
|
||||
|
||||
const schema = {
|
||||
columns: [
|
||||
{
|
||||
name: "title",
|
||||
validator: new TitleValidator(createContainer()),
|
||||
},
|
||||
{
|
||||
name: "size",
|
||||
},
|
||||
{
|
||||
name: "height",
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
const csvParser = new CsvParser(createContainer(), schema)
|
||||
|
||||
it("given a line containing a column which is not defined in the schema, then validation should fail", async () => {
|
||||
try {
|
||||
await csvParser.buildData([
|
||||
{
|
||||
title: "sunglasses",
|
||||
size: "M",
|
||||
height: "100",
|
||||
first_name: "lebron",
|
||||
},
|
||||
])
|
||||
} catch (err) {
|
||||
expect(err.message).toEqual(
|
||||
"Unable to treat column first_name from the csv file. No target column found in the provided schema"
|
||||
)
|
||||
}
|
||||
})
|
||||
|
||||
it("given a line containing a column which does not pass a validation constraint, then validation should fail", async () => {
|
||||
try {
|
||||
await csvParser.buildData([
|
||||
{ title: "contains a number 1", size: "M", height: "100" },
|
||||
])
|
||||
} catch (err) {
|
||||
expect(err.message).toEqual("title should not contain a number")
|
||||
}
|
||||
})
|
||||
|
||||
it("given a line which passes all validation constraints, then should returned validated content", async () => {
|
||||
const content = await csvParser.buildData([
|
||||
{ title: "great product", size: "M", height: "100" },
|
||||
])
|
||||
|
||||
expect(content).toEqual([
|
||||
{
|
||||
title: "great product",
|
||||
size: "M",
|
||||
height: "100",
|
||||
},
|
||||
])
|
||||
})
|
||||
|
||||
it("given a line which does not provide a value for a required column, then should throw an error", async () => {
|
||||
try {
|
||||
await csvParser.buildData([{ size: "S", height: "100" }])
|
||||
} catch (err) {
|
||||
expect(err.message).toEqual(
|
||||
`Missing column(s) "title" from the given csv file`
|
||||
)
|
||||
}
|
||||
})
|
||||
|
||||
it("given a line which does not provide a value for multiple required columns, then should throw an error", async () => {
|
||||
try {
|
||||
await csvParser.buildData([{ size: "S" }])
|
||||
} catch (err) {
|
||||
expect(err.message).toEqual(
|
||||
`Missing column(s) "title", "height" from the given csv file`
|
||||
)
|
||||
}
|
||||
})
|
||||
|
||||
it("given a line which does not provide a value for a required column, then should throw an error", async () => {
|
||||
try {
|
||||
await csvParser.buildData([
|
||||
{ title: "t-shirt", height: "100", size: "" },
|
||||
])
|
||||
} catch (err) {
|
||||
expect(err.message).toEqual(
|
||||
`No value found for target column "size" in line 1 of the given csv file`
|
||||
)
|
||||
}
|
||||
})
|
||||
})
|
||||
|
||||
describe("mapTo", () => {
|
||||
const csvParser = new CsvParser(createContainer(), {
|
||||
columns: [
|
||||
{
|
||||
name: "title",
|
||||
mapTo: "product_title",
|
||||
},
|
||||
],
|
||||
})
|
||||
|
||||
it("given a mapTo field for a column, when building data including that column, should rename the column name to what mapTo refers to", async () => {
|
||||
const content = await csvParser.buildData([{ title: "a product" }])
|
||||
|
||||
expect(content).toEqual([
|
||||
{
|
||||
product_title: "a product",
|
||||
},
|
||||
])
|
||||
})
|
||||
})
|
||||
|
||||
describe("transformer", () => {
|
||||
const csvParser = new CsvParser(createContainer(), {
|
||||
columns: [
|
||||
{
|
||||
name: "title",
|
||||
},
|
||||
{
|
||||
name: "price usd",
|
||||
transform: (value) => Math.round(Number(value) * 100),
|
||||
},
|
||||
],
|
||||
})
|
||||
|
||||
it("given a transformer function for a column, when building data, should transform that column's value according to the transformation function", async () => {
|
||||
const content = await csvParser.buildData([
|
||||
{ title: "medusa t-shirt", "price usd": "19.99" },
|
||||
])
|
||||
|
||||
expect(content).toEqual([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"price usd": 1999,
|
||||
},
|
||||
])
|
||||
})
|
||||
})
|
||||
|
||||
describe("match", () => {
|
||||
describe("regex", () => {
|
||||
const csvParser = new CsvParser(createContainer(), {
|
||||
columns: [
|
||||
{
|
||||
name: "title",
|
||||
},
|
||||
{
|
||||
name: "prices",
|
||||
match: /.*Variant Price.*/i,
|
||||
transform: (value) => Math.round(Number(value) * 100),
|
||||
},
|
||||
],
|
||||
})
|
||||
|
||||
it("given a column with the match property as regex and a transformer, when building data, should resolve that column for all entries in the line that match the regex", async () => {
|
||||
const content = await csvParser.buildData([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"variant price usd": "19.99",
|
||||
"variant price cad": "26.79",
|
||||
"variant price dkk": "1389",
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
"variant price usd": "9.99",
|
||||
"variant price cad": "16.79",
|
||||
"variant price dkk": "389",
|
||||
},
|
||||
])
|
||||
|
||||
expect(content).toEqual([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"variant price usd": 1999,
|
||||
"variant price cad": 2679,
|
||||
"variant price dkk": 138900,
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
"variant price usd": 999,
|
||||
"variant price cad": 1679,
|
||||
"variant price dkk": 38900,
|
||||
},
|
||||
])
|
||||
})
|
||||
})
|
||||
|
||||
describe("reducer", () => {
|
||||
const schema = {
|
||||
columns: [
|
||||
{
|
||||
name: "title",
|
||||
},
|
||||
{
|
||||
name: "prices",
|
||||
match: /.*Variant Price ([a-z]+).*/i,
|
||||
reducer: (builtLine, key, value) => {
|
||||
const [, currency_code] = key.match(
|
||||
/.*Variant Price ([a-z]+).*/i
|
||||
)
|
||||
const existingPrices = builtLine.prices ?? []
|
||||
const price = {
|
||||
amount: Math.round(Number(value) * 100),
|
||||
currency_code,
|
||||
}
|
||||
return {
|
||||
...builtLine,
|
||||
prices: [...existingPrices, price],
|
||||
}
|
||||
},
|
||||
validator: {
|
||||
validate: (builtLine) => {
|
||||
const unexistingCurrency = builtLine.prices?.find(
|
||||
(price) => !currencies[price.currency_code.toUpperCase()]
|
||||
)
|
||||
if (unexistingCurrency) {
|
||||
throw new Error(
|
||||
`wrong currency: ${unexistingCurrency.currency_code}`
|
||||
)
|
||||
}
|
||||
return true
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
}
|
||||
const csvParser = new CsvParser(createContainer(), schema)
|
||||
|
||||
it("given a column with match and reducer properties, when building data, should return the result of the reducer function", async () => {
|
||||
const content = await csvParser.buildData([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"variant price usd": "19.99",
|
||||
"variant price cad": "26.79",
|
||||
"variant price dkk": "1389",
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
"variant price usd": "9.99",
|
||||
"variant price cad": "16.79",
|
||||
"variant price dkk": "389",
|
||||
},
|
||||
])
|
||||
|
||||
expect(content).toEqual([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
prices: [
|
||||
{
|
||||
currency_code: "usd",
|
||||
amount: 1999,
|
||||
},
|
||||
{
|
||||
currency_code: "cad",
|
||||
amount: 2679,
|
||||
},
|
||||
{
|
||||
currency_code: "dkk",
|
||||
amount: 138900,
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
prices: [
|
||||
{
|
||||
currency_code: "usd",
|
||||
amount: 999,
|
||||
},
|
||||
{
|
||||
currency_code: "cad",
|
||||
amount: 1679,
|
||||
},
|
||||
{
|
||||
currency_code: "dkk",
|
||||
amount: 38900,
|
||||
},
|
||||
],
|
||||
},
|
||||
])
|
||||
})
|
||||
|
||||
it("given a column with match and reducer properties, when building data, should run validation on the built data", async () => {
|
||||
try {
|
||||
await csvParser.buildData([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"variant price usd": "19.99",
|
||||
"variant price cad": "26.79",
|
||||
"variant price grp": "1389",
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
"variant price usd": "9.99",
|
||||
"variant price cad": "16.79",
|
||||
"variant price grp": "389",
|
||||
},
|
||||
])
|
||||
} catch (err) {
|
||||
expect(err.message).toEqual("wrong currency: grp")
|
||||
}
|
||||
})
|
||||
|
||||
describe("invalid column properties", () => {
|
||||
const schema = {
|
||||
columns: [
|
||||
{
|
||||
name: "title",
|
||||
},
|
||||
{
|
||||
name: "variants",
|
||||
match: /.*Variant Price ([a-z]+).*/i,
|
||||
mapTo: "prices",
|
||||
},
|
||||
],
|
||||
}
|
||||
const csvParser = new CsvParser(createContainer(), schema)
|
||||
|
||||
it("given a column with match and mapTo property, when building data, then the mapTo property should be ignored", async () => {
|
||||
const content = await csvParser.buildData([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"variant price usd": "19.99",
|
||||
"variant price cad": "26.79",
|
||||
"variant price dkk": "1389",
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
"variant price usd": "9.99",
|
||||
"variant price cad": "16.79",
|
||||
"variant price dkk": "389",
|
||||
},
|
||||
])
|
||||
|
||||
expect(content).toEqual([
|
||||
{
|
||||
title: "medusa t-shirt",
|
||||
"variant price usd": "19.99",
|
||||
"variant price cad": "26.79",
|
||||
"variant price dkk": "1389",
|
||||
},
|
||||
{
|
||||
title: "medusa sunglasses",
|
||||
"variant price usd": "9.99",
|
||||
"variant price cad": "16.79",
|
||||
"variant price dkk": "389",
|
||||
},
|
||||
])
|
||||
})
|
||||
})
|
||||
})
|
||||
})
|
||||
})
|
||||
})
|
||||
@@ -0,0 +1,202 @@
|
||||
import { AwilixContainer } from "awilix"
|
||||
import { difference } from "lodash"
|
||||
import Papa, { ParseConfig } from "papaparse"
|
||||
import { AbstractParser } from "../interfaces/abstract-parser"
|
||||
import { CsvParserContext, CsvSchema } from "../interfaces/csv-parser"
|
||||
|
||||
const DEFAULT_PARSE_OPTIONS = {
|
||||
dynamicTyping: true,
|
||||
header: true,
|
||||
}
|
||||
|
||||
class CsvParser<
|
||||
TSchema extends CsvSchema<TParserResult, TOutputResult> = CsvSchema,
|
||||
TParserResult = unknown,
|
||||
TOutputResult = unknown
|
||||
> extends AbstractParser<TSchema, TParserResult, ParseConfig, TOutputResult> {
|
||||
protected readonly $$delimiter: string = ";"
|
||||
|
||||
constructor(
|
||||
protected readonly container: AwilixContainer,
|
||||
schema: TSchema,
|
||||
delimiter?: string
|
||||
) {
|
||||
super(schema)
|
||||
if (delimiter) {
|
||||
this.$$delimiter = delimiter
|
||||
}
|
||||
}
|
||||
|
||||
public async parse(
|
||||
readableStream: NodeJS.ReadableStream,
|
||||
options: ParseConfig = DEFAULT_PARSE_OPTIONS
|
||||
): Promise<TParserResult[]> {
|
||||
const csvStream = Papa.parse(Papa.NODE_STREAM_INPUT, options)
|
||||
|
||||
const parsedContent: TParserResult[] = []
|
||||
readableStream.pipe(csvStream)
|
||||
for await (const chunk of csvStream) {
|
||||
parsedContent.push(chunk)
|
||||
}
|
||||
|
||||
return parsedContent
|
||||
}
|
||||
|
||||
async buildData(data: TParserResult[]): Promise<TOutputResult[]> {
|
||||
const validatedData = [] as TOutputResult[]
|
||||
for (let i = 0; i < data.length; i++) {
|
||||
const builtLine = await this._buildLine(data[i], i + 1)
|
||||
validatedData.push(builtLine)
|
||||
}
|
||||
return validatedData
|
||||
}
|
||||
|
||||
private async _buildLine(
|
||||
line: TParserResult,
|
||||
lineNumber: number
|
||||
): Promise<TOutputResult> {
|
||||
let outputTuple = {} as TOutputResult
|
||||
const columnMap = this.buildColumnMap_(this.$$schema.columns)
|
||||
|
||||
const tupleKeys = Object.keys(line)
|
||||
|
||||
/**
|
||||
* map which keeps track of the columns processed
|
||||
* used to detect any missing columns which are present in the schema but not in the line
|
||||
*/
|
||||
const processedColumns = {}
|
||||
for (const tupleKey of tupleKeys) {
|
||||
const column = this.resolveColumn_(tupleKey, columnMap)
|
||||
|
||||
/**
|
||||
* if the tupleKey does not correspond to any column defined in the schema
|
||||
*/
|
||||
if (!column) {
|
||||
throw new Error(
|
||||
`Unable to treat column ${tupleKey} from the csv file. No target column found in the provided schema`
|
||||
)
|
||||
}
|
||||
|
||||
processedColumns[column.name] = true
|
||||
|
||||
/**
|
||||
* if the value corresponding to the tupleKey is empty and the column is required in the schema
|
||||
*/
|
||||
if (!line[tupleKey] && column.required) {
|
||||
throw new Error(
|
||||
`No value found for target column "${column.name}" in line ${lineNumber} of the given csv file`
|
||||
)
|
||||
}
|
||||
|
||||
const context = {
|
||||
line,
|
||||
lineNumber,
|
||||
column: column.name,
|
||||
tupleKey,
|
||||
}
|
||||
|
||||
outputTuple = this.resolveTuple_(outputTuple, column, context)
|
||||
}
|
||||
|
||||
/**
|
||||
* missing columns = columns defined in the schema - columns present in the line
|
||||
*/
|
||||
const missingColumns = difference(
|
||||
Object.keys(columnMap),
|
||||
Object.keys(processedColumns)
|
||||
)
|
||||
|
||||
if (missingColumns.length > 0) {
|
||||
throw new Error(
|
||||
`Missing column(s) ${formatMissingColumns(
|
||||
missingColumns
|
||||
)} from the given csv file`
|
||||
)
|
||||
}
|
||||
|
||||
/**
|
||||
* Runs the validation defined in the schema columns
|
||||
*/
|
||||
for (const column of this.$$schema.columns) {
|
||||
const context = {
|
||||
line,
|
||||
lineNumber,
|
||||
column: column.name,
|
||||
}
|
||||
|
||||
if (column.validator) {
|
||||
await column.validator.validate(outputTuple, context)
|
||||
}
|
||||
}
|
||||
|
||||
return outputTuple
|
||||
}
|
||||
|
||||
private buildColumnMap_(
|
||||
columns: TSchema["columns"]
|
||||
): Record<string, TSchema["columns"][number]> {
|
||||
return columns.reduce((map, column) => {
|
||||
if (typeof column.name === "string") {
|
||||
map[column.name] = column
|
||||
}
|
||||
return map
|
||||
}, {})
|
||||
}
|
||||
|
||||
private resolveColumn_(
|
||||
tupleKey: string,
|
||||
columnMap: Record<string, TSchema["columns"][number]>
|
||||
): TSchema["columns"][number] | undefined {
|
||||
if (columnMap[tupleKey]) {
|
||||
return columnMap[tupleKey]
|
||||
}
|
||||
|
||||
const matchedColumn = this.$$schema.columns.find((column) =>
|
||||
"match" in column &&
|
||||
typeof column.match === "object" &&
|
||||
column.match instanceof RegExp
|
||||
? column.match.test(tupleKey)
|
||||
: false
|
||||
)
|
||||
|
||||
return matchedColumn
|
||||
}
|
||||
|
||||
private resolveTuple_(
|
||||
tuple: TOutputResult,
|
||||
column: TSchema["columns"][number],
|
||||
context: CsvParserContext<TParserResult> & { tupleKey: string }
|
||||
): TOutputResult {
|
||||
const outputTuple = { ...tuple }
|
||||
const { tupleKey, ...csvContext } = context
|
||||
const { line } = csvContext
|
||||
|
||||
let resolvedKey = tupleKey
|
||||
/**
|
||||
* if match is provided, then we should call the reducer if it's defined
|
||||
* otherwise, before using the mapTo property, we should make sure match was not provided
|
||||
*/
|
||||
if ("match" in column && column.reducer) {
|
||||
return column.reducer(outputTuple, tupleKey, line[tupleKey], csvContext)
|
||||
} else if (!("match" in column) && "mapTo" in column && column.mapTo) {
|
||||
resolvedKey = column.mapTo
|
||||
}
|
||||
|
||||
const resolvedValue = column.transform
|
||||
? column.transform(line[tupleKey], csvContext)
|
||||
: line[tupleKey]
|
||||
|
||||
outputTuple[resolvedKey] = resolvedValue
|
||||
|
||||
return outputTuple
|
||||
}
|
||||
}
|
||||
|
||||
const formatMissingColumns = (list: string[]): string =>
|
||||
list.reduce(
|
||||
(text, curr, i, array) =>
|
||||
text + (i < array.length - 1 ? `"${curr}", ` : `"${curr}"`),
|
||||
""
|
||||
)
|
||||
|
||||
export default CsvParser
|
||||
Reference in New Issue
Block a user