datapipe-js/utils

datapipe-js/utils is a set of JavaScript utility and helper functions for parsing, converting many other data management tasks

parseCsv

Parse Csv text into array of items. It automatically recognizes Dates, numbers and booleans. Also, provides number of other options to skip values converts etc

parseCsv(content: string, options?: ParsingOptions): ScalarObject[]

Parsing options:

Name	Definition	Default Value
delimiter	Define delimiter	','
skipRows	Rows to skip	0
textFields	a list of text fields what requires NO conversion	[]
dateFields	a list of date fields (string or string[]) e.g. ['Date1', ['Date2', 'MM/dd/yyyy'], ['Date3', 'yyyyMM']]	[]
numberFields	A list of fields what should be parsed as numbers or stay blank	[]
booleanFields	A list of boolean fields	[]
skipUntil	A callback function to provide skip initial rows. (tokens: string[]) => boolean
takeWhile	A callback function to provide a take while rows (tokens: string[]) => boolean
elementSelector	element definition clallback (fieldDescriptions: FieldDescription[], tokens: string[]) => any

Date and number fields will be converted automatically. In most cases you don't have to confugire fields. Please use textFields property if you don't want some particular field to be converted. Also, use dateFields to specify date format e.g. US date: MM/dd/yyyy.

parseCsvToTable

Parse Csv text into tables of string values. It does not resolves any types, but it provides suggestions. All other features like skipWhile, take while works well there

parseCsvToTable(content: string, options?: ParsingOptions): StringsDataTable

toCsv

Converts array to the delimiter (comma) separated value

toCsv(array: ScalarObject[], delimiter = ','): string

fromTable

Converts rows and columns to a list of ScalarObjects.

• rowsOrTable Table data or Array of values .
• fieldNames Column names. If not provided then, it will be auto generated
• fieldDataTypes Column names

fromTable(

rowsOrTable: PrimitiveType[][] | TableDto,

fieldNames?: string[],

fieldDataTypes?: DataTypeName[]

): ScalarObject[]

toTable

Converts an array of ScalarObjects into the table. An efficient format to transfer over the wire

• values an array of ScalarObjects

toTable(values: ScalarObject[]): TableDto

Takes an array

[

{f1: 11, f2: 12, f3: 13},

{f1: 21, f2: 22, f3: 23},

{f1: 31, f2: 32, f3: 33}

]

Converts to

{

fieldNames: ["f1", "f2", "f3"],

rows:[

[11, 12, 13],

[21, 22, 23],

[31, 32, 33]

]

}

toObject

Converts array of items to the object map. Where key selector can be defined.

• array array to be converted
• keyField a key field selected

toObject(array: any[], keyField: string | string[] | Selector<any, string>): Record<string, any>

toSeries

Convert array into an object of series.

const array = [

{f1: 11, f2: 12, f3: 13},

{f1: 21, f2: 22, f3: 23},

{f1: 31, f2: 32, f3: 33},

]

consoe.log(toSeries(object))

// output object

// {

// f1: [11, 21, 31],

// f2: [12, 22, 32],

// f3: [13, 23, 33]

//}

parseDatetimeOrNull

Parses string to the Date or returns null. It is more efficient parser than new Date() and works better with UK date format

• value value to parse

parseDatetimeOrNull(value: string | Date): Date | null

parseNumberOrNull

Parses string to the number or returns null. It is more efficient parser than standard (parseFloat) and parses numbers like 1,000.32

• value value to parse

parseNumberOrNull(value: string | Number): Number | null

parseBooleanOrNull

Parses string to the boolean or returns null. It is treating ['1', 'yes', 'true', 'on'] as true and ['0', 'no', 'false', 'off'] as false

• value value to parse

parseBooleanOrNull(value: string | Boolean): Boolean | null

dateToString

Converts Date (or Date with time) to the ISO string with TimeZone trick. Usually it should be used before sending to the server

dateToString(d: Date): string

deepClone

Returns a deep copy of your object or array.

deepClone(obj: any): any