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Merge pull request #21162 from tomwanzek/d3-dsv-jsdoc-strictnullchecks

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[d3-dsv] Validate for strictNullChecks and JSDoc
This commit is contained in:
Ron Buckton
2017-11-03 21:54:52 -07:00
committed by GitHub
parent 827b452f8b 22b6e41ed4
commit 1afa046e68
3 changed files with 408 additions and 72 deletions
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182
types/d3-dsv/d3-dsv-tests.ts
View File

@@ -21,7 +21,7 @@ const tsvTestStringWithHeader = 'Year\tMake\tModel\tLength\n1997\tFord\tE350\t2.
const pipedTestStringWithHeader = 'Year|Make|Model|Length\n1997|Ford|E350|2.34\n2000|Mercury|Cougar|2.38';
interface ParsedTestObject {
year: Date;
year: Date | null;
make: string;
model: string;
length: number;
@@ -35,8 +35,9 @@ let parseRowsMappedArray: ParsedTestObject[];
let columns: string[];
let num: number;
let date: Date;
let dateNull: Date | null;
let str: string;
let strMaybe: string | undefined;
// ------------------------------------------------------------------------------------------
// Test CSV
@@ -50,7 +51,7 @@ parseArray = d3Dsv.csvParse(csvTestStringWithHeader);
columns = parseArray.columns;
str = parseArray[0]['Year'];
strMaybe = parseArray[0]['Year'];
// date = parseArray[0]['Year']; // fails, return value is string
// with row mapper ---------------------------------------------------------------------------
@@ -60,19 +61,39 @@ parseMappedArray = d3Dsv.csvParse(csvTestStringWithHeader, (rawRow, index, colum
const i: number = index;
const c: string[] = columns;
const pr: ParsedTestObject = {
year: new Date(+rr['Year'], 0, 1),
make: rr['Make'],
model: rr['Model'],
length: +rr['Length']
year: rr['Year'] ? new Date(+rr['Year']!, 0, 1) : null,
make: rr['Make'] ? rr['Make']! : "Missing Value",
model: rr['Model'] ? rr['Model']! : "Missing Value",
length: ['Length'] ? +rr['Length']! : NaN
};
return pr;
});
parseMappedArray = d3Dsv.csvParse(csvTestStringWithHeader, (rawRow, index, columns) => {
const rr: d3Dsv.DSVRowString = rawRow;
const i: number = index;
const c: string[] = columns;
const d: number | null = rr['Year'] ? +rr['Year']! : null;
const pr: ParsedTestObject | null | undefined = d !== null
? (
d > 1997
? {
year: new Date(d, 0, 1),
make: rr['Make'] ? rr['Make']! : "Missing Value",
model: rr['Model'] ? rr['Model']! : "Missing Value",
length: ['Length'] ? +rr['Length']! : NaN
}
: undefined
)
: null;
return pr;
});
columns = parseMappedArray.columns;
date = parseMappedArray[0].year;
str = parseMappedArray[0].make;
str = parseMappedArray[0].model;
dateNull = parseMappedArray[0].year;
strMaybe = parseMappedArray[0].make;
strMaybe = parseMappedArray[0].model;
num = parseMappedArray[0].length;
// csvParseRows(...) ============================================================================
@@ -81,7 +102,7 @@ num = parseMappedArray[0].length;
parseRowsArray = d3Dsv.csvParseRows(csvTestString);
str = parseRowsArray[0][0]; // 'Year' of first row
strMaybe = parseRowsArray[0][0]; // 'Year' of first row
// date = parseRowsArray[0][0]; // fails, return value is string
// with row mapper ---------------------------------------------------------------------------
@@ -89,18 +110,25 @@ str = parseRowsArray[0][0]; // 'Year' of first row
parseRowsMappedArray = d3Dsv.csvParseRows(csvTestString, (rawRow, index) => {
const rr: string[] = rawRow;
const i: number = index;
const pr: ParsedTestObject = {
year: new Date(+rr[0], 0, 1),
make: rr[1],
model: rr[2],
length: +rr[3]
};
const d: number | null = rr[0].length ? +rr[0] : null;
const pr: ParsedTestObject | null | undefined = d !== null
? (
d > 1997
? {
year: new Date(d, 0, 1),
make: rr[1].length ? rr[1] : "Missing Value",
model: rr[2].length ? rr[2] : "Missing Value",
length: rr[3].length ? +rr[3] : NaN
}
: undefined
)
: null;
return pr;
});
date = parseRowsMappedArray[0].year;
str = parseRowsMappedArray[0].make;
str = parseRowsMappedArray[0].model;
dateNull = parseRowsMappedArray[0].year;
strMaybe = parseRowsMappedArray[0].make;
strMaybe = parseRowsMappedArray[0].model;
num = parseRowsMappedArray[0].length;
// csvFormat(...) ============================================================================
@@ -111,7 +139,7 @@ str = d3Dsv.csvFormat(parseRowsMappedArray, columns);
// csvFormatRows(...) ========================================================================
str = d3Dsv.csvFormatRows(parseRowsMappedArray.map((d, i) => [
d.year.getFullYear().toString(),
d.year ? d.year.getFullYear().toString() : '',
d.make,
d.model,
d.length.toString()
@@ -129,7 +157,7 @@ parseArray = d3Dsv.tsvParse(tsvTestStringWithHeader);
columns = parseArray.columns;
str = parseArray[0]['Year'];
strMaybe = parseArray[0]['Year'];
// date = parseArray[0]['Year']; // fails, return value is string
// with row mapper ---------------------------------------------------------------------------
@@ -138,20 +166,27 @@ parseMappedArray = d3Dsv.tsvParse(tsvTestStringWithHeader, (rawRow, index, colum
const rr: d3Dsv.DSVRowString = rawRow;
const i: number = index;
const c: string[] = columns;
const pr: ParsedTestObject = {
year: new Date(+rr['Year'], 0, 1),
make: rr['Make'],
model: rr['Model'],
length: +rr['Length']
};
const d: number | null = rr['Year'] ? +rr['Year']! : null;
const pr: ParsedTestObject | null | undefined = d !== null
? (
d > 1997
? {
year: new Date(d, 0, 1),
make: rr['Make'] ? rr['Make']! : "Missing Value",
model: rr['Model'] ? rr['Model']! : "Missing Value",
length: ['Length'] ? +rr['Length']! : NaN
}
: undefined
)
: null;
return pr;
});
columns = parseMappedArray.columns;
date = parseMappedArray[0].year;
str = parseMappedArray[0].make;
str = parseMappedArray[0].model;
dateNull = parseMappedArray[0].year;
strMaybe = parseMappedArray[0].make;
strMaybe = parseMappedArray[0].model;
num = parseMappedArray[0].length;
// tsvParseRows(...) ============================================================================
@@ -160,7 +195,7 @@ num = parseMappedArray[0].length;
parseRowsArray = d3Dsv.tsvParseRows(tsvTestString);
str = parseRowsArray[0][0]; // 'Year' of first row
strMaybe = parseRowsArray[0][0]; // 'Year' of first row
// date = parseRowsArray[0][0]; // fails, return value is string
// with row mapper ---------------------------------------------------------------------------
@@ -168,18 +203,25 @@ str = parseRowsArray[0][0]; // 'Year' of first row
parseRowsMappedArray = d3Dsv.tsvParseRows(tsvTestString, (rawRow, index) => {
const rr: string[] = rawRow;
const i: number = index;
const pr: ParsedTestObject = {
year: new Date(+rr[0], 0, 1),
make: rr[1],
model: rr[2],
length: +rr[3]
};
const d: number | null = rr[0].length ? +rr[0] : null;
const pr: ParsedTestObject | null | undefined = d !== null
? (
d > 1997
? {
year: new Date(d, 0, 1),
make: rr[1].length ? rr[1] : "Missing Value",
model: rr[2].length ? rr[2] : "Missing Value",
length: rr[3].length ? +rr[3] : NaN
}
: undefined
)
: null;
return pr;
});
date = parseRowsMappedArray[0].year;
str = parseRowsMappedArray[0].make;
str = parseRowsMappedArray[0].model;
dateNull = parseRowsMappedArray[0].year;
strMaybe = parseRowsMappedArray[0].make;
strMaybe = parseRowsMappedArray[0].model;
num = parseRowsMappedArray[0].length;
// tsvFormat(...) ============================================================================
@@ -190,7 +232,7 @@ str = d3Dsv.tsvFormat(parseRowsMappedArray, columns);
// tsvFormatRows(...) ========================================================================
str = d3Dsv.tsvFormatRows(parseRowsMappedArray.map((d, i) => [
d.year.getFullYear().toString(),
d.year ? d.year.getFullYear().toString() : '',
d.make,
d.model,
d.length.toString()
@@ -213,7 +255,7 @@ parseArray = dsv.parse(pipedTestStringWithHeader);
columns = parseArray.columns;
str = parseArray[0]['Year'];
strMaybe = parseArray[0]['Year'];
// date = parseArray[0]['Year']; // fails, return value is string
// with row mapper ---------------------------------------------------------------------------
@@ -222,20 +264,27 @@ parseMappedArray = dsv.parse(pipedTestStringWithHeader, (rawRow, index, columns)
const rr: d3Dsv.DSVRowString = rawRow;
const i: number = index;
const c: string[] = columns;
const pr: ParsedTestObject = {
year: new Date(+rr['Year'], 0, 1),
make: rr['Make'],
model: rr['Model'],
length: +rr['Length']
};
const d: number | null = rr['Year'] ? +rr['Year']! : null;
const pr: ParsedTestObject | null | undefined = d !== null
? (
d > 1997
? {
year: new Date(d, 0, 1),
make: rr['Make'] ? rr['Make']! : "Missing Value",
model: rr['Model'] ? rr['Model']! : "Missing Value",
length: ['Length'] ? +rr['Length']! : NaN
}
: undefined
)
: null;
return pr;
});
columns = parseMappedArray.columns;
date = parseMappedArray[0].year;
str = parseMappedArray[0].make;
str = parseMappedArray[0].model;
dateNull = parseMappedArray[0].year;
strMaybe = parseMappedArray[0].make;
strMaybe = parseMappedArray[0].model;
num = parseMappedArray[0].length;
// parseRows(...) ============================================================================
@@ -244,7 +293,7 @@ num = parseMappedArray[0].length;
parseRowsArray = dsv.parseRows(pipedTestString);
str = parseRowsArray[0][0]; // 'Year' of first row
strMaybe = parseRowsArray[0][0]; // 'Year' of first row
// date = parseRowsArray[0][0]; // fails, return value is string
// with row mapper ---------------------------------------------------------------------------
@@ -252,18 +301,25 @@ str = parseRowsArray[0][0]; // 'Year' of first row
parseRowsMappedArray = dsv.parseRows(pipedTestString, (rawRow, index) => {
const rr: string[] = rawRow;
const i: number = index;
const pr: ParsedTestObject = {
year: new Date(+rr[0], 0, 1),
make: rr[1],
model: rr[2],
length: +rr[3]
};
const d: number | null = rr[0].length ? +rr[0] : null;
const pr: ParsedTestObject | null | undefined = d !== null
? (
d > 1997
? {
year: new Date(d, 0, 1),
make: rr[1].length ? rr[1] : "Missing Value",
model: rr[2].length ? rr[2] : "Missing Value",
length: rr[3].length ? +rr[3] : NaN
}
: undefined
)
: null;
return pr;
});
date = parseRowsMappedArray[0].year;
str = parseRowsMappedArray[0].make;
str = parseRowsMappedArray[0].model;
dateNull = parseRowsMappedArray[0].year;
strMaybe = parseRowsMappedArray[0].make;
strMaybe = parseRowsMappedArray[0].model;
num = parseRowsMappedArray[0].length;
// format(...) ============================================================================
@@ -274,7 +330,7 @@ str = dsv.format(parseRowsMappedArray, columns);
// formatRows(...) ========================================================================
str = dsv.formatRows(parseRowsMappedArray.map((d, i) => [
d.year.getFullYear().toString(),
d.year ? d.year.getFullYear().toString() : '',
d.make,
d.model,
d.length.toString()

294
types/d3-dsv/index.d.ts vendored
View File

@@ -3,19 +3,35 @@
// Definitions by: Tom Wanzek <https://github.com/tomwanzek>, Alex Ford <https://github.com/gustavderdrache>, Boris Yankov <https://github.com/borisyankov>
// Definitions: https://github.com/DefinitelyTyped/DefinitelyTyped
// Last module patch version validated against: 1.0.30
// ------------------------------------------------------------------------------------------
// Shared Types and Interfaces
// ------------------------------------------------------------------------------------------
/**
* An object representing a DSV parsed row with values represented as strings.
*/
export interface DSVRowString {
[key: string]: string;
[key: string]: string | undefined;
}
/**
* An object representing a DSV parsed row with values represented as an arbitrary datatype, depending
* on the performed parsed row mapping.
*/
export interface DSVRowAny {
[key: string]: any;
}
/**
* An array object representing all parsed rows. The array is enhanced with a property listing
* the names of the parsed columns.
*/
export interface DSVParsedArray<T> extends Array<T> {
/**
* List of column names.
*/
columns: string[];
}
@@ -25,20 +41,108 @@ export interface DSVParsedArray<T> extends Array<T> {
// csvParse(...) ============================================================================
/**
* Parses the specified string, which must be in the comma-separated values format, returning an array of objects representing the parsed rows.
*
* Unlike csvParseRows, this method requires that the first line of the CSV content contains a comma-separated list of column names;
* these column names become the attributes on the returned objects.
*
* The returned array also exposes a columns property containing the column names in input order (in contrast to Object.keys, whose iteration order is arbitrary).
*
* Equivalent to dsvFormat(",").parse.
*
* @param csvString A string, which must be in the comma-separated values format.
*/
export function csvParse(csvString: string): DSVParsedArray<DSVRowString>;
export function csvParse<ParsedRow extends DSVRowAny>(csvString: string, row: (rawRow: DSVRowString, index: number, columns: string[]) => ParsedRow): DSVParsedArray<ParsedRow>;
/**
* Parses the specified string, which must be in the comma-separated values format, returning an array of objects representing the parsed rows.
*
* Unlike csvParseRows, this method requires that the first line of the CSV content contains a comma-separated list of column names;
* these column names become the attributes on the returned objects.
*
* The returned array also exposes a columns property containing the column names in input order (in contrast to Object.keys, whose iteration order is arbitrary).
*
* Equivalent to dsvFormat(",").parse.
*
* @param csvString A string, which must be in the comma-separated values format.
* @param row A row conversion function which is invoked for each row, being passed an object representing the current row (d),
* the index (i) starting at zero for the first non-header row, and the array of column names. If the returned value is null or undefined,
* the row is skipped and will be ommitted from the array returned by dsv.parse; otherwise, the returned value defines the corresponding row object.
* In effect, row is similar to applying a map and filter operator to the returned rows.
*/
export function csvParse<ParsedRow extends DSVRowAny>(
csvString: string,
row: (rawRow: DSVRowString, index: number, columns: string[]) => ParsedRow | undefined | null
): DSVParsedArray<ParsedRow>;
// csvParseRows(...) ========================================================================
/**
* Parses the specified string, which must be in the comma-separated values format, returning an array of arrays representing the parsed rows.
*
* Unlike csvParse, this method treats the header line as a standard row, and should be used whenever CSV content does not contain a header.
* Each row is represented as an array rather than an object. Rows may have variable length.
*
* If a row conversion function is not specified, field values are strings. For safety, there is no automatic conversion to numbers, dates, or other types.
* In some cases, JavaScript may coerce strings to numbers for you automatically (for example, using the + operator), but better is to specify a row conversion function.
*
* Equivalent to dsvFormat(",").parseRows.
*
* @param csvString A string, which must be in the comma-separated values format.
*/
export function csvParseRows(csvString: string): string[][];
export function csvParseRows<ParsedRow extends DSVRowAny>(csvString: string, row: (rawRow: string[], index: number) => ParsedRow): ParsedRow[];
/**
* Parses the specified string, which must be in the comma-separated values format, returning an array of arrays representing the parsed rows.
*
* Unlike csvParse, this method treats the header line as a standard row, and should be used whenever CSV content does not contain a header.
* Each row is represented as an array rather than an object. Rows may have variable length.
*
* Equivalent to dsvFormat(",").parseRows.
*
* @param csvString A string, which must be in the comma-separated values format.
* @param row A row conversion function which is invoked for each row, being passed an array representing the current row (d), the index (i)
* starting at zero for the first row, and the array of column names. If the returned value is null or undefined,
* the row is skipped and will be ommitted from the array returned by dsv.parse; otherwise, the returned value defines the corresponding row object.
* In effect, row is similar to applying a map and filter operator to the returned rows.
*/
export function csvParseRows<ParsedRow extends DSVRowAny>(
csvString: string,
row: (rawRow: string[], index: number) => ParsedRow | undefined | null
): ParsedRow[];
// csvFormat(...) ============================================================================
/**
* Formats the specified array of object rows as comma-separated values, returning a string.
* This operation is the inverse of csvParse. Each row will be separated by a newline (\n),
* and each column within each row will be separated by the comma-delimiter.
* Values that contain either the comma-delimiter, a double-quote (") or a newline will be escaped using double-quotes.
*
* If columns is not specified, the list of column names that forms the header row is determined by the union of all properties on all objects in rows;
* the order of columns is nondeterministic.
*
* Equivalent to dsvFormat(",").format.
*
* @param rows Array of object rows.
* @param columns An array of strings representing the column names.
*/
export function csvFormat(rows: DSVRowAny[], columns?: string[]): string;
// csvFormatRows(...) ========================================================================
/**
* Formats the specified array of array of string rows as comma-separated values, returning a string.
* This operation is the reverse of csvParseRows. Each row will be separated by a newline (\n),
* and each column within each row will be separated by the comma-delimiter.
* Values that contain either the comma-delimiter, a double-quote (") or a newline will be escaped using double-quotes.
*
* To convert an array of objects to an array of arrays while explicitly specifying the columns, use array.map.
* If you like, you can also array.concat this result with an array of column names to generate the first row.
*
* Equivalent to dsvFormat(",").formatRows.
*
* @param rows An array of array of string rows.
*/
export function csvFormatRows(rows: string[][]): string;
// ------------------------------------------------------------------------------------------
@@ -47,33 +151,209 @@ export function csvFormatRows(rows: string[][]): string;
// tsvParse(...) ============================================================================
/**
* Parses the specified string, which must be in the tab-separated values format, returning an array of objects representing the parsed rows.
*
* Unlike tsvParseRows, this method requires that the first line of the TSV content contains a tab-separated list of column names;
* these column names become the attributes on the returned objects.
*
* The returned array also exposes a columns property containing the column names in input order (in contrast to Object.keys, whose iteration order is arbitrary).
*
* Equivalent to dsvFormat("\t").parse.
*
* @param tsvString A string, which must be in the tab-separated values format.
*/
export function tsvParse(tsvString: string): DSVParsedArray<DSVRowString>;
export function tsvParse<MappedRow extends DSVRowAny>(tsvString: string, row: (rawRow: DSVRowString, index: number, columns: string[]) => MappedRow): DSVParsedArray<MappedRow>;
/**
* Parses the specified string, which must be in the tab-separated values format, returning an array of objects representing the parsed rows.
*
* Unlike tsvParseRows, this method requires that the first line of the TSV content contains a tab-separated list of column names;
* these column names become the attributes on the returned objects.
*
* The returned array also exposes a columns property containing the column names in input order (in contrast to Object.keys, whose iteration order is arbitrary).
*
* Equivalent to dsvFormat("\t").parse.
*
* @param tsvString A string, which must be in the tab-separated values format.
* @param row A row conversion function which is invoked for each row, being passed an object representing the current row (d),
* the index (i) starting at zero for the first non-header row, and the array of column names. If the returned value is null or undefined,
* the row is skipped and will be ommitted from the array returned by dsv.parse; otherwise, the returned value defines the corresponding row object.
* In effect, row is similar to applying a map and filter operator to the returned rows.
*/
export function tsvParse<MappedRow extends DSVRowAny>(
tsvString: string,
row: (rawRow: DSVRowString, index: number, columns: string[]) => MappedRow | undefined | null
): DSVParsedArray<MappedRow>;
// tsvParseRows(...) ========================================================================
/**
* Parses the specified string, which must be in the tab-separated values format, returning an array of arrays representing the parsed rows.
*
* Unlike tsvParse, this method treats the header line as a standard row, and should be used whenever TSV content does not contain a header.
* Each row is represented as an array rather than an object. Rows may have variable length.
*
* If a row conversion function is not specified, field values are strings. For safety, there is no automatic conversion to numbers, dates, or other types.
* In some cases, JavaScript may coerce strings to numbers for you automatically (for example, using the + operator), but better is to specify a row conversion function.
*
* Equivalent to dsvFormat("\t").parseRows.
*
* @param tsvString A string, which must be in the tab-separated values format.
*/
export function tsvParseRows(tsvString: string): string[][];
export function tsvParseRows<MappedRow extends DSVRowAny>(tsvString: string, row: (rawRow: string[], index: number) => MappedRow): MappedRow[];
/**
* Parses the specified string, which must be in the tab-separated values format, returning an array of arrays representing the parsed rows.
*
* Unlike tsvParse, this method treats the header line as a standard row, and should be used whenever TSV content does not contain a header.
* Each row is represented as an array rather than an object. Rows may have variable length.
*
* Equivalent to dsvFormat("\t").parseRows.
*
* @param tsvString A string, which must be in the tab-separated values format.
* @param row A row conversion function which is invoked for each row, being passed an array representing the current row (d), the index (i)
* starting at zero for the first row, and the array of column names. If the returned value is null or undefined,
* the row is skipped and will be ommitted from the array returned by dsv.parse; otherwise, the returned value defines the corresponding row object.
* In effect, row is similar to applying a map and filter operator to the returned rows.
*/
export function tsvParseRows<MappedRow extends DSVRowAny>(
tsvString: string,
row: (rawRow: string[], index: number) => MappedRow | undefined | null
): MappedRow[];
// tsvFormat(...) ============================================================================
/**
* Formats the specified array of object rows as tab-separated values, returning a string.
* This operation is the inverse of tsvParse. Each row will be separated by a newline (\n),
* and each column within each row will be separated by the tab-delimiter.
* Values that contain either the tab-delimiter, a double-quote (") or a newline will be escaped using double-quotes.
*
* If columns is not specified, the list of column names that forms the header row is determined by the union of all properties on all objects in rows;
* the order of columns is nondeterministic.
*
* Equivalent to dsvFormat("\t").format.
*
* @param rows Array of object rows.
* @param columns An array of strings representing the column names.
*/
export function tsvFormat(rows: DSVRowAny[], columns?: string[]): string;
// tsvFormatRows(...) ========================================================================
/**
* Formats the specified array of array of string rows as tab-separated values, returning a string.
* This operation is the reverse of tsvParseRows. Each row will be separated by a newline (\n),
* and each column within each row will be separated by the tab-delimiter.
* Values that contain either the tab-delimiter, a double-quote (") or a newline will be escaped using double-quotes.
*
* To convert an array of objects to an array of arrays while explicitly specifying the columns, use array.map.
* If you like, you can also array.concat this result with an array of column names to generate the first row.
*
* Equivalent to dsvFormat("\t").formatRows.
*
* @param rows An array of array of string rows.
*/
export function tsvFormatRows(rows: string[][]): string;
// ------------------------------------------------------------------------------------------
// DSV Generalized Parsers and Formatters
// ------------------------------------------------------------------------------------------
/**
* A DSV parser and formatter
*/
export interface DSV {
/**
* Parses the specified string, which must be in the delimiter-separated values format with the appropriate delimiter, returning an array of objects representing the parsed rows.
*
* Unlike dsv.parseRows, this method requires that the first line of the DSV content contains a delimiter-separated list of column names;
* these column names become the attributes on the returned objects.
*
* The returned array also exposes a columns property containing the column names in input order (in contrast to Object.keys, whose iteration order is arbitrary).
*
* @param dsvString A string, which must be in the delimiter-separated values format with the appropriate delimiter.
*/
parse(dsvString: string): DSVParsedArray<DSVRowString>;
parse<ParsedRow extends DSVRowAny>(dsvString: string, row: (rawRow: DSVRowString, index: number, columns: string[]) => ParsedRow): DSVParsedArray<ParsedRow>;
/**
* Parses the specified string, which must be in the delimiter-separated values format with the appropriate delimiter, returning an array of objects representing the parsed rows.
*
* Unlike dsv.parseRows, this method requires that the first line of the DSV content contains a delimiter-separated list of column names;
* these column names become the attributes on the returned objects.
*
* The returned array also exposes a columns property containing the column names in input order (in contrast to Object.keys, whose iteration order is arbitrary).
*
* @param dsvString A string, which must be in the delimiter-separated values format with the appropriate delimiter.
* @param row A row conversion function which is invoked for each row, being passed an object representing the current row (d),
* the index (i) starting at zero for the first non-header row, and the array of column names. If the returned value is null or undefined,
* the row is skipped and will be ommitted from the array returned by dsv.parse; otherwise, the returned value defines the corresponding row object.
* In effect, row is similar to applying a map and filter operator to the returned rows.
*/
parse<ParsedRow extends DSVRowAny>(
dsvString: string,
row: (rawRow: DSVRowString, index: number, columns: string[]) => ParsedRow | undefined | null
): DSVParsedArray<ParsedRow>;
/**
* Parses the specified string, which must be in the delimiter-separated values format with the appropriate delimiter, returning an array of arrays representing the parsed rows.
*
* Unlike dsv.parse, this method treats the header line as a standard row, and should be used whenever DSV content does not contain a header.
* Each row is represented as an array rather than an object. Rows may have variable length.
*
* If a row conversion function is not specified, field values are strings. For safety, there is no automatic conversion to numbers, dates, or other types.
* In some cases, JavaScript may coerce strings to numbers for you automatically (for example, using the + operator), but better is to specify a row conversion function.
*
* @param dsvString A string, which must be in the delimiter-separated values format with the appropriate delimiter.
*/
parseRows(dsvString: string): string[][];
parseRows<ParsedRow extends DSVRowAny>(dsvString: string, row: (rawRow: string[], index: number) => ParsedRow): ParsedRow[];
/**
* Parses the specified string, which must be in the delimiter-separated values format with the appropriate delimiter, returning an array of arrays representing the parsed rows.
*
* Unlike dsv.parse, this method treats the header line as a standard row, and should be used whenever DSV content does not contain a header.
* Each row is represented as an array rather than an object. Rows may have variable length.
*
* @param dsvString A string, which must be in the delimiter-separated values format with the appropriate delimiter.
* @param row A row conversion function which is invoked for each row, being passed an array representing the current row (d), the index (i)
* starting at zero for the first row, and the array of column names. If the returned value is null or undefined,
* the row is skipped and will be ommitted from the array returned by dsv.parse; otherwise, the returned value defines the corresponding row object.
* In effect, row is similar to applying a map and filter operator to the returned rows.
*/
parseRows<ParsedRow extends DSVRowAny>(
dsvString: string,
row: (rawRow: string[], index: number) => ParsedRow | undefined | null
): ParsedRow[];
/**
* Formats the specified array of object rows as delimiter-separated values, returning a string.
* This operation is the inverse of dsv.parse. Each row will be separated by a newline (\n),
* and each column within each row will be separated by the delimiter (such as a comma, ,).
* Values that contain either the delimiter, a double-quote (") or a newline will be escaped using double-quotes.
*
* If columns is not specified, the list of column names that forms the header row is determined by the union of all properties on all objects in rows;
* the order of columns is nondeterministic.
*
* @param rows Array of object rows.
* @param columns An array of strings representing the column names.
*/
format(rows: DSVRowAny[], columns?: string[]): string;
/**
* Formats the specified array of array of string rows as delimiter-separated values, returning a string.
* This operation is the reverse of dsv.parseRows. Each row will be separated by a newline (\n),
* and each column within each row will be separated by the delimiter (such as a comma, ,).
* Values that contain either the delimiter, a double-quote (") or a newline will be escaped using double-quotes.
*
* To convert an array of objects to an array of arrays while explicitly specifying the columns, use array.map.
* If you like, you can also array.concat this result with an array of column names to generate the first row.
*
* @param rows An array of array of string rows.
*/
formatRows(rows: string[][]): string;
}
/**
* Constructs a new DSV parser and formatter for the specified delimiter.
*
* @param delimiter A delimiter character. The delimiter must be a single character (i.e., a single 16-bit code unit);
* so, ASCII delimiters are fine, but emoji delimiters are not.
*/
export function dsvFormat(delimiter: string): DSV;

4
types/d3-dsv/tsconfig.json
View File

@@ -6,7 +6,7 @@
],
"noImplicitAny": true,
"noImplicitThis": true,
"strictNullChecks": false,
"strictNullChecks": true,
"strictFunctionTypes": true,
"baseUrl": "../",
"typeRoots": [
@@ -20,4 +20,4 @@
"index.d.ts",
"d3-dsv-tests.ts"
]
}
}