21722643399

Committed 05 Feb 2026 05:58PM UTC coverage: 61.648% (+0.02%) from 61.633%

Build # 21722643399

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Pull #3298

github

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web-flow

Commit Message

Merge cf4c058bd into 4bdf8f4ff

Pull Request Pull Request #3298: Implement WKT validation in data-type.ts

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74.12

/src/common-utils/src/data-type.ts

// SPDX-License-Identifier: MIT
// Copyright contributors to the kepler.gl project

import {Analyzer, DATA_TYPES as AnalyzerDATA_TYPES} from 'type-analyzer';
import {ArrowTableInterface, ApacheVectorInterface, RowData, Field} from '@kepler.gl/types';
import {ALL_FIELD_TYPES} from '@kepler.gl/constants';
import {console as globalConsole} from 'global/window';
import {range} from 'd3-array';
import {isHexWkb, notNullorUndefined} from './data';
import {h3IsValid} from './h3-utils';

const H3_ANALYZER_TYPE = 'H3';

// Returns true if the value is likely a WKT geometry string (heuristic check).
const WKT_PREFIX_RE =
  /^(?:SRID=\d+\s*;\s*)?(?:POINT|LINESTRING|POLYGON|MULTIPOINT|MULTILINESTRING|MULTIPOLYGON|GEOMETRYCOLLECTION)(?:\s+(?:Z|M|ZM))?\s*\(/i;

function isWkt(value: unknown): boolean {
  if (typeof value !== 'string') {
    return false;
  }

  const s = value.trim();
  if (s.length < 10) {
    return false;
  }

  // Quick structural checks to avoid regex work for typical strings.
  if (!s.includes('(') || !s.includes(')')) {
    return false;
  }

  return WKT_PREFIX_RE.test(s);
}

export const ACCEPTED_ANALYZER_TYPES = [
  AnalyzerDATA_TYPES.DATE,
  AnalyzerDATA_TYPES.TIME,
  AnalyzerDATA_TYPES.DATETIME,
  AnalyzerDATA_TYPES.NUMBER,
  AnalyzerDATA_TYPES.INT,
  AnalyzerDATA_TYPES.FLOAT,
  AnalyzerDATA_TYPES.BOOLEAN,
  AnalyzerDATA_TYPES.STRING,
  AnalyzerDATA_TYPES.GEOMETRY,
  AnalyzerDATA_TYPES.GEOMETRY_FROM_STRING,
  AnalyzerDATA_TYPES.PAIR_GEOMETRY_FROM_STRING,
  AnalyzerDATA_TYPES.ZIPCODE,
  AnalyzerDATA_TYPES.ARRAY,
  AnalyzerDATA_TYPES.OBJECT,
  H3_ANALYZER_TYPE
];

const IGNORE_DATA_TYPES = Object.keys(AnalyzerDATA_TYPES).filter(
  type => !ACCEPTED_ANALYZER_TYPES.includes(type)
);

/**
 * Getting sample data for analyzing field type.
 */
export function getSampleForTypeAnalyze({
  fields,
  rows,
  sampleCount = 50
}: {
  fields: string[];
  rows: unknown[][] | RowData;
  sampleCount?: number;
}): RowData {
  const total = Math.min(sampleCount, rows.length);
  // const fieldOrder = fields.map(f => f.name);
  const sample = range(0, total, 1).map(() => ({}));

  if (rows.length < 1) {
    return [];
  }
  const isRowObject = !Array.isArray(rows[0]);

  // collect sample data for each field
  fields.forEach((field, fieldIdx) => {
    // row counter
    let i = 0;
    // sample counter
    let j = 0;

    while (j < total) {
      if (i >= rows.length) {
        // if depleted data pool
        sample[j][field] = null;
        j++;
      } else if (notNullorUndefined(rows[i][isRowObject ? field : fieldIdx])) {
        const value = rows[i][isRowObject ? field : fieldIdx];
        sample[j][field] = typeof value === 'string' ? value.trim() : value;
        j++;
        i++;
      } else {
        i++;
      }
    }
  });

  return sample;
}

/**
 * Getting sample data for analyzing field type for Arrow tables.
 * @param table Arrow table or an array of vectors.
 * @param fields Field names.
 * @param sampleCount Number of sample rows to get.
 * @returns Sample rows.
 */
export function getSampleForTypeAnalyzeArrow(
  table: ArrowTableInterface | ApacheVectorInterface[],
  fields: string[],
  sampleCount = 50
): any[] {
  const isTable = !Array.isArray(table);

  const numRows = isTable ? table.numRows : table[0].length;
  const getVector = isTable ? index => table.getChildAt(index) : index => table[index];

  const total = Math.min(sampleCount, numRows);
  const sample = range(0, total, 1).map(() => ({}));

  if (numRows < 1) {
    return [];
  }

  // collect sample data for each field
  fields.forEach((field, fieldIdx) => {
    let rowIndex = 0;
    let sampleIndex = 0;

    while (sampleIndex < total) {
      if (rowIndex >= numRows) {
        // if depleted data pool
        sample[sampleIndex][field] = null;
        sampleIndex++;
      } else if (notNullorUndefined(getVector(fieldIdx)?.get(rowIndex))) {
        const value = getVector(fieldIdx)?.get(rowIndex);
        sample[sampleIndex][field] = typeof value === 'string' ? value.trim() : value;
        sampleIndex++;
        rowIndex++;
      } else {
        rowIndex++;
      }
    }
  });

  return sample;
}

/**
 * Convert type-analyzer output to kepler.gl field types
 *
 * @param aType
 * @returns corresponding type in `ALL_FIELD_TYPES`
 */
/* eslint-disable complexity */
export function analyzerTypeToFieldType(aType: string): string {
  const {
    DATE,
    TIME,
    DATETIME,
    NUMBER,
    INT,
    FLOAT,
    BOOLEAN,
    STRING,
    GEOMETRY,
    GEOMETRY_FROM_STRING,
    PAIR_GEOMETRY_FROM_STRING,
    ZIPCODE,
    ARRAY,
    OBJECT
  } = AnalyzerDATA_TYPES;

  // TODO: un recognized types
  // CURRENCY PERCENT NONE
  switch (aType) {
    case DATE:
      return ALL_FIELD_TYPES.date;
    case TIME:
    case DATETIME:
      return ALL_FIELD_TYPES.timestamp;
    case FLOAT:
      return ALL_FIELD_TYPES.real;
    case INT:
      return ALL_FIELD_TYPES.integer;
    case BOOLEAN:
      return ALL_FIELD_TYPES.boolean;
    case GEOMETRY:
    case GEOMETRY_FROM_STRING:
    case PAIR_GEOMETRY_FROM_STRING:
      return ALL_FIELD_TYPES.geojson;
    case ARRAY:
      return ALL_FIELD_TYPES.array;
    case OBJECT:
      return ALL_FIELD_TYPES.object;
    case NUMBER:
    case STRING:
    case ZIPCODE:
      return ALL_FIELD_TYPES.string;
    case H3_ANALYZER_TYPE:
      return ALL_FIELD_TYPES.h3;
    default:
      globalConsole.warn(`Unsupported analyzer type: ${aType}`);
      return ALL_FIELD_TYPES.string;
  }
}

/**
 * Analyze field types from data in `string` format, e.g. uploaded csv.
 * Assign `type`, `fieldIdx` and `format` (timestamp only) to each field
 *
 * @param data array of row object
 * @param fieldOrder array of field names as string
 * @returns formatted fields
 * @public
 * @example
 *
 * import {getFieldsFromData} from '@kepler.gl/common-utils';
 * const data = [{
 *   time: '2016-09-17 00:09:55',
 *   value: '4',
 *   surge: '1.2',
 *   isTrip: 'true',
 *   zeroOnes: '0'
 * }, {
 *   time: '2016-09-17 00:30:08',
 *   value: '3',
 *   surge: null,
 *   isTrip: 'false',
 *   zeroOnes: '1'
 * }, {
 *   time: null,
 *   value: '2',
 *   surge: '1.3',
 *   isTrip: null,
 *   zeroOnes: '1'
 * }];
 *
 * const fieldOrder = ['time', 'value', 'surge', 'isTrip', 'zeroOnes'];
 * const fields = getFieldsFromData(data, fieldOrder);
 * // fields = [
 * // {name: 'time', format: 'YYYY-M-D H:m:s', fieldIdx: 1, type: 'timestamp'},
 * // {name: 'value', format: '', fieldIdx: 4, type: 'integer'},
 * // {name: 'surge', format: '', fieldIdx: 5, type: 'real'},
 * // {name: 'isTrip', format: '', fieldIdx: 6, type: 'boolean'},
 * // {name: 'zeroOnes', format: '', fieldIdx: 7, type: 'integer'}];
 *
 */
export function getFieldsFromData(data: RowData, fieldOrder: string[]): Field[] {
  // add a check for epoch timestamp
  const metadata = Analyzer.computeColMeta(
    data,
    [
      {regex: /.*geojson|all_points/g, dataType: 'GEOMETRY'},
      {regex: /.*census/g, dataType: 'STRING'}
    ],
    {ignoredDataTypes: IGNORE_DATA_TYPES}
  );

  const {fieldByIndex} = renameDuplicateFields(fieldOrder);

  const result = fieldOrder.map((field, index) => {
    const name = fieldByIndex[index];

    const fieldMeta = metadata.find(m => m.key === field);

    // fieldMeta could be undefined if the field has no data and Analyzer.computeColMeta
    // will ignore the field. In this case, we will simply assign the field type to STRING
    // since dropping the column in the RowData could be expensive
    let type = fieldMeta?.type || 'STRING';
    const format = fieldMeta?.format || '';

    // quick check if first valid string in column is H3
    if (type === AnalyzerDATA_TYPES.STRING) {
      for (let i = 0, n = data.length; i < n; ++i) {
        if (notNullorUndefined(data[i][name])) {
          type = h3IsValid(data[i][name] || '') ? H3_ANALYZER_TYPE : type;
          break;
        }
      }
    }

    // quick check if string is hex wkb
    if (type === AnalyzerDATA_TYPES.STRING) {
      type = data.some(d => isHexWkb(d[name])) ? AnalyzerDATA_TYPES.GEOMETRY : type;
    }

    // quick check if string is wkt
    if (type === AnalyzerDATA_TYPES.STRING) {
      type = data.some(d => isWkt(d[name])) ? AnalyzerDATA_TYPES.GEOMETRY_FROM_STRING : type;
    }

    return {
      name,
      id: name,
      displayName: name,
      format,
      fieldIdx: index,
      type: analyzerTypeToFieldType(type),
      analyzerType: type,
      valueAccessor: dc => d => {
        return dc.valueAt(d.index, index);
      }
    };
  });

  return result;
}

/**
 * pass in an array of field names, rename duplicated one
 * and return a map from old field index to new name
 *
 * @param fieldOrder
 * @returns new field name by index
 */
export function renameDuplicateFields(fieldOrder: string[]): {
  allNames: string[];
  fieldByIndex: string[];
} {
  return fieldOrder.reduce<{allNames: string[]; fieldByIndex: string[]}>(
    (accu, field, i) => {
      const {allNames} = accu;
      let fieldName = field;

      // add a counter to duplicated names
      if (allNames.includes(field)) {
        let counter = 0;
        while (allNames.includes(`${field}-${counter}`)) {
          counter++;
        }
        fieldName = `${field}-${counter}`;
      }

      accu.fieldByIndex[i] = fieldName;
      accu.allNames.push(fieldName);

      return accu;
    },
    {allNames: [], fieldByIndex: []}
  );
}

1	// SPDX-License-Identifier: MIT
2	// Copyright contributors to the kepler.gl project
3
4	import {Analyzer, DATA_TYPES as AnalyzerDATA_TYPES} from 'type-analyzer';
5	import {ArrowTableInterface, ApacheVectorInterface, RowData, Field} from '@kepler.gl/types';
6	import {ALL_FIELD_TYPES} from '@kepler.gl/constants';
7	import {console as globalConsole} from 'global/window';
8	import {range} from 'd3-array';
9	import {isHexWkb, notNullorUndefined} from './data';
10	import {h3IsValid} from './h3-utils';
11
12	const H3_ANALYZER_TYPE = 'H3';	15✔
13
14	// Returns true if the value is likely a WKT geometry string (heuristic check).
15	const WKT_PREFIX_RE =
16	/^(?:SRID=\d+\s;\s)?(?:POINT\|LINESTRING\|POLYGON\|MULTIPOINT\|MULTILINESTRING\|MULTIPOLYGON\|GEOMETRYCOLLECTION)(?:\s+(?:Z\|M\|ZM))?\s*\(/i;	15✔
17
18	function isWkt(value: unknown): boolean {
19	if (typeof value !== 'string') {	1,471✔
20	return false;	60✔
21	}
22
23	const s = value.trim();	1,411✔
24	if (s.length < 10) {	1,411✔
25	return false;	475✔
26	}
27
28	// Quick structural checks to avoid regex work for typical strings.
29	if (!s.includes('(') \|\| !s.includes(')')) {	936!
30	return false;	936✔
31	}
32
NEW 33	return WKT_PREFIX_RE.test(s);	×
34	}
35
36	export const ACCEPTED_ANALYZER_TYPES = [	15✔
37	AnalyzerDATA_TYPES.DATE,
38	AnalyzerDATA_TYPES.TIME,
39	AnalyzerDATA_TYPES.DATETIME,
40	AnalyzerDATA_TYPES.NUMBER,
41	AnalyzerDATA_TYPES.INT,
42	AnalyzerDATA_TYPES.FLOAT,
43	AnalyzerDATA_TYPES.BOOLEAN,
44	AnalyzerDATA_TYPES.STRING,
45	AnalyzerDATA_TYPES.GEOMETRY,
46	AnalyzerDATA_TYPES.GEOMETRY_FROM_STRING,
47	AnalyzerDATA_TYPES.PAIR_GEOMETRY_FROM_STRING,
48	AnalyzerDATA_TYPES.ZIPCODE,
49	AnalyzerDATA_TYPES.ARRAY,
50	AnalyzerDATA_TYPES.OBJECT,
51	H3_ANALYZER_TYPE
52	];
53
54	const IGNORE_DATA_TYPES = Object.keys(AnalyzerDATA_TYPES).filter(	15✔
55	type => !ACCEPTED_ANALYZER_TYPES.includes(type)	270✔
56	);
57
58	/**
59	* Getting sample data for analyzing field type.
60	*/
61	export function getSampleForTypeAnalyze({
62	fields,
63	rows,
64	sampleCount = 50	118✔
65	}: {
66	fields: string[];
67	rows: unknown[][] \| RowData;
68	sampleCount?: number;
69	}): RowData {
70	const total = Math.min(sampleCount, rows.length);	119✔
71	// const fieldOrder = fields.map(f => f.name);
72	const sample = range(0, total, 1).map(() => ({}));	1,362✔
73
74	if (rows.length < 1) {	119!
UNCOV 75	return [];	×
76	}
77	const isRowObject = !Array.isArray(rows[0]);	119✔
78
79	// collect sample data for each field
80	fields.forEach((field, fieldIdx) => {	119✔
81	// row counter
82	let i = 0;	947✔
83	// sample counter
84	let j = 0;	947✔
85
86	while (j < total) {	947✔
87	if (i >= rows.length) {	15,078✔
88	// if depleted data pool
89	sample[j][field] = null;	1,000✔
90	j++;	1,000✔
91	} else if (notNullorUndefined(rows[i][isRowObject ? field : fieldIdx])) {	14,078!
92	const value = rows[i][isRowObject ? field : fieldIdx];	13,073!
93	sample[j][field] = typeof value === 'string' ? value.trim() : value;	13,073✔
94	j++;	13,073✔
95	i++;	13,073✔
96	} else {
97	i++;	1,005✔
98	}
99	}
100	});
101
102	return sample;	119✔
103	}
104
105	/**
106	* Getting sample data for analyzing field type for Arrow tables.
107	* @param table Arrow table or an array of vectors.
108	* @param fields Field names.
109	* @param sampleCount Number of sample rows to get.
110	* @returns Sample rows.
111	*/
112	export function getSampleForTypeAnalyzeArrow(
113	table: ArrowTableInterface \| ApacheVectorInterface[],
114	fields: string[],
115	sampleCount = 50	×
116	): any[] {
UNCOV 117	const isTable = !Array.isArray(table);	×
118
119	const numRows = isTable ? table.numRows : table[0].length;	×
UNCOV 120	const getVector = isTable ? index => table.getChildAt(index) : index => table[index];	×
121
122	const total = Math.min(sampleCount, numRows);	×
UNCOV 123	const sample = range(0, total, 1).map(() => ({}));	×
124
125	if (numRows < 1) {	×
UNCOV 126	return [];	×
127	}
128
129	// collect sample data for each field
130	fields.forEach((field, fieldIdx) => {	×
131	let rowIndex = 0;	×
UNCOV 132	let sampleIndex = 0;	×
133
134	while (sampleIndex < total) {	×
UNCOV 135	if (rowIndex >= numRows) {	×
136	// if depleted data pool
137	sample[sampleIndex][field] = null;	×
138	sampleIndex++;	×
139	} else if (notNullorUndefined(getVector(fieldIdx)?.get(rowIndex))) {	×
140	const value = getVector(fieldIdx)?.get(rowIndex);	×
141	sample[sampleIndex][field] = typeof value === 'string' ? value.trim() : value;	×
142	sampleIndex++;	×
UNCOV 143	rowIndex++;	×
144	} else {
UNCOV 145	rowIndex++;	×
146	}
147	}
148	});
149
UNCOV 150	return sample;	×
151	}
152
153	/**
154	* Convert type-analyzer output to kepler.gl field types
155	*
156	* @param aType
157	* @returns corresponding type in `ALL_FIELD_TYPES`
158	*/
159	/* eslint-disable complexity */
160	export function analyzerTypeToFieldType(aType: string): string {
161	const {
162	DATE,
163	TIME,
164	DATETIME,
165	NUMBER,
166	INT,
167	FLOAT,
168	BOOLEAN,
169	STRING,
170	GEOMETRY,
171	GEOMETRY_FROM_STRING,
172	PAIR_GEOMETRY_FROM_STRING,
173	ZIPCODE,
174	ARRAY,
175	OBJECT
176	} = AnalyzerDATA_TYPES;	973✔
177
178	// TODO: un recognized types
179	// CURRENCY PERCENT NONE
180	switch (aType) {	973✔
181	case DATE:
182	return ALL_FIELD_TYPES.date;	19✔
183	case TIME:
184	case DATETIME:
185	return ALL_FIELD_TYPES.timestamp;	133✔
186	case FLOAT:
187	return ALL_FIELD_TYPES.real;	332✔
188	case INT:
189	return ALL_FIELD_TYPES.integer;	193✔
190	case BOOLEAN:
191	return ALL_FIELD_TYPES.boolean;	48✔
192	case GEOMETRY:
193	case GEOMETRY_FROM_STRING:
194	case PAIR_GEOMETRY_FROM_STRING:
195	return ALL_FIELD_TYPES.geojson;	70✔
196	case ARRAY:
197	return ALL_FIELD_TYPES.array;	21✔
198	case OBJECT:
199	return ALL_FIELD_TYPES.object;	10✔
200	case NUMBER:
201	case STRING:
202	case ZIPCODE:
203	return ALL_FIELD_TYPES.string;	127✔
204	case H3_ANALYZER_TYPE:
205	return ALL_FIELD_TYPES.h3;	16✔
206	default:
207	globalConsole.warn(`Unsupported analyzer type: ${aType}`);	4✔
208	return ALL_FIELD_TYPES.string;	4✔
209	}
210	}
211
212	/**
213	* Analyze field types from data in `string` format, e.g. uploaded csv.
214	* Assign `type`, `fieldIdx` and `format` (timestamp only) to each field
215	*
216	* @param data array of row object
217	* @param fieldOrder array of field names as string
218	* @returns formatted fields
219	* @public
220	* @example
221	*
222	* import {getFieldsFromData} from '@kepler.gl/common-utils';
223	* const data = [{
224	* time: '2016-09-17 00:09:55',
225	* value: '4',
226	* surge: '1.2',
227	* isTrip: 'true',
228	* zeroOnes: '0'
229	* }, {
230	* time: '2016-09-17 00:30:08',
231	* value: '3',
232	* surge: null,
233	* isTrip: 'false',
234	* zeroOnes: '1'
235	* }, {
236	* time: null,
237	* value: '2',
238	* surge: '1.3',
239	* isTrip: null,
240	* zeroOnes: '1'
241	* }];
242	*
243	* const fieldOrder = ['time', 'value', 'surge', 'isTrip', 'zeroOnes'];
244	* const fields = getFieldsFromData(data, fieldOrder);
245	* // fields = [
246	* // {name: 'time', format: 'YYYY-M-D H:m:s', fieldIdx: 1, type: 'timestamp'},
247	* // {name: 'value', format: '', fieldIdx: 4, type: 'integer'},
248	* // {name: 'surge', format: '', fieldIdx: 5, type: 'real'},
249	* // {name: 'isTrip', format: '', fieldIdx: 6, type: 'boolean'},
250	* // {name: 'zeroOnes', format: '', fieldIdx: 7, type: 'integer'}];
251	*
252	*/
253	export function getFieldsFromData(data: RowData, fieldOrder: string[]): Field[] {
254	// add a check for epoch timestamp
255	const metadata = Analyzer.computeColMeta(	119✔
256	data,
257	[
258	{regex: /.*geojson\|all_points/g, dataType: 'GEOMETRY'},
259	{regex: /.*census/g, dataType: 'STRING'}
260	],
261	{ignoredDataTypes: IGNORE_DATA_TYPES}
262	);
263
264	const {fieldByIndex} = renameDuplicateFields(fieldOrder);	119✔
265
266	const result = fieldOrder.map((field, index) => {	119✔
267	const name = fieldByIndex[index];	955✔
268
269	const fieldMeta = metadata.find(m => m.key === field);	5,416✔
270
271	// fieldMeta could be undefined if the field has no data and Analyzer.computeColMeta
272	// will ignore the field. In this case, we will simply assign the field type to STRING
273	// since dropping the column in the RowData could be expensive
274	let type = fieldMeta?.type \|\| 'STRING';	955✔
275	const format = fieldMeta?.format \|\| '';	955✔
276
277	// quick check if first valid string in column is H3
278	if (type === AnalyzerDATA_TYPES.STRING) {	955✔
279	for (let i = 0, n = data.length; i < n; ++i) {	141✔
280	if (notNullorUndefined(data[i][name])) {	146✔
281	type = h3IsValid(data[i][name] \|\| '') ? H3_ANALYZER_TYPE : type;	138!
282	break;	138✔
283	}
284	}
285	}
286
287	// quick check if string is hex wkb
288	if (type === AnalyzerDATA_TYPES.STRING) {	955✔
289	type = data.some(d => isHexWkb(d[name])) ? AnalyzerDATA_TYPES.GEOMETRY : type;	1,472✔
290	}
291
292	// quick check if string is wkt
293	if (type === AnalyzerDATA_TYPES.STRING) {	955✔
294	type = data.some(d => isWkt(d[name])) ? AnalyzerDATA_TYPES.GEOMETRY_FROM_STRING : type;	1,471!
295	}
296
297	return {	955✔
298	name,
299	id: name,
300	displayName: name,
301	format,
302	fieldIdx: index,
303	type: analyzerTypeToFieldType(type),
304	analyzerType: type,
305	valueAccessor: dc => d => {	17✔
UNCOV 306	return dc.valueAt(d.index, index);	×
307	}
308	};
309	});
310
311	return result;	119✔
312	}
313
314	/**
315	* pass in an array of field names, rename duplicated one
316	* and return a map from old field index to new name
317	*
318	* @param fieldOrder
319	* @returns new field name by index
320	*/
321	export function renameDuplicateFields(fieldOrder: string[]): {
322	allNames: string[];
323	fieldByIndex: string[];
324	} {
325	return fieldOrder.reduce<{allNames: string[]; fieldByIndex: string[]}>(	119✔
326	(accu, field, i) => {
327	const {allNames} = accu;	955✔
328	let fieldName = field;	955✔
329
330	// add a counter to duplicated names
331	if (allNames.includes(field)) {	955✔
332	let counter = 0;	2✔
333	while (allNames.includes(`${field}-${counter}`)) {	2✔
334	counter++;	1✔
335	}
336	fieldName = `${field}-${counter}`;	2✔
337	}
338
339	accu.fieldByIndex[i] = fieldName;	955✔
340	accu.allNames.push(fieldName);	955✔
341
342	return accu;	955✔
343	},
344	{allNames: [], fieldByIndex: []}
345	);
346	}

keplergl / kepler.gl / 21722643399

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