puppeteer-table-parser
v2.2.0
Published
Library to make parsing website tables much easier!
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🕸 🕷 puppeteer-table-parser
Library to make parsing website tables much easier!
When you are using puppeteer
for scrapping websites and web application, you will find out that parsing tables consistently is not that easy.
This library brings you abstraction between puppeteer
and page context
.
This library solves the following issues:
- ✨ Parsing columns by their name.
- ✨ Respect the defined order of columns.
- ✨ Appending custom columns with custom data.
- ✨ Custom sanitization of data in cells.
- ✨ Group and Aggregate data by your own function.
- ✨ Merge data from two independent tables into one structure.
- ✨ Handles invalid HTML structure.
- ✨ Retrieve results as CSV or array of plain JS objects.
- ✨ And much more!
Installation
yarn add puppeteer-table-parser
npm install puppeteer-table-parser
// CommonJS
const { tableParser } = require('puppeteer-table-parser')
// ESM / Typescript
import { tableParser } from 'puppeteer-table-parser'
API
interface ParserSettings {
selector: string; // CSS selector
allowedColNames: Record<string, string>; // key = input name, value = output name)
headerRowsSelector?: string | null; // (default: 'thead tr', null ignores table's header selection)
headerRowsCellSelector?: string; // (default: 'td,th')
bodyRowsSelector?: string; // (default: 'tbody tr')
bodyRowsCellSelector?: string; // (default: 'td')
reverseTraversal?: boolean // (default: false)
temporaryColNames?: string[]; // (default: [])
extraCols?: ExtraCol[]; // (default: [])
withHeader?: boolean; // (default: true)
csvSeparator?: string; // (default: ';')
newLine?: string; // (default: '\n')
rowValidationPolicy?: RowValidationPolicy; // (default: 'NON_EMPTY')
groupBy?: {
cols: string[];
handler?: (rows: string[][], getColumnIndex: GetColumnIndexType) => string[];
}
rowValidator: (
row: string[],
getColumnIndex: GetColumnIndexType,
rowIndex: number,
rows: Readonly<string[][]>,
) => boolean;
rowTransform?: (row: string[], getColumnIndex: GetColumnIndexType) => void;
asArray?: boolean; // (default: false)
rowValuesAsArray?: boolean; // (default: false)
rowValuesAsObject?: boolean; // (default: false)
colFilter?: (elText: string[], index: number) => string; // (default: (txt: string) => txt.join(' '))
colParser?: (value: string, formattedIndex: number, getColumnIndex: GetColumnIndexType) => string; // (default: (txt: string) => txt.trim())
optionalColNames?: string[]; // (default: [])
};
Parsing workflow
- Find table(s) by provided CSS selector.
- Find associated columns by applying
colFilter
on their text and verify their count. - Filter rows based on
rowValidationPolicy
- Add extra columns specified in
extraCols
property in settings. - Run
rowValidator
function for every table row. - Run
colParser
for every cell in a row. - Run
rowTransform
function for each row. - Group results into buckets (
groupBy.cols
) property and pick the aggregated rows. - Add processed row to a temp array result.
- Add
header
column ifwithHeader
property istrue
. - Merge partial results and return them.
Examples
All data came from the HTML page, which you can find in
test/assets/1.html
.
Basic example (the simple table where we want to parse three columns without editing)
import { tableParser } from 'puppeteer-table-parser'
await tableParser(page, {
selector: 'table',
allowedColNames: {
'Car Name': 'car',
'Horse Powers': 'hp',
'Manufacture Year': 'year',
},
});
car;hp;year
Audi S5;332;2015
Alfa Romeo Giulia;500;2020
BMW X3;215;2017
Skoda Octavia;120;2012
Basic example with custom column name parsing:
import { tableParser } from 'puppeteer-table-parser'
await tableParser(page, {
selector: 'table',
colFilter: (value: string[]) => {
return value.join(' ').replace(' ', '-').toLowerCase();
},
colParser: (value: string) => {
return value.trim();
},
allowedColNames: {
'car-name': 'car',
'horse-powers': 'hp',
'manufacture-year': 'year',
},
})
car;hp;year
Audi S5;332;2015
Alfa Romeo Giulia;500;2020
BMW X3;215;2017
Skoda Octavia;120;2012
Basic example with row validation and using temporary column.
import { tableParser } from 'puppeteer-table-parser'
await tableParser(page, {
selector: 'table',
allowedColNames: {
'Car Name': 'car',
'Manufacture Year': 'year',
'Horse Powers': 'hp',
},
temporaryColNames: ['Horse Powers'],
rowValidator: (row: string[], getColumnIndex) => {
const powerIndex = getColumnIndex('hp');
return Number(row[powerIndex]) < 250;
},
});
car;year
BMW X3;2017
Skoda Octavia;2012
Advanced example:
Uses custom temporary column for filtering. It uses an extra column with custom position to be filled on a fly.
import { tableParser } from 'puppeteer-table-parser'
await tableParser(page, {
selector: 'table',
allowedColNames: {
'Manufacture Year': 'year',
'Horse Powers': 'hp',
'Car Name': 'car',
},
temporaryColNames: ['Horse Powers'],
extraCols: [
{
colName: 'favorite',
data: '',
position: 0,
},
],
rowValidator: (row: string[], getColumnIndex) => {
const horsePowerIndex = getColumnIndex('hp');
return Number(row[horsePowerIndex]) > 150;
},
rowTransform: (row: string[], getColumnIndex) => {
const nameIndex = getColumnIndex('car');
const favoriteIndex = getColumnIndex('favorite');
if (row[nameIndex].includes('Alfa Romeo')) {
row[favoriteIndex] = 'YES';
} else {
row[favoriteIndex] = 'NO';
}
},
asArray: false,
rowValuesAsArray: false
});
favorite;year;car
NO;2015;Audi S5
YES;2020;Alfa Romeo Giulia
NO;2017;BMW X3
Optional columns
Sometimes you can be in a situation where some if
your columns are desired, but they are not available in a table.
You can easily add an exception for them via optionalColNames
property.
import { tableParser } from 'puppeteer-table-parser'
await tableParser(page, {
selector: 'table',
allowedColNames: {
'Car Name': 'car',
'Rating': 'rating',
},
optionalColNames: ['rating']
});
Grouping and Aggregating
import { tableParser } from 'puppeteer-table-parser'
await tableParser(page, {
selector: '#my-table',
allowedColNames: {
'Employee Name': 'name',
'Age': 'age',
},
groupBy: {
cols: ['name'],
handler: (rows: string[][], getColumnIndex) => {
const ageIndex = getColumnIndex('age');
// select one with the minimal age
return rows.reduce((previous, current) =>
previous[ageIndex] < current[ageIndex] ? previous : current,
);
},
}
});
For more, look at the test
folder! 🙈