pdfreader

Read text and parse tables from PDF files.

Supports tabular data with automatic column detection, and rule-based parsing.

Dependencies: it is based on pdf2json, which itself relies on Mozilla's pdf.js.

ℹ️ This module is meant to be run using Node.js only. It does not work from a web browser.

Summary:

• Installation, tests and CLI usage
• Raw PDF reading (incl. examples)
• Rule-based data extraction
• Troubleshooting & FAQ

Installation, tests and CLI usage

npm install pdfreader
cd node_modules/pdfreader
npm test
node parse.js test/sample.pdf

Raw PDF reading

The PdfReader class reads a PDF file, and calls a function on each item found while parsing that file.

An item object can match one of the following objects:

• null, when the parsing is over, or an error occured.
• {file:{path:string}}, when a PDF file is being opened.
• {page:integer, width:float, height:float}, when a new page is being parsed, provides the page number, starting at 1.
• {text:string, x:float, y:float, w:float, h:float...}, represents each text with its position.

Example:

new PdfReader().parseFileItems("sample.pdf", function(err, item) {
  if (err) callback(err);
  else if (!item) callback();
  else if (item.text) console.log(item.text);
});

Raw PDF reading from a PDF already in memory (buffer)

The PdfReader class reads a PDF file, and calls a function on each item found while parsing that file.

An item object can match one of the following objects:

• null, when the parsing is over, or an error occured.
• {file:{path:string}}, when a PDF file is being opened.
• {page:integer}, when a new page is being parsed, provides the page number, starting at 1.
• {text:string, x:float, y:float, w:float, h:float...}, represents each text with its position.

Example:

var fs = require("fs");
fs.readFile("sample.pdf", (err, pdfBuffer) => {
  // pdfBuffer contains the file content
  new PdfReader().parseBuffer(pdfBuffer, function(err, item) {
    if (err) callback(err);
    else if (!item) callback();
    else if (item.text) console.log(item.text);
  });
});

Example: parsing lines of text from a PDF file

Here is the code required to convert this PDF file into text:

var pdfreader = require("pdfreader");

var rows = {}; // indexed by y-position

function printRows() {
  Object.keys(rows) // => array of y-positions (type: float)
    .sort((y1, y2) => parseFloat(y1) - parseFloat(y2)) // sort float positions
    .forEach(y => console.log((rows[y] || []).join("")));
}

new pdfreader.PdfReader().parseFileItems("CV_ErhanYasar.pdf", function(
  err,
  item
) {
  if (!item || item.page) {
    // end of file, or page
    printRows();
    console.log("PAGE:", item.page);
    rows = {}; // clear rows for next page
  } else if (item.text) {
    // accumulate text items into rows object, per line
    (rows[item.y] = rows[item.y] || []).push(item.text);
  }
});

Fork this example from parsing a CV/résumé.

Example: parsing a table from a PDF file

Here is the code required to convert this PDF file into a textual table:

var pdfreader = require("pdfreader");

const nbCols = 2;
const cellPadding = 40; // each cell is padded to fit 40 characters
const columnQuantitizer = item => parseFloat(item.x) >= 20;

const padColumns = (array, nb) =>
  Array.apply(null, { length: nb }).map((val, i) => array[i] || []);
// .. because map() skips undefined elements

const mergeCells = cells =>
  (cells || [])
    .map(cell => cell.text)
    .join("") // merge cells
    .substr(0, cellPadding)
    .padEnd(cellPadding, " "); // padding

const renderMatrix = matrix =>
  (matrix || [])
    .map((row, y) =>
      padColumns(row, nbCols)
        .map(mergeCells)
        .join(" | ")
    )
    .join("\n");

var table = new pdfreader.TableParser();

new pdfreader.PdfReader().parseFileItems(filename, function(err, item) {
  if (!item || item.page) {
    // end of file, or page
    console.log(renderMatrix(table.getMatrix()));
    console.log("PAGE:", item.page);
    table = new pdfreader.TableParser(); // new/clear table for next page
  } else if (item.text) {
    // accumulate text items into rows object, per line
    table.processItem(item, columnQuantitizer(item));
  }
});

Fork this example from parsing a CV/résumé.

Rule-based data extraction

The Rule class can be used to define and process data extraction rules, while parsing a PDF document.

Rule instances expose "accumulators": methods that defines the data extraction strategy to be used for each rule.

Example:

var processItem = Rule.makeItemProcessor([
  Rule.on(/^Hello \"(.*)\"$/)
    .extractRegexpValues()
    .then(displayValue),
  Rule.on(/^Value\:/)
    .parseNextItemValue()
    .then(displayValue),
  Rule.on(/^c1$/)
    .parseTable(3)
    .then(displayTable),
  Rule.on(/^Values\:/)
    .accumulateAfterHeading()
    .then(displayValue)
]);
new PdfReader().parseFileItems("sample.pdf", function(err, item) {
  processItem(item);
});

Troubleshooting & FAQ

Is it possible to parse a PDF document from a web application?

Solutions exist, but this module cannot be run directly by a web browser. If you really want to use this module, you will have to integrate it into your back-end so that PDF files can be read from your server.

Cannot read property 'userAgent' of undefined error from an express-based node.js app

Dmitry found out that you may need to run these instructions before including the pdfreader module:

global.navigator = {
  userAgent: "node"
};

window.navigator = {
  userAgent: "node"
};

Source: express - TypeError: Cannot read property 'userAgent' of undefined error on node.js app run - Stack Overflow