@dictadata/pdf-junction 0.9.x

PdfJunction implements a junction for reading tabular data in PDF documents. PdfJunction is a storage plugin for use with @dictadata/storage-junctions and related projects @dictadata/storage-tracts ETL command line utility and @dictadata/storage-node API Server.

The plugin uses the pdf-data-parser module to parse the PDF documents.

Installation

npm install @dictadata/storage-junctions @dictadata/pdf-junction

Plugin Initialization

Import the Storage Junctions library and the PDF Junction plugin. Then register PDF Junction with the Storage Junctions' Storage module. This will register PDF Junction for use with storage model "pdf".

const { Storage } = require("@dictadata/storage-junctions");
const PdfJunction = require("@dictadata/pdf-junction");

Storage.Junctions.use("pdf", PdfJunction);

Creating an instance of PDFJunction

Create an instance of PDFJunction class.

let junction = Storage.activate(smt, options);

SMT

PdfJunction constructor takes an SMT, Storage Memory Trace, with the address of the data source. SMT can be a string or object. The string format is "model|locus|schema|key" which for PDFJunction is "pdf|url or local path|document filename|*".

// SMT string
let smt = "pdf|./path/|mydoc.pdf|*"

// SMT object
let SMT = {
  model: "pdf",
  locus: "http://server.org/path/",
  schema: "mydoc.pdf",
  key: "*" // all rows
}

PdfJunction Options

PdfJunction constructor takes an options object with the following fields.

{string|regexp} heading - Section heading in the document after which the parser will look for tabular data; optional, default: none. The parser does a string comparison or match looking for first occurrence of heading value in the first cell of rows, row[0]. If not specified then data output starts with first row of the document.

{string|regexp} stopHeading - Section heading or text in the document after the tabular data; optional, default: none. The parser does a string comparison or regexp match looking for occurrence of stopHeading value in the first cell of rows. If not specified then data output stops on value of cells or the end of document.

{integer} cells - Minimum number of cells in tabular data; optional, default: 1. After heading string is found parser will look for the first row that contains at least cells count of cells. The parser will output rows until it encounters a row with less than cells count of cells.

{boolean} newlines - Preserve new lines in cell data; optional, default: false. When false newlines will be replaced by spaces. Preserving newlines characters will keep the formatting of multiline text such as descriptions. Though, newlines are problematic for cells containing multiword identifiers and keywords that might be wrapped in the PDF text.

{Boolean} artifacts - Parse artifacts content, default: false. Artifacts content specifies objects on the page such as table/grid lines and headers/footers. Grid lines do not have text content, but headers and footers might. If page headers and footers show up in output try the pageHeader and pageFooter options.

{Integer} pageHeader - Height of page header area in points, default: 0. Content within this area of the page will not be included in output. Use about 16 points per line including blank lines.

{Integer} pageFooter - Height of page footer area in points, default: 0. Content within this area of the page will not be included in output. Use about 16 points per line including blank lines.

{Boolean} repeatingHeaders - Indicates if table headers are repeated on each page, default: false. The table headers will be compare to the first row on each subsequent page. If found they will be removed from the output.

{Integer} lineHeight - Approximate line height ratio based on font size; default 1.67. The parser extracts font size from the pdf content. The line height ratio maybe used when comparing the position of content items on the page.

{boolean} trim - trim whitespace from output values, default: true.

Streaming Usage

The following example creates an instance of PdfReader and collects streamed data into an array. In this case the storage construct is an object representing a row of cells from the PDF document. PdfReader is derived from Node.js stream Readable. So the reader can be the source of any Node.js pipeline.

  async retrieveData() {
    let response = [];

    let junction = Storage.activate(smt, options);
    let reader = junction.createReader();

    reader.on('data', (construct) => {
      response.push(construct);
    })
    rs.on('end', () => {
      console.log('End of data.');
    });
    rs.on('error', (err) => {
      console.error(err);
    });

    await stream.finished(reader);

    return response;
  }

Using PdfJunction plugin with Storage-Tracts ETL

PdfJunction can be used from the command line, batch file or task schedular via the Storage-Tracts ETL command line utility.

Install Storage-Tracts

Install Storage-Tracts in NPM's global workspace. This will allow you to run from any folder using the command "etl" or "storage-etl".

npm -g install @dictadata/storage-tracts

Storage_Tracts ETL Utility

The ETL utility takes two parameters as shown below. See the Storage-Tracts documentation for full details.

etl [-t tractsFile] [tractName]

ETL Tracts File

An ETL Tracts file is a JSON object describing the storage source and storage destination. Each top level property is a tract. For PDF files you will need to also specify the plugin.

{
  "config": {
    "plugins": {
      "junctions": {
        "@dictadata/pdf-junction": [ "pdf" ]
      }
    }
  },
  "transfer": {
    "action": "transfer",
    "origin": {
      "smt": "pdf|./test/data/input/|foofile.pdf|*",
      "options": {
        "heading": "pdf section heading",
        "cells": 7,
        "repeatingHeaders": true
      }
    },
    "terminal": {
      "smt": "json|./test/data/output/|foofile.json|*"
    }
  }
}

Examples

Hello World

HelloWorld.pdf is a single page PDF document with the string "Hello, world!" positioned on the page. The parser output is one row with one cell.

Create an ETL tract file named mytracts.json with one tract name hello_world.

{
  "hello_world": {
    "action": "transfer",
    "origin": {
      "smt": "pdf|./test/data/input/pdf/|helloworld.pdf|*",
    },
    "terminal": {
      "smt": "json|./test/data/output/pdf/|helloworld.json|*"
    }
  },
  "plugins": {
    "junctions": {
      "dictadata/pdf-junction": [ "pdf" ]
    }
  }
}

Run the ETL command.

etl -t mytracts.json hello_world

The output is save in file helloworld.json which contains the data rows from the pdf document.

[
  { "Greeting": "Hello, world!" }
]

See the pdf-data-parser project for more complex examples.