7 Best PDF Scraper 2023: How to Scrape PDF Files With Python

Published on: October 3, 2022
Last Updated: October 3, 2022

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In a hurry?
The best PDF scraper in 2023, as found in our independent testing, is Apify!


If you have been looking for information related to scraping data from PDF files, you have come to the right place.

In this article, we will talk about some of the best PDF scrapers you can find in the market; additionally, we will also talk about creating your own PDF scraper if you know how to code. 

When it comes to the availability of data, there is no standard format. The data of interest can be accessible in any format.

As a data scientist, your job is to extract the data from a particular format and present it in a format that you can use for your research work. 

In most cases, data obtained from databases and on web pages are very easy to extract and use; however, getting data from PDF files is not an easy task.

If you want to know how to collect data from PDF files in an automated manner, then this article is for you.,

We will also be discussing how to make this process faster and more efficient for you. 

Extracting data from PDF files is known as PDF scraping.

For this process, you will have to use a computer bot called a PDF scraper that will load the content of a PDF file and then make use of a parser to scan and locate the data of interest you want to scrape.

Once the data has been collected, you can use or store it in the PDF scraper if you are using a customized one. 

There are some simple technologies like the OCR (Optical Object Recognition) that can help identify the content of a PDF document.

We will be learning in detail how to extract data from PDF files; additionally, we will also talk about how you can create a PDF scraper with the help of Python. 

Best PDF Scrapers 2023

Of course, not every person who wants to scrape PDF files for data is a programmer. Some are just regular people who do not know how to code.

Thankfully, you will find a large number of computer programs that can help you extract data from PDF files.

While there are many good applications available in the market, we will talk only about the best ones, which includes:

  1. Apify – 🏆 Winner!
  2. Bright Data
  3. Amazon Textract
  4. Nanonets
  5. DocParser
  6. FineReader PDF
  7. Docsumo

1. Apify

Apify

Apify is an excellent PDF scraper, because at the end of the day, they want to make sure that the web is working for you, and not the other way around.

They said they’re really good for helping their clients automate everything that they do manually in a web browser, and the best part is that you can run their features at scale.

This means that if you’re trying to gather a lot of data right now, or just a little bit, their features are going to be able to make it work.

They talk about being your one-stop shop when it comes to data extraction, web scraping, and more.

You can either browse their tools that they have already made up for you, or you can talk to them about making a customized solution.

2. Bright Data

Bright Data Data Collector

This service should definitely one of the best when it comes to being a PDF scraper because they can help you with all of your needs and they can help you in a manner that is safe and secure.

They say they can help you with data collection, and they can also help you with data sets that are made up already, which means that you’re going to be able to effortlessly scrape all the information you need from PDF format, and you can even switch up this format as well and export this data into a different format.

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You can either get started with them straight away, or you can ask for a demo, which means that you can test out their features really well before you commit to any of them.

One of the standout features when it comes to this PDF scraper is the fact that they have access to proxies as well, meaning that you’re going to be able to cover your tracks, and make sure that everything you do online is safe and secure.

3. Amazon Textract

  • Cost: $139 for a single-user license
  • Availability of free trials: None
  • Format for the data output: TSV, XML, JSON, Excel, CSV, TXT, etc. 
  • Platforms supported: Desktop
Amazon Textract

The Amazon Textract is quite an amazing tool that you can use to extract data from PDF files and other formats as well. The service will automatically extract handwriting and texts from any document and can also identify dense text, forms, and tables with the help of intelligent AI.

The best part here is that you do not even have to learn anything about coding. 

Amazon Textract utilizes the OCR technology for identifying handwriting and printed texts in any PDF documents. Additionally, it is very easy to understand and use this tool.

As a free user, you will be able to analyze 1K pages for three months each, thereby bringing the total to 3K pages. 

4. Nanonets

  • Cost: $0.0015 for a single page
  • Availability of free trials: Monthly 100 pages
  • Format for the data output: Support available for multiple formats
  • Platforms supported: Web
Nanonets

Nanonets is an amazing service and one of the best in the market if you are looking for tools that can help extract data from PDF files.

An interesting aspect of Nanonets is that apart from helping you extract data from PDF files, you can also make use of the embedded OCR technology to extract written data from the images. 

Even if the PDF documents are not structured, you will still be able to extract data from them. Today, it is not uncommon to see PDF files not following any standards; hence, most of these files are not structured.

Most tools are unable to read and extract data from unstructured PDF files; however, Nanonets can do so very easily and effectively. 

5. DocParser

  • Cost: $39 for 100-500 pages per month
  • Availability of free trials: 30-150 pages per month
  • Format for the data output: XML, Excel, CSV
  • Platforms supported: Web
DocParser

As the name suggests, DocParser is a document parser that will extract data from any kind of document, including PDF files.

However, let us learn in detail the types of documents from which you can extract data – DocParser can extract data from PDF files, word documents, as well as images. 

One curious feature of DocParser is that the tool makes use of specific templates to streamline the data collection process and make it easier.

Some other types of templates include bank statements, purchase orders, invoices, etc. 

Learning how to use DocParser is very easy – the first thing you need to do is upload the documents. Once done, simply define the riles and the data of interest that you want to scrape.

Next, just tap on the Extraction button, and the files will be systematically downloaded. 

When it comes to the format of the exported data, you can utilize popular formats like XML, CSV, and Excel. You can also make use of cloud applications like Zapier.

6. FineReader PDF

  • Cost: $199 one-time payment
  • Availability of free trials: Yes
  • Format for the data output: JSON, Excel, CSV
  • Platforms supported: Android, iOS, Mac, and Windows
FineReader PDF

FineReader PDF is easily one of the oldest PDF data extraction tools in the market today. The company aims to help digitize office documents.

Apart from this, this tool can also help in data extraction from PDF files. The service can be availed for various platforms like Android, iOS, Mac, and Windows. 

If you do not want to install any kind of software on your device, you can access FineReader PDF via your web browser. As for pricing, you simply need to pay once to use this data extraction tool.

Based on the information available on its official website, FineReader PDF has been downloaded more than 100 million times; as of now, the company has more than 17K corporate clients from all parts of the world. 

7. Docsumo

  • Cost: $25 per month 
  • Availability of free trials: 
  • Format for the data output: XML, JSON, CSV
  • Platforms supported: Web
Docsumo

While it is placed last, it is definitely not the least. Docsumo is one of the top PDF scrapers that you can find in the market. This tool makes use of smarter technology to process all sorts of documents, including PDF files.

All you need to do is upload the document to the tool, define the extraction rules, and review the data that is then extracted. Additionally, the tool also has API integration support.

Docsumo can easily automate the decision-making process to extract data from unstructured documents. Thanks to the embedded OCR technology, you will be able to extract content from the documents as well as the images.

Often seen as an alternative to manual data re-entry, this automated process saves a lot of time, is less error-prone, and is more efficient. 

How to Scrape PDF Files With Python

As a programmer, designing your own PDF scraper is quite easy if you have the know-how of coding.

One of the best things about creating your own PDF scraper is that you will no longer have to deal with any type of block.

However, does this imply that you will face absolutely no problem with using your own PDF scraper? Let us learn more about it in this section.

One important aspect of parsing is that you need to mind the parsing area, particularly if the data of interest is hidden under a heap of content.

For instance, let us consider that you want to scrape all the email addresses that are hidden in the text – the most prominent issue here is that you will have to use a regular expression. 

Overall, extracting data from a PDF file requires more skills than you would need for simply copying the file content.

You will also have to be skilled in terms of text processing so that you can parse the data that you are looking for. 

For Python programmers, there are several amazing libraries available for them so that they can scrape various PDF files.

For instance, you can simply make use of the PyPDF2 Library for simple data; as for data in tabular form, you can use the tabula-py library. 

PyPDF2 library

No matter what library you end up using, you will still require some expertise in processing the text with the help of regular expression if you want to scrape hidden data.

You will find the Regular Expression module embedded in the standard Python library.

In the next section, we have provided you with a script that will help you understand the ways of using PyPDF2 library on PDF documents for data extraction:

import requests

import PyPDF2



x = requests.get("http://codex.cs.yale.edu/avi/db-book/db4/slide-dir/ch1-2.pdf").content

with open("my_pdf.pdf", 'wb') as my_data:

    my_data.write(x)


open_pdf_file = open("my_pdf.pdf", 'rb')

s = PyPDF2.PdfFileReader(open_pdf_file)

print(s.getPage(1).extractText())

Final Thoughts 

From the above, you now understand that you can easily scrape data from even unstructured PDF documents.

While some of the above-mentioned tools make use of conventional methods to scrape the data of interest from PDF documents, it is recommended that you use the ones that are fitted with OCR technology so that you will be able to extract data more effectively. 

The five tools mentioned above are just a handful out of the many applications you can find to scrape data from PDF files.

Yes, there are many other tools that can help you do the same. However, the five above-mentioned tools are considered the best in the market and the most trusted as well.

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Written by Jason Wise

Hello! I’m the editor at EarthWeb, with a particular interest in business and technology topics, including social media, privacy, and cryptocurrency. As an experienced editor and researcher, I have a passion for exploring the latest trends and innovations in these fields and sharing my insights with our readers. I also enjoy testing and reviewing products, and you’ll often find my reviews and recommendations on EarthWeb. With a focus on providing informative and engaging content, I am committed to ensuring that EarthWeb remains a leading source of news and analysis in the tech industry.
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