Michael Bryan

Michael Bryan


PDF Processing with Python

PDF Processing with Python - As you know PDF processing comes under text analytics . Most of the Text Analytics Library or frameworks are designed in Python only .


Being a high-level, interpreted language with a relatively easy syntax, Python is perfect even for those who don’t have prior programming experience. Popular Python libraries are well integrated and provide the solution to handle unstructured data sources like Pdf and could be used to make it more sensible and useful

PDF is one of the most important and widely used digital media. used to present and exchange documents. PDFs contain useful information, links and buttons, form fields, audio, video, and business logic.

Why Python for PDF processing

As you know PDF processing comes under text analytics . Most of the Text Analytics Library or frameworks are designed in Python only . This gives a leverage on text analytics . One more thing you can never process a pdf directly in exising frameworks of Machine Learning or Natural Language Processing . Unless they are proving explicit interface for this . We have to convert pdf to text first.

Python Librairies for PDF Processing

As a Data Scientist , You may not stick to data format . PDFs is good source of data . Most of the organization release their data in PDFs only . As AI is growing , We need more data for prediction and classification . Hence ignoring PDFs as data source could be a blunder . Actually PDF processing is little difficult but we can leverage the below API for making it easier .

In this section, we will discover the Top Python PDF Library:


PDFMiner is a tool for extracting information from PDF documents. Unlike other PDF-related tools, it focuses entirely on getting and analyzing text data. PDFMiner allows one to obtain the exact location of text in a page, as well as other information such as fonts or lines. It includes a PDF converter that can transform PDF files into other text formats (such as HTML). It has an extensible PDF parser that can be used for other purposes than text analysis.


PyPDF2 is a pure-python PDF library capable of splitting, merging together, cropping, and transforming the pages of PDF files. It can also add custom data, viewing options, and passwords to PDF files. It can retrieve text and metadata from PDFs as well as merge entire files together.


Quite similar like above two mention . Apart from those similarity , pdfrw has its own USPs (Unique selling Points) . Actually the requirement of API depends on use case.


It is wrapper Implementation of PDFMiner . No API is perfect , There were few short coming in PDFMiner . Slate beautifully address them.

Setup Environment

**Step 1: **Select Version of Python to Install from Python.org .

**Step 2: **Download Python Executable Installer.

**Step 3: **Run Executable Installer.

**Step 4: **Verify Python Was Installed On Windows.

**Step 5: **Verify Pip Was Installed.

Step 6: Add Python Path to Environment Variables (Optional).

Step 7: Install Python extension for your IDE.

I am working with Python 3.7 in visual studio code. For more information about how to setup your environment and select your python interepter to start coding with VS Code, check*** ***Getting Started with Python in VS Code documentation.
** **Now you’ll be able to execute python scripts with your IDE.

**Step 8 **: Install pdfminer.six

pip install pdfminer.six

**Step 9 **: Install PyPDF2

pip install PyPDF2

Done! Now, you can start processing pdf documents with python.

Merging Multiple PDF Documents

Now that we have a bunch of PDFs, let’s learn how we might take them and merge them back together. One useful use case for doing this is for businesses to merge their dailies into a single PDF. I have needed to merge PDFs for work . One project that sticks out in my mind is scanning documents in. Depending on the scanner you have, you might end up scanning a document into multiple PDFs, so being able to join them together again can be wonderful.

When the original PyPdf came out, the only way to get it to merge multiple PDFs together was like this:

# Merging Multiple PDF Documents with Python 3.7 and PyPDF2
	import glob
	from PyPDF2 import PdfFileWriter, PdfFileReader

	def merger(output_path, input_paths):
	pdf_writer = PdfFileWriter()
	for path in input_paths:
	pdf_reader = PdfFileReader(path)
	for page in range(pdf_reader.getNumPages()):
	with open(output_path, 'wb') as fh:

	if __name__ == '__main__':
	paths = glob.glob('pdf_files_path/I*.pdf')
	#Retrieve all pdfs start with I
	merger('output_pdf_file_path/pdf_merger.pdf', paths)

Splitting Merged PDF Document

The PyPDF2 package gives you the ability to split up a single PDF into multiple ones, let’s find out how:

# Splitting Merged PDF Document with Python 3.7 and PyPDF2
import os
from PyPDF2 import PdfFileReader, PdfFileWriter
def pdf_splitter(path):
fname = os.path.splitext(os.path.basename(path))[0]
pdf = PdfFileReader(path)
for page in range(pdf.getNumPages()):
pdf_writer = PdfFileWriter()
output_filename = 'pdf_directory/{}_page_{}.pdf'.format(fname, page+1)
with open(output_filename, 'wb') as out:
print('Created: {}'.format(output_filename))

if __name__ == '__main__':
path = "Specify your pdf path here"

Extract Text from PDF

The PDFMiner library excels at extracting data and coordinates from a PDF. In most cases, you can use the included command-line scripts to extract text and images (<strong>pdf2txt.py</strong>).

The package includes the <strong>pdf2txt.py</strong> command-line command, which you can use to extract text and images. The command supports many options and is very flexible. Some popular options are shown below.

See the usage information for complete details

pdf2txt.py [options] filename.pdf
    -o output file name
    -p comma-separated list of page numbers to extract
    -t output format (text/html/xml/tag[for Tagged PDFs])
    -O dirname (triggers extraction of images from PDF into directory)
    -P password
pdf2txt.py [options] filename.pdf
    -o output file name
    -p comma-separated list of page numbers to extract
    -t output format (text/html/xml/tag[for Tagged PDFs])
    -O dirname (triggers extraction of images from PDF into directory)
    -P password

That’s right, you can even use the command to convert PDF to TXT! For example, say you want the TXT version of the first and third pages of your PDF, including images

pdf2txt.py -O myoutput -o myoutput/myfile.txt -t txt-p 1,3 myfile.pdf

If you are writing Python code and you don’t want to shell out to the command line with <strong>os.system</strong>or <strong>subprocess</strong>, you use the package as a library.

For example, to extract text from PDF you need:

# Extract Text from PDF with Python 3.7 and PDFMiner
	from pdfminer.pdfinterp import PDFResourceManager,PDFPageInterpreter
	from pdfminer.converter import TextConverter
	from pdfminer.layout import LAParams
	from pdfminer.pdfpage import PDFPage
	from io import BytesIO
	def pdf_to_text(path):
	manager = PDFResourceManager()
	retstr = BytesIO()
	layout = LAParams(all_texts=True)
	device = TextConverter(manager, retstr, laparams=layout)
	filepath = open(path, 'rb')
	interpreter = PDFPageInterpreter(manager, device)
	for page in PDFPage.get_pages(filepath, check_extractable=True):
	text = retstr.getvalue()
	return text

	if __name__ == "__main__":
	text = pdf_to_text("Specify your pdf path here")

#python #data-science

What is GEEK

Buddha Community

PDF Processing with Python

ahmed khemiri


Thanks a lot mate for sharing!
original article from here https://towardsdatascience.com/pdf-preprocessing-with-python-19829752af9f

Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt


Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.


Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

August  Larson

August Larson


Creating PDF Invoices in Python with pText


The Portable Document Format (PDF) is not a WYSIWYG (What You See is What You Get) format. It was developed to be platform-agnostic, independent of the underlying operating system and rendering engines.

To achieve this, PDF was constructed to be interacted with via something more like a programming language, and relies on a series of instructions and operations to achieve a result. In fact, PDF is based on a scripting language - PostScript, which was the first device-independent Page Description Language.

In this guide, we’ll be using pText - a Python library dedicated to reading, manipulating and generating PDF documents. It offers both a low-level model (allowing you access to the exact coordinates and layout if you choose to use those) and a high-level model (where you can delegate the precise calculations of margins, positions, etc to a layout manager).

We’ll take a look at how to create a PDF invoice in Python using pText.

#python #pdf #creating pdf invoices in python with ptext #creating pdf invoices #pdf invoice #creating pdf invoices in python with ptext

Art  Lind

Art Lind


Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

Art  Lind

Art Lind


How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.


In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips