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Adding Watermarks to PDFs in Python with simple and efficient approach

In today’s digital age, the need to protect and personalize PDF documents is more crucial than ever. Whether you want to brand your documents or add a confidential watermark, Python provides a powerful and straightforward solution. In this blog, we’ll explore a simple Python script that utilizes the PyPDF2 and ReportLab libraries to effortlessly add watermarks to multiple PDF files.

Setting Up the Environment

Before diving into the script, make sure you have the required libraries installed. You can do this by running the following commands.

pip install PyPDF2
pip install reportlab

Understanding the Script

The entire script can be seen at the end. Let’s break down the key components of the script.

1. create_watermark() Function

   – This function uses the ReportLab library to generate a PDF containing a customizable watermark.

   – You can specify the watermark text, color, transparency, font, and rotation angle.

2. add_watermark() Function

   – The core function that adds the watermark to each page of the input PDF.

   – It uses PyPDF2 to merge the original PDF with the watermark PDF on each page.

3. delete_watermark_file() Function

   – A utility function to delete the temporary watermark PDF file after it has been merged with the input files.

4. Command Line Arguments

   – The script accepts two command line arguments:

     – `–path`: The path to the directory containing the PDF files to watermark.

     – `–watermark_text`: The text to be used as the watermark.

Here is the entire script.

import PyPDF2
import argparse
from reportlab.pdfgen import canvas
from reportlab.lib.units import inch
from reportlab.lib import colors
import os

def create_watermark(watermark_text, output_pdf):
    pdf = canvas.Canvas(output_pdf)
    pdf.translate(inch, inch) # move the current origin point(0,0) of the canvas by the current given horizontal and vertical distances
    pdf.setFillColor(colors.red, alpha=0.3) # set the font color with alpha value to adjust the transparency of watermark text
    pdf.setFont("Helvetica", 50) # set font and font size
    pdf.rotate(45) # rotate the canvas by 45 degrees
    pdf.drawCentredString(400, 100, watermark_text) # center the watermark text
    pdf.save()

def add_watermark(input_pdf, output_directory, watermark_pdf):
    base_filename = os.path.splitext(os.path.basename(input_pdf))[0]
    output_pdf = os.path.join(output_directory, f'{base_filename}.pdf')
    with open(input_pdf, 'rb') as file:
        pdf_reader = PyPDF2.PdfReader(file)
        pdf_writer = PyPDF2.PdfWriter()

        for page_num in range(len(pdf_reader.pages)):
            page = pdf_reader.pages[page_num]
            watermark_reader = PyPDF2.PdfReader(watermark_pdf)
            watermark_page = watermark_reader.pages[0]
            page.merge_page(watermark_page)
            pdf_writer.add_page(page)

        with open(output_pdf, 'wb') as output_file:
            pdf_writer.write(output_file)

def delete_watermark_file(watermark_pdf):
    if os.path.exists(watermark_pdf):
        os.remove(watermark_pdf)
        
if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument("--path", required=True, type=str, help="Path of the directory of file lists")
    parser.add_argument("--watermark_text", required=True, type=str, help="Text to be watermark")
    
    args = parser.parse_args()

    path = args.path
    watermark_text = args.watermark_text
    
    print('Processing.....')
    file_list = [file_name for file_name in os.listdir(path) if os.path.isfile(os.path.join(path, file_name))]

    output_directory = os.path.join(path, 'output_directory')
    if not os.path.exists(output_directory):
        os.makedirs(output_directory)
            
    watermark_pdf_file = os.path.join(path, 'watermark.pdf')
    create_watermark(watermark_text, watermark_pdf_file)
    for file_name in file_list:
        if not file_name == 'watermark.pdf':
            input_pdf_file = os.path.join(path, file_name)
            add_watermark(input_pdf_file, output_directory, watermark_pdf_file)
            
    delete_watermark_file(watermark_pdf_file)
    print('Done!')

Running the Script

To run the script, execute the following command.

python script_name.py --path /path/to/pdf/files --watermark_text "Your Watermark Text"

The script will process each PDF file in the specified directory, add the watermark, and save the watermarked files in a newly created ‘output_directory.’

Conclusion

With this Python script, you can easily add watermarks to your PDF documents, making them visually distinctive and secure. Whether you’re protecting sensitive information or branding your documents, this solution provides a quick and efficient way to enhance your PDF files. I would recommend to look into the used libraries in details and feel free to customize the script further to suit your specific requirements, such as adjusting colors, fonts, or rotation angles for the watermark.

Ref: https://pypdf2.readthedocs.io/en/3.0.0/index.html

Ref: https://docs.reportlab.com

Asahi



Google Map with Generative AI feature

Google Maps is set to revolutionize the way users discover new places with the introduction of a generative AI feature, as announced by the company. Leveraging large language models (LLMs), the feature analyzes a vast database of over 250 million locations on Google Maps and taps into contributions from over 300 million Local Guides. By employing a more conversational approach, users can make nuanced queries, such as seeking “places with a vintage vibe in SF,” and Maps will generate tailored recommendations for thrift shops, complete with categories, photo carousels, and review summaries.

Image Credit : Google

Designed to be intuitive, the generative AI feature goes beyond conventional search experiences. Users can engage in a more dynamic interaction by asking follow-up questions. For example, if the initial query relates to vintage shops and is followed by “How about lunch?” the AI will seamlessly transition to finding restaurants that align with the user’s preferences, creating a more personalized and fluid exploration experience.

Image Credit : google

Google emphasizes the inclusivity of the new feature, asserting its capability to generate recommendations for even the most niche or specific queries. Initially launching as an early access experiment in the U.S., the feature will be accessible to select Local Guides—Google’s community contributors—before extending to a wider user base in the near future. While the company hasn’t disclosed the countries that will receive the feature, the move aligns with Google Maps’ evolving role from a navigation tool to a comprehensive platform for discovering and exploring new places.

This generative AI feature follows Google’s recent updates to Maps, which transformed the platform into a more sophisticated search tool, incorporating AI-powered features like photo results and suggesting specific places in response to ambiguous queries. Google envisions this innovation as just the starting point, expressing its commitment to further enhancing Maps with generative AI, solidifying its position as a go-to destination for exploration and discovery.



[VR] VIVE Eye Tracking SDK のセットアップ方法

今回はUnity VRの開発環境で、VIVE Eye Tracking SDK のセットアップをおこなう方法について紹介します。
以下の手順をおこなうことによりHTC VIVE Pro Eyeのアイトラッキング機能のセットアップおよび開発環境の構築をおこなうことが可能になります。

続きを読む

AmazonLightsailとtailscaleを使ったお手軽固定IPの取得

Static IPをアタッチしたLightsailとLinuxが動作しているローカルPCをtailscaleのVPNで繋いで
手軽に固定IPを利用してみます。

続きを読む

Exploring different UUIDs versions

UUIDs, or Universally Unique Identifiers, are strings of characters used to uniquely identify information in computer systems. They play a crucial role in various applications, from databases to distributed systems. In this blog, we will explore the different versions of UUIDs, each designed for specific use cases and scenarios.

1. UUID Basics

Before delving into the versions, it’s essential to understand the basic structure of a UUID. A UUID is a 128-bit number typically represented as a 32-character hexadecimal string, separated by hyphens into five groups. The uniqueness of UUIDs is achieved by combining timestamps, node information, and random or pseudo-random numbers.

2. UUID Version 1: Time-based UUIDs

UUID version 1 is based on the current timestamp and the unique node (typically a MAC address) to ensure uniqueness. The timestamp component allows sorting and ordering of UUIDs based on their creation time. While effective, the reliance on a timestamp makes it less suitable for scenarios where privacy and security are top priorities.

3. UUID Version 2: DCE Security UUIDs

Version 2 is similar to Version 1 but includes additional information related to the POSIX UID/GID and POSIX timestamps. However, Version 2 is rarely used in practice, and Version 1 is more widely accepted.

4. UUID Version 3 and 5: Name-based UUIDs (MD5 and SHA-1)

These versions are generated by hashing a namespace identifier and a name using MD5 (Version 3) or SHA-1 (Version 5). The resulting hash is then combined with specific bits to form the UUID. While these versions ensure uniqueness within a given namespace, the use of MD5 and SHA-1 has raised security concerns due to vulnerabilities in these hashing algorithms.

5. UUID Version 4: Random UUIDs

Version 4 UUIDs are generated using random or pseudo-random numbers. This version prioritizes randomness over time-based information, making it suitable for scenarios where ordering is less critical, and privacy is a priority. The randomness is achieved through the use of a random number generator.

6. UUID Version 6: Modified Version 1

A newer addition, Version 6 combines the best of both Version 1 and Version 4. It includes timestamp information for ordering and randomness for improved security. This version is designed to address some of the privacy concerns associated with Version 1.

Conclusion

Understanding the different versions of UUIDs is essential for choosing the right type based on the specific requirements of your application. Whether you prioritize time-based ordering, security, or randomness, there’s a UUID version designed to meet your needs. As technology evolves, so do UUID specifications, ensuring that these unique identifiers continue to play a vital role in the ever-expanding digital landscape.

Asahi



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